Author: headspin

Salesforce, a CRM platform, is integral to many businesses’ operations. As organizations frequently update their Salesforce environments to leverage new features, fix bugs, or improve performance, maintaining the system’s integrity becomes crucial. This is where Salesforce regression testing comes into play. This blog delves into Salesforce regression testing, its benefits, best practices, and how the HeadSpin Platform can assist in this crucial process.

What is Salesforce Regression Testing?

Salesforce regression testing is a critical quality assurance process designed to ensure that recent changes or updates to the Salesforce environment do not negatively impact the existing functionalities of the system. This type of testing involves re-running a subset of previously executed tests to verify that the system still behaves as expected after modifications.

Critical Aspects of Salesforce Regression Testing

• Re-Running Existing Tests: The core of Salesforce regression testing is to re-run tests that have already been executed. These tests were initially created to verify the correct functioning of various features and workflows within the Salesforce environment. By re-running these tests, teams can confirm that the previously verified functionalities work correctly after the changes.
• Detection of Unintended Consequences: Code changes, even minor ones, can sometimes lead to unexpected issues elsewhere in the application. Salesforce regression testing helps identify unintended consequences by thoroughly testing the application, ensuring that new changes do not break existing functionalities.
• Ensuring System Integrity: The primary goal of Salesforce regression testing is to maintain the overall integrity and stability of the Salesforce environment. By regularly performing regression tests, organizations can ensure that their Salesforce applications remain reliable and perform as expected, even after multiple updates and enhancements.
• Supporting Continuous Integration and Delivery: In modern software development practices, continuous integration (CI) and continuous delivery (CD) are essential for rapid and efficient development cycles. Salesforce regression testing plays a vital role in CI/CD pipelines by providing automated testing capabilities that can be triggered with every code change. This ensures that any issues introduced by new changes are detected and addressed early in the development process.

Types of Salesforce Regression Testing

• Automated Regression Testing: This involves using automated testing tools to execute regression test cases. Automation significantly speeds up the testing process, ensuring consistency and reducing human error. Tools like Selenium, Provar, and the HeadSpin Platform are commonly used to automate Salesforce regression tests.
• Manual Regression Testing: Although less common due to its time-consuming nature, manual regression testing can be performed for complex test scenarios that may not be easily automated. Manual testing involves testers executing test cases manually to verify that the application behaves as expected.

Benefits of Salesforce Regression Testing

Ensures Stability and Reliability

Regularly performing Salesforce regression testing is essential for maintaining the stability and reliability of your Salesforce environment. As Salesforce environments undergo frequent updates and modifications, new changes may inadvertently disrupt existing functionalities. Regression testing mitigates this risk by verifying that these updates do not introduce new defects or break existing features. This proactive measure helps maintain a robust and reliable system that end-users can trust.

Enhances User Experience

A smooth and bug-free user experience is crucial for user satisfaction and retention. By locating and fixing bugs before they reach end-users, Salesforce regression testing is pivotal in enhancing the overall user experience. It ensures that users can continue relying on the system for their daily tasks without encountering unexpected issues, increasing productivity and satisfaction.

Facilitates Continuous Improvement

Salesforce is a dynamic platform with frequent updates, new feature rollouts, and enhancements. Salesforce regression testing supports continuous improvement by ensuring that each new change is thoroughly tested and does not negatively impact existing functionalities. This approach allows organizations to continuously innovate and enhance their Salesforce environment while maintaining high-quality standards.

Saves Time and Resources

Manual testing can be time-consuming and resource-intensive, especially when dealing with repetitive test cases. Automated Salesforce regression testing can significantly reduce the time and effort required for testing. Automation tools can execute tests quickly, allowing testers to focus on critical tasks.

Improves Test Coverage

Salesforce regression testing helps improve test coverage by ensuring that all critical functionalities are re-tested after each update. This comprehensive approach reduces the risk of overlooked issues and ensures that every part of the system functions correctly. Improved test coverage leads to higher-quality software and reduces the likelihood of post-release defects.

Enhances Collaboration and Communication

Regression testing often involves collaboration between teams, such as development, testing, and operations. By incorporating Salesforce regression testing into the development process, organizations can foster better communication and collaboration among teams. This approach ensures everyone is in sync with the system’s status and potential issues, leading to more effective problem-solving and decision-making.

Supports Compliance and Risk Management

Many industries have strict regulatory requirements that necessitate rigorous testing and validation of software systems. Salesforce regression testing helps organizations comply with these regulations by providing documented evidence of thorough testing and validation processes. Additionally, it supports risk management.

Best Practices for Salesforce Regression Testing

Ensuring the effectiveness of Salesforce regression testing requires a strategic approach. Below are detailed best practices that can help streamline and enhance the regression testing process:

Prioritize Test Cases

Identifying and prioritizing critical test cases is crucial. Focus on the following areas:

• Core Business Processes: Ensure that the most critical functionalities of your Salesforce environment are thoroughly tested. These include key workflows, customer interactions, and transaction processes.
• Frequently Used Features: Prioritize testing for features used frequently by end-users, as issues in these areas can significantly impact user satisfaction.
• Recent Changes: Pay special attention to areas of the application that have undergone recent changes or updates.

Automate Where Possible

Automation is a key component of efficient Salesforce regression testing. Consider the following:

• Test Automation Tools: Utilize tools like Selenium, Provar, TestComplete, and the HeadSpin Platform to automate repetitive and time-consuming test cases. These tools can execute tests quickly and accurately, reducing the risk of human error.
• Reusable Test Scripts: Develop reusable test scripts that can be easily maintained and updated. This reduces the effort required to adapt to new changes in the Salesforce environment.
• Regular Updates: Continuously update your automation scripts to align with the latest changes in your Salesforce environment.

Maintain a Comprehensive Test Suite

A comprehensive and well-maintained test suite is essential for effective Salesforce regression testing. Consider the following practices:

• Regular Review: Regularly review and update your test cases to ensure they remain relevant and comprehensive.
• Coverage: Ensure your test suite covers all critical functionalities and potential integration points within your Salesforce environment.
• Documentation: Maintain clear and detailed documentation for your test cases. This will help team members understand and execute tests.

Use Realistic Test Data

Using realistic test data is vital for accurate Salesforce regression testing. Follow these guidelines:

• Production-Like Data: Use data sets that closely mirror your production environment to uncover issues that might not be evident with artificial data.
• Data Privacy: Ensure that test data is anonymized and complies with privacy regulations to protect sensitive information.
• Variety: Include a variety of data scenarios to test different use cases and edge cases, ensuring comprehensive test coverage.

Integrate with CI/CD Pipelines

Integrating Salesforce regression testing with CI/CD pipelines ensures continuous testing and early detection of issues. Implement the following practices:

• Automated Triggers: Set up automated triggers to run regression tests with every code change, ensuring that issues are located and addressed early.
• Continuous Feedback: Provide continuous feedback to developers, enabling them to address any issues that arise during regression testing quickly.
• Pipeline Integration: Utilize tools like Jenkins, GitLab CI, or CircleCI to integrate regression testing into your CI/CD pipeline, streamlining the testing process.

Leverage Cloud-Based Testing

Cloud-based testing platforms offer numerous advantages for Salesforce regression testing. Consider the following:

• Scalability: Cloud platforms provide scalable resources, allowing you to run extensive test suites without significant hardware investments.
• Accessibility: Cloud-based testing environments are accessible from anywhere, enabling distributed teams to collaborate effectively.
• Cost Efficiency: Cloud platforms often offer pay-as-you-go models, making it cost-effective to scale testing efforts based on demand.

These best practices will help organizations enhance the efficiency and effectiveness of their Salesforce regression testing efforts, ensuring a stable and reliable Salesforce environment that meets user expectations and business requirements.

How the HeadSpin Platform Can Help with Advanced Regression Testing

The HeadSpin Platform offers comprehensive support for Salesforce regression testing, enhancing the efficiency and effectiveness of your testing efforts. Here’s how HeadSpin can assist:

Automated Testing

HeadSpin provides robust automation capabilities, allowing you to automate a wide range of Salesforce test cases. This ensures consistent and accurate test execution, saving time and reducing manual effort.

Real Device Testing

With HeadSpin, you can test real devices and environments, ensuring your Salesforce application performs optimally across different platforms and conditions.

Performance Monitoring

HeadSpin’s advanced performance monitoring tools provide detailed insights into the performance of your Salesforce environment. By tracking key performance metrics, you can ensure that updates and changes do not degrade the system’s performance.

Seamless Integration

HeadSpin integrates seamlessly with popular CI/CD tools, facilitating continuous testing and ensuring that Salesforce regression testing is integral to your development workflow.

Conclusion

Salesforce regression testing is a critical practice for maintaining your Salesforce environment’s stability, reliability, and performance. With these best practices and advanced tools like the HeadSpin Platform, organizations can ensure that their Salesforce applications continue to meet user expectations and business requirements.

Article Source:

This article was originally published on:

https://www.headspin.io/blog/salesforce-regression-testing-guide

Achieving stability and reliability in applications hinges on comprehensive testing before release. The rise of cloud-native technologies and automated testing in recent years has enabled faster and more thorough testing processes. Automated testing has become a crucial component of the Agile development pipeline, especially in the context of Continuous Integration and Continuous Deployment practices, which aim to streamline development and testing for enhanced competitiveness and quality-driven outcomes. A range of tools are used to implement CI/CD, with Jenkins emerging as the most popular solution. 

This blog explores the various features and benefits of Jenkins test automation, shedding light on how this powerful tool can facilitate and enhance the testing process.

What is Jenkins Test Automation?

Jenkins Test Automation is automating test cases in CI/CD pipelines using Jenkins. By integrating with various testing tools and frameworks, Jenkins testing allows for seamless execution of automated tests, ensuring that every code change is verified through a consistent and efficient testing process. As part of test automation, Jenkins testing helps run tests like unit, integration, and regression tests, significantly improving software quality.

Why Should Developers and QA Engineers Utilize Jenkins?

Jenkins test automation is a renowned open-source automation server within the CI/CD pipeline. It enables seamless building, testing, and deployment of applications, ensuring high-quality software. With its flexible plugin architecture and extensive ecosystem, Jenkins integrates effortlessly with various tools and services, empowering users with automated testing capabilities. Its extensibility allows for customization through plugin creation, making Jenkins test automation a versatile solution.

Jenkins’ automated testing capabilities allow tests to be configured to run automatically every time new code is pushed to the repository, streamlining the testing process and ensuring consistent quality control. To enable the Continuous Integration/Continuous Deployment (CI/CD) pipeline in Jenkins, the Pipeline comes into play, providing a suite of plugins to support the implementation as well as integration of continuous delivery pipelines. Using the Pipeline DSL (domain-specific language), developers can express the steps of their CI/CD process as code, resulting in a straightforward configuration file that can be added to the version control repository and tracked for any changes made to it. By utilizing Jenkins for automated testing in the CI/CD pipeline, development teams can enhance the efficiency and reliability of software development processes.

With various plugins available, Jenkins is designed to optimize the software development process, making it more efficient.

Advantages of using Jenkins

● QA Automation: Jenkins can automate several tasks in the software development process, including building, testing, and deploying code. By automating QA testing processes, Jenkins can minimize the risk of errors and enhance the speed and efficiency of the development process. Below are a few details on Jenkins test automation:

1. Runs Automated Test Suites: Jenkins comes with plugins for various test frameworks, such as Selenium, Cucumber, and Appium, that enable automated test suites to be executed in CI pipelines.
2. Summarizes the results: Most Jenkins plugins provide a summarized overview of the test results, which can be accessed and reviewed on a user-friendly HTML page.
3. Provides Trends: Jenkins also tracks the test results over time and visualizes them in a trend graph, providing stakeholders with a better understanding of test performance and progress.
4. Displays details on Test Failures: Jenkins meticulously logs test results, including detailed information on test failures, to facilitate efficient troubleshooting by developers and testers.

● Customization: Jenkins is highly customizable, with a wide range of plugins available that enable users to tailor Jenkins to their specific needs. This makes it possible to integrate Jenkins with various tools and processes, allowing organizations to build a custom software development workflow.

● Collaboration: Jenkins can be configured to send notifications to team members and stakeholders when specific events occur, such as the completion of a build or the detection of an error. This helps to facilitate collaboration and improve communication within the development team.

● Scalability: Jenkins is designed for easy scalability and can handle a large number of builds and deployments. This makes it suitable for use in organizations of all sizes, from small startups to large enterprises.

What Are the Challenges of Using Jenkins that SREs Should Keep in Mind?

Jenkins, despite being a popular tool for automated testing in CI/CD pipelines, comes with its own set of limitations. Here are some of them:

• With a large number of contributors, Jenkins has a multitude of plugins for single-tool integration, which can make it challenging for users to select the right one.
• Although Jenkins has plugins that support Docker integration, it still needs to catch up in this domain compared to other tools.
• Jenkins does not offer a cloud-based service, and users must rely on cloud service providers like AWS, GCP, Azure, Cloudbees, etc.
• With a complex configuration, Jenkins has a steep learning curve, and new users might find it overwhelming.
• Plugins in Jenkins need to be customizable, limiting flexibility for users.
• Lack of authentication/authorization rules and options in Jenkins.
• Most community-driven plugins in Jenkins need clear documentation on how to use them.

When to use Jenkins for Test Automation?

Jenkins is best used for test automation when establishing a CI/CD pipeline that integrates testing into the software development process; Jenkins is best used for test automation. Here are key scenarios where Jenkins Testing should be implemented:

• Frequent Code Changes: Jenkins is ideal when your team makes frequent code changes and needs to ensure that every change passes through automated testing.
• Continuous Integration: Jenkins Testing is highly beneficial for projects that require continuous integration, where code is merged several times a day, and automated tests help catch bugs early.
• Cross-platform Testing: When your application needs to be tested on different platforms or devices, Jenkins can efficiently automate tests across multiple environments.
• Scaling Test Automation: Jenkins is perfect for scaling test automation, especially when integrating with tools like Selenium or Appium for automated functional testing.

To implement Jenkins Testing effectively, you must have a well-defined set of automated test cases and integrate them into the CI/CD pipeline.

How Should Testers Approach Continuous Integration Using Jenkins

In spite of its limitations, Jenkins remains the most effective tool for implementing automated testing in CI/CD pipelines. The extensive range of plugins and the strong community support make it a powerful ally for automation efforts, regardless of the software being tested.

As already discussed, Jenkins boasts a plugin system that enables easy job building and third-party service integrations with cloud providers. Despite this, Jenkins is simply an additional layer above the OS of the build agent, meaning any command that the agent’s command line supports can be executed via Jenkins. This makes Jenkins an orchestrator of commands within a pipeline.

To get started with Jenkins, you could begin with the shell plugin, which allows defining the commands for the pipeline. Common commands for automated testing within a CI/CD pipeline might include compiling the application, running various tests (unit, integration, or functional), and generating an application artifact deployable across different environments.

If you’re working with a .NET application, the necessary commands for automated testing might include:

dotnet build

dotnet test

dotnet publish

At its core, a Jenkins pipeline is a collection of plugins that facilitates implementing and integrating continuous delivery pipelines within Jenkins. This is done by using a Jenkinsfile, a text file stored in source control that defines the pipeline.

A Jenkins pipeline follows a structured approach comprising stages and steps which include:

● General

Specify the project name, along with a description. This is where you can add any job parameters and configure log rotation.

● Source Code Management

Input the URL of your source code repository in the Jenkins CI server to start the automated testing process.

● Build Triggers

Define when to complete a job and schedule it, based on a specific timeline or after a change is made for Continuous Testing.

● Build Environment

Choose options based on the environment in which you execute the build, such as setting up Continuous Monitoring, choosing when to abort the build, and adding time-out actions.

● Build

This step is critical for automated testing and Continuous Integration/Deployment. Select the option you need, depending on which plugins you install and use.

● Post-build Actions

Configure how the results of a job would be reported, such as sending email updates on the job status and setting up notifications for Continuous Monitoring.

How HeadSpin Empowers Organizations to Optimize Automated Continuous Testing

The HeadSpin Platform empowers development and QA teams with comprehensive continuous testing capabilities across various technologies. It focuses on the following:

• Automated Testing: Support all significant testing automation frameworks, such as Appium, Selenium, XCTest, Espresso, and more.
• CI/CD Integration: Seamless test automation for new builds by automatically analyzing builds, executing tests, and providing performance regression insights.
• Continuous Monitoring: 24/7 access to any device running any application on any network worldwide for continuous quality assurance.
• Parallel Testing: HeadSpin provides a user-friendly interface along with integrations and automation features, enabling the execution of multiple tests simultaneously. This capability enhances scalability and expands the test coverage. Additionally, the platform enables the testing of mobile applications on devices located in various global locations, accommodating different time zones and network conditions. By facilitating parallel testing, HeadSpin ensures the integrity of the system.

With the HeadSpin plugin, every session is associated with a build_id, enabling tracking devices used during a build and providing end-of-build statistics based on HeadSpin performance data.

The Platform supports mobile, web, IoT, and 5G applications, offering functional, load, and performance testing. Throughout the software development lifecycle, HeadSpin facilitates continuous testing and monitoring with its main features aligned with the critical components of continuous testing:

• Automated User Journeys: Integration of popular test automation platforms like Appium or Selenium to automate various customer user journeys.
• Performance Regression: Comparison of performance across builds, locations, networks, and devices to identify performance variations over time.
• API Usage Monitoring: Monitoring of application usage of APIs or tracking the impact of third-party APIs on application performance.

Wrapping Up

Jenkins test automation works seamlessly with CI methodologies and expediting the testing process. With its comprehensive features and continuous evolution, Jenkins offers companies a powerful, all-in-one tool for efficient test automation. By embracing Jenkins, teams gain confidence through quick result visibility and enjoy the numerous advantages it brings to their testing efforts.

HeadSpin facilitates seamless integrations with various CI/CD tools, enabling automated tests on multiple devices and browsers across the globe through its extensive real-device cloud.

Article Source:

This article is originally published on:

https://www.headspin.io/blog/how-to-conduct-efficient-jenkins-automated-testing

Testing is an integral part of the software development process. It helps developers identify and fix problems in their code before it becomes a problem for users. By testing your code, you can ensure that it is stable and reliable.

There are many different types of testing, but Cucumber testing is one of the most popular approaches. Cucumber testing is a behavior-driven development (BDD) technique. BDD is an approach to software development that focuses on defining the behavior of an application as concrete examples before writing the code. This helps developers to understand how the application should behave. It also helps developers to collaborate with stakeholders to build more correct and more accessible applications.

What is Cucumber Testing?

Cucumber was developed to make it easier for developers and testers to work together on behavior-driven development projects. It is based on the principle that tests should be written in a language everyone on the team can understand.

By using Cucumber testing, teams can avoid misunderstandings and reduce the need for lengthy discussions about the code. Cucumber tests allow us to keep writing readable test code for humans to encourage collaboration than traditional code-based tests. This makes them more flexible and easier to maintain.

Benefits of Cucumber Testing

Cucumber automation testing is a software testing process that deals with an application’s behavior. It tests applications as a behavior-driven development (BDD) style. Cucumber tests are written in a simple, natural language that anyone can understand, even people who are not technical experts.

The primary purpose of Cucumber automation testing is to help teams communicate better about the behavior of an application. By writing tests in a shared language, everyone on the team can understand them. This helps avoid misunderstandings and reduces the need for lengthy discussions about the code.

Cucumber tests are also easier to change than traditional code-based tests for collaborators. Because they are written in a natural language, they are less likely to break when the code changes. This makes them more flexible and easier to maintain.

Some of the benefits of Cucumber testing include:

• Improved communication among team members
• Reduced need for lengthy discussions about the code
• Easier to change than traditional code-based tests
• More flexible and easier to maintain

Cucumber Testing Vs. Traditional Testing

Cucumber testing is a behavior-driven development (BDD) approach to testing software. This means that tests are written in a simple, natural language that anyone can understand. In contrast, traditional testing approaches are typically code-based. This makes them more challenging to change and maintain.

Another difference between Cucumber and traditional testing is that Cucumber tests are designed to be less likely to break when the code changes. This makes them more flexible and easier to maintain over time.

Getting Started with Cucumber Testing

The best way to get started with Cucumber automation testing is to find a tutorial or guide that walks you through the process. There are many great resources available online that can help you get started.

Once you understand how Cucumber automation testing works, you can start writing your tests. Cucumber tests are written in a simple, natural language called Gherkin. You can learn more about Gherkin by reading the Cucumber documentation. Test code behind the Gherkin is written in proper programming languages for the project.

How Does Cucumber Testing Work?

If you’re working on a behavior-driven development (BDD) project, you may want to use Cucumber automation testing to help with communication and collaboration. Cucumber automation testing is a software testing process that deals with an application’s behavior. It is used to test applications written in a BDD style.

Cucumber tests are written in a simple, natural language that anyone can understand. This makes them ideal for teams who want to improve communication and avoid misunderstandings.

To use Cucumber testing for your project, you must set up a few things first.

1. Install the Cucumber command-line tool.
2. Create a file with a .feature extension. This file should contain a description of the feature you want to test and the individual scenarios you want to test.
3. Write your scenarios in Gherkin syntax. Each scenario should include the Given, When, and Then steps.
4. Run your tests using the Cucumber command-line tool.

When you’re ready to start writing your tests, you’ll need to create a file with a .feature extension. This file should contain a description of the feature you want to test and the individual scenarios you want to test. Each method should be written in Gherkin syntax and include Given, When, and Then steps.

Once you have created your .feature file, you can run your tests using the Cucumber command-line tool. This tool will parse your .feature file and execute your scenarios.

Writing Cucumber Tests

Let’s say you’re working on a project to create a new website. You’ve been asked to add a feature that allows users to sign up for an account. To do this, you’ll need to write a Cucumber test.

First, you’ll need to create a file with a .feature extension. This file should contain a description of the feature you want to test and the individual scenarios you want to test. Each scenario should be written in Gherkin syntax and include Given, When, and Then steps.

Here’s an example of what your .feature file might look like:

Feature: Sign up for an account

Scenario: Successful signup

Given I am on the signup page

When I fill out the form with my information

Then I should see a confirmation message

This .feature file contains a scenario that tests the signup feature. The system includes the Given, When, and Then steps that describe what should happen when the user tries to sign up for an account.

Once you have created your .feature file, you can run your tests using the Cucumber command-line tool. This tool will parse your .feature file and execute your scenarios.

You can also use other tools to help write and run your Cucumber tests. For example, you can use a tool like Cucumber Studio to help manage your project’s Cucumber tests.

Types of Cucumber Tests

Cucumber testing can be used to test a variety of different types of applications. Here are some examples of the different kinds of Cucumber tests you can use:

Acceptance tests: These tests help you determine if an application meets the requirements the customer or client sets. Acceptance tests are typically written in Gherkin syntax.

Functional tests: These tests help you determine if an application is working as expected. Functional tests are typically written in a programming language like Ruby or JavaScript.

Unit tests: These tests help you determine if a specific unit of code is working as expected. Unit tests are typically written in a programming language like Ruby or JavaScript.

Integration tests: These tests help you determine if different parts of an application are working together as expected. Integration tests are typically written in a programming language like Ruby or JavaScript.

When to Use Cucumber Tests

Cucumber automation testing is an excellent tool for teams who want to improve communication and avoid misunderstandings. Cucumber automation testing can be used to test a variety of different applications.

Different types of Cucumber tests include acceptance tests, functional tests, unit tests, and integration tests. You can use Cucumber testing when you want to test an application’s functionality or to ensure that different parts of an application are working together as expected.

Best Practices for Writing Effective Cucumber Tests

Here are best practices to help you write effective Cucumber tests:

• Use a tool like Cucumber Studio to help manage your project’s Cucumber tests.
• Write your scenarios in Gherkin syntax.
• Include Given, When, and Then steps in your scenarios.
• Make sure your scenarios are clear and concise.
• Run your tests using the Cucumber command-line tool.
• Use other tools to help write and run your Cucumber together as expected in the background keywords to avoid duplication.
• Use tags to organize and run specific scenarios.

Interpreting Test Results

Once you have written your Cucumber tests, you can run them using the Cucumber command-line tool. This tool will parse your .feature file and execute your scenarios.

The Cucumber command-line tool will generate a report showing your tests’ results. The report will show which scenarios passed and which scenarios failed.

You can also use other tools to help write and run your Cucumber tests. For example, you can use a tool like Cucumber Studio to help manage your project’s Cucumber tests.

An example test report for Cucumber looks like this:

Feature: login

To access the site

As a user

I need to be able to log in

Scenario: Successful Login

  Given I am on the login page

  When I fill in “username” with “test”

  And I fill in “password” with “test”

  And I click on the “Login” button

  Then I should see the “Welcome” page

Scenario: Failed Login

  Given I am on the login page

  When I fill in “username” with “test”

  And I fill in “password” with “wrong password”

  And I click on the “Login” button

  Then I should see the “Error” page

Two scenarios (1 passed, one failed)

Eight steps (4 passed, four failed)

0m1.146s

In this report, you can see which scenarios passed and which scenarios failed. You can also see the steps that were executed for each scenario.

The report helps debug your Cucumber tests. It can also help you understand why a particular test might have failed.

Cucumber Testing Challenges and How to Solve Them

There are a few common problems that can occur when writing Cucumber tests. Here are some tips to help you avoid these problems:

• Make sure your scenarios are clear and concise. This will help ensure that your tests are easy to understand and maintain.
• Use tags to organize and run specific scenarios. This will help you keep your Cucumber tests organized and ensure that only the scenarios you want to run are executed.
• Use the background keywords to avoid duplication. This keyword can be used to define steps that should be run before each scenario in a feature file.
• This can help avoid duplication and make your scenarios easier to read.
• Ensure that your .feature files are located in the correct directory. Cucumber will look for .feature files in the directory where the Cucumber command is run.
• Make sure that your .feature files are located in this directory, or you will not be able to run your tests.

These tips should help you avoid common problems when writing Cucumber tests. If you are still having trouble, many resources are available online to help you troubleshoot your issues.

How Cucumber Integrates with HeadSpin

HeadSpin provides a platform for running Cucumber tests. This platform can run your Cucumber tests on real devices or in the cloud.

The HeadSpin platform provides various features to help you run your Cucumber tests. For example, you can use the HeadSpin platform to:

• Tag your scenarios so that they can be run together or separately
• View reports showing the results of your Cucumber tests
• Integrate with other tools such as Jira and Slack
• You can then schedule your tests to run at specific times or tag your scenarios so that they can be run together or separately. The HeadSpin platform will provide you with reports showing the results of your Cucumber tests.
• You can also integrate the HeadSpin platform with other tools such as Jira and Slack.

Enhancing your Cucumber tests with features like data tables, screenshots, and more

You can enhance your Cucumber tests by adding features like data tables, screenshots, and more. These features can help you make your tests more robust and easier to understand.

Data tables: Data tables can be used to provide input data for your Cucumber tests. Data tables can be defined in your .feature files or can be external files.

You can use data tables to test different input values or run the same scenario with varying data sets.

Screenshots: Screenshots can be taken automatically when a Cucumber test fails. These screenshots can help you debug your tests and understand why they might have failed.

You can configure Cucumber to take screenshots automatically by setting the ‘screenshot’ option in your Cucumber.yml file.

HTML reports: HTML reports can be generated to show the results of your Cucumber tests. These reports can be used to share the results of your tests with others.

You can generate HTML reports using the ‘html_report’ formatter in your Cucumber.yml file.

JSON reports: JSON reports can be generated to show the results of your Cucumber tests. These reports can be used to share the results of your tests with others or to integrate with other tools.

You can generate JSON reports using the ‘json_report’ formatter in your Cucumber.yml file.

XML reports: XML reports can be generated to show the results of your Cucumber tests. These reports can be used to share the results of your tests with others or to integrate with other tools.

You can generate XML reports using the ‘xml_report’ formatter in your Cucumber.yml file.

All these features are explained in detail below:

Data Tables

Using data tables is one way to make your Cucumber tests more robust. Data tables allow you to test your application with multiple sets of data.

For example, you could use a data table to test a login feature with a different username and password combinations. To use a data table, you must define the header row and the data rows in your .feature file.

The header row defines the variable names used in the data rows. The data rows contain the actual data used in the test.

Here is an example of a data table:

Scenario Outline: Login feature

Given I am on the login page

When I enter my username and password

Then I should be logged in

Examples:

| username | password |

| user1 | pass1 |

| user2 | pass2 |

| user3 | pass3 |

In this example, the Scenario Outline defines a login feature that will be tested with three different data sets. The first set of data is defined in the Examples section.

This section contains a table with two columns: username and password. The first row in the table defines the variable names that will be used in the remaining rows.

The second and third rows contain the actual data that will be used in the test. When this scenario is run, the login feature will be tested three times with different combinations of username and password.

Screenshots

Another way to enhance your Cucumber tests is to take screenshots. Screenshots can help debug purposes or for creating reports.

You need to use the embed method to take a screenshot in Cucumber. The embed method takes a screenshot and embeds it in the HTML report.

Here is an example of how to use the embed method:

Scenario: Login feature

Given I am on the login page

When I enter my username and password

Then I should be logged in

And I take a screenshot

def take_screenshot

embed(“screenshot.png”, “image/png”)

end

In this example, the take_screenshot method takes a screenshot and embeds it in the HTML report. The method takes a screenshot of the login page and saves it as a png file.

You can view the screenshot in the HTML report that Cucumber generates.

Generating Reports

Cucumber can generate reports in various formats such as HTML, JSON, and XML. You need to use the –format option followed by the desired report format to generate a report.

For example, to generate an HTML report, you would use the following command:

Cucumber –format HTML

This command would generate an HTML report in the current directory. The report would contain information about the scenarios that were run and whether they passed or failed.

You can also generate a JSON report using the –format JSON option. This report will contain information about the scenarios and their results.

The JSON report would be saved in the current directory.

You can generate an XML report using the –format XML option. This report will contain information about the scenarios and their results.

The XML report would be saved in the current directory.

Integrating with Other Tools

Cucumber can be integrated with other tools such as Jira and Slack. To integrate Cucumber with Jira, you need to use the Cucumber-JVM library.

This library allows you to create Cucumber reports in Jira’s native format. To use this library, you need to add it to your project’s dependencies.

Once you have added the dependency, you must configure Cucumber to use the formatter. You can do this by adding the following line to your Cucumber.properties file:

Cucumber.formatter = io.Cucumber.jvm.formatter.JiraFormatter:output

This line tells Cucumber to use the Jira formatter and output the report to the current directory.

To integrate Cucumber with Slack, you need to implement posting results to Slack via the Slack API or use a published slack notification library. This library allows you to create Cucumber reports in Slack’s native format.

To use this library, you need to add it to your project’s dependencies. Once you have added the dependency, you must configure Cucumber to use the formatter.

You can do this by adding the following line to your Cucumber.properties file:

Cucumber.formatter = io.Cucumber.formatter.SlackFormatter:output

This line tells Cucumber to use the Slack formatter and output the report to the current directory.

The Bottom Line

Cucumber testing is a great way to test your web applications. Following the tips in this guide, you can avoid common problems and get the most out of Cucumber automation testing. The HeadSpin platform provides an easy way to run your Cucumber tests on real devices.

With HeadSpin, you can quickly test your web applications on various devices and browsers. HeadSpin platform provides an easy way to run your Cucumber tests on real devices or in the cloud. Sign up for a HeadSpin account today and start running your Cucumber tests.

Article Source:

This article was originally published on:

https://www.headspin.io/blog/cucumber-testing-a-complete-guide

Unit, integration, and functional testing are crucial components of software application testing. Each of these employs a distinct and unique process to test the application. However, the most important remains functional testing and functional regression testing. Unit or integration testing cannot replace this, either by itself or collectively. While unit testing involves testing individual modules of an application, isolated integration testing checks if different modules are working together as a group. Finally, functional testing checks whether the system operates the way it is supposed to.

Together, these constitute an application that is bug-free and smooth for the end-user. Functionality is related to integration tests. The latter is performed only when the former has yielded desired results. However, successful automated functional testing signifies that the entire app is running smoothly.

Unit testing

Unit testing involves testing applications at a unit level. It checks single components. You can optimize ROI (return on investment) if your codebase runs multiple unit tests with fewer integration tests and even fewer functional tests. Since the unit is the smallest part of an application, they are easier to write and quicker to execute. Usually, these tests are written and performed by software developers themselves. The primary aim here is to match the requirements to the unit’s behavior. This kind of testing is usually done before integration testing using white box testing techniques. Some of the most popular unit testing tools used for different languages are JUnit of Java Framework, PHPUnit of PHP framework, and NUnit of .Net framework.

Unit testing has several benefits, for instance:

• It checks whether or not there is correct output for valid input. 
• It also checks for failures that occur with invalid input. 
• It finds issues and bugs in the early stages to resolve them faster. It also reduces overall project costs. 
• Since unit testing tests small pieces of code and isolated functions, the issues it spots are independent of other test cases. 
• It makes resolving issues at a later stage easier by simplifying unit test cases and making the very act of testing code easy.
• Unit testing helps to save time and cost and is also easy to maintain.

Integration testing

Integration testing, as mentioned before, tests if the different parts of a system can work together and how well they work in synthesis. Various modules of such an ecosystem are merged to facilitate integration testing procedures. The purpose of this is to check the overall performance and reliability. This is performed on modules that have already undergone unit testing. It then defines if the combination of these elements can provide the desired output or not.

There are three types of approaches to integration testing as are as follows:

The Big Bang Approach

• Here, the modules are integrated and tested as a whole if the entire system is ready for such an integration. This is different from system testing. While system testing is for the ecosystem, integration testing checks only the modules. The Big Bang Approach lets you test everything simultaneously, thereby preserving resources. However, it could be challenging to identify specific errors.   

The Top-Down Approach

• Here, different modules or units are combined is tested using a top-to-bottom approach. First, the units are tested individually by writing test STUBS. Lower levels are then integrated in sequential order until the last one is compiled and tested. Experts believe that it is the most organic way of organizing a test because it is similar to the way things happen in real-life situations. The primary issue is that functionality is constantly tested at the end. It could mean going back and fixing issues through functional regression testing.

The Bottom-Up Approach  

Modules are tested from the bottom to the topmost level in the bottom-up approach. Simulator programs called DRIVERS facilitate this process. The bottom-up approach helps to detect bugs at lower levels. It enables the team to function as expected.

Functionality testing 

Automated functional testing is a black-box testing technique that ensures the overall operability of the application. This checks if a desirable output is generated out of a specific input. Test cases are then written based on the requirements and scenarios and then implemented. The number of tests can vary based on the nature of the software. Each test case comprises the test summary, prerequisites, input steps, test data, expected output, and notes (if any).

The two forms of automated functional testing are as follows:

• Requirement-based: The test cases are created based on the app’s demands.
• Business scenario-based: The tests are customized to align with the business strategy. 

Functional regression testing tests, or rather re-tests applications when new and improved features are added, and functions are modified for existing applications. It also checks if the older attributes and functionalities work well with the upgrades. While functional testing can assure all operations are working flawlessly, functional regression testing comes into play only when the team has published a new build that aims to fix bugs or debug new updates.

The benefits of functional regression testing include the following:

• It plays an integral role in agile environments where every sprint is crucial. Functional regression testing makes sure that previous and current releases all work together seamlessly.
• It helps to identify bugs in the software. Regression tests make software resistant to discrepancies. Such procedures provide support to testing and QA teams to deliver fast results.
•  It helps retain the integrity of an application despite new additions.
• Regressive testing helps to shorten the overall testing lifecycle. 
• These tests help achieve a higher Customer Satisfaction Index (CSI) and can eventually be considered crucial for expanding business. 
• They help reduce calls for incidents in production. Thus, the cost of the overall project reduces.

The main differences between the three 

The differences between unit testing, integration testing, and functionality testing can be divided into the following categories:

• Purpose: Unit testing checks the most basic unit of the application, each module, individually. Integration testing checks two or more modules combined to perform tasks. Functional automation testing tests the behavior of the application when it functions as a whole. 
• Complexity: Unit testing is simple in its language and is easy to write since it includes the smallest of codes. While integration testing is slightly more complex compared to unit tests, functionality testing constitutes the most complicated of the batch.
• Testing techniques: Unit testing involves white box testing techniques. Functionality regression testing consists of only black-box testing techniques. Integration testing uses both black and white box techniques- also called grey-box testing. 
• Errors covered: Unit tests can cover issues that occur with frequency in different modules. It nullifies the chance of any problem going unnoticed. In the case of integration testing, the errors covered include bugs that occur when integrating various modules. Issue escape is a rare occurrence. For automated functionality testing, issues that hinder the performance of an application are identified. Scenario-based problems are also tested here. There is the most chance of issue escape here because the list of tests to be run is infinite.

A focus on functional vs. unit testing

When examining functional vs. unit testing, it’s crucial to understand their distinct roles within the software testing lifecycle. Unit testing concentrates on testing individual components or functions of the software in isolation. Developers use unit tests to ensure specific parts of the code, such as methods or classes, work as expected. These tests are highly granular, quick to execute and help catch bugs early in development, ensuring the internal logic of the code functions correctly without dependencies.

In contrast, functional testing evaluates the software’s performance by testing its functionality in real-world scenarios. It assesses the application’s workflow, interactions, and behavior to ensure the software meets user requirements. Unlike unit tests, functional tests simulate user experiences to ensure the software operates as intended.

The difference between functional vs. unit testing lies in their scope: unit testing ensures the correctness of individual components, while functional testing verifies the application’s overall functionality. When choosing between functional vs. unit testing, it’s essential to recognize that both testing types are necessary to deliver reliable, high-quality software. However, they serve different purposes at various stages of development.

Functional Testing Vs. Unit Testing Vs. Integration Testing

Criteria	Functional Testing	Unit Testing	Integration Testing
Purpose	Validate that the entire application works as intended according to user requirements.	Ensure that individual units or functions work correctly.	Verify that different units work together as expected.
Complexity	High, as it involves the entire system and user scenarios.	Low, focusing on small, isolated pieces of code.	Medium, as it involves multiple units and their interactions.
Testing Technique	Black-box testing.	White-box testing.	Both black-box and white-box testing.
Errors Covered	Logical, workflow, and system-level errors.	Syntax, logical, and isolated functional errors.	Interface errors, data flow issues, and interaction problems.

Conclusion

To conclude, we must understand that these processes are interconnected and correlated. Unit testing is imperative to ensure that your software is working seamlessly. Unit testing facilitates flawless paths and lines of code. This, in turn, must be followed by integration tests to make sure that separate units can work together cohesively. Finally, all of the above must be followed by functional tests to deliver a polished app. Functional regression testing also needs to be performed if the application in question is an existing software where updates are being implemented.

Article Source:

This article was originally published on:

https://www.headspin.io/blog/unit-integration-and-functional-testing-4-main-points-of-difference

Mobile app testing frameworks are essential for automating the testing of native apps, reducing test execution time, and identifying bugs before app deployment. As mobile applications progress from development to testing, it is crucial to ensure they are fit for user delivery.

In this blog, we’ll explore the best mobile app testing frameworks for 2024. This curated list aims to assist mobile app developers in making informed decisions for more effective app development. Choosing the most appropriate framework can take time and effort, given the differences in features among various options. This blog seeks to streamline selection by providing insights into popular frameworks, their features, and relevant details.

What is Mobile Automation Testing?

Mobile Automation Testing uses automation tools and scripts to perform testing tasks on mobile applications. It enables repetitive, time-consuming, and complex test scenarios to be executed automatically, ensuring accuracy, speed, and scalability. By using automation tools for mobile testing, teams can simulate user interactions, validate functionalities, and assess the performance of mobile apps across devices and platforms without manual intervention. This approach helps identify bugs early, improve app quality, and reduce the overall time to market.

When Should You Go for Mobile Test Automation?

Mobile test automation is particularly beneficial when repetitive test cases must be executed across multiple devices or operating systems. Consider opting for automation tools for mobile testing in the following cases:

• When you need to run the same tests frequently due to app updates.
• When your app requires extensive testing across various device configurations.
• When manual testing becomes too time-consuming or prone to errors.
• When you want to achieve faster test execution to meet tight deadlines.
• When you aim to improve test coverage and accuracy by automating complex test scenarios.

Incorporating automation tools for mobile testing can significantly enhance the efficiency of your testing process, ensuring your mobile app delivers a seamless user experience.

The Importance of Mobile App Testing in Development

The mobile landscape is dominated by two major players: Android and iOS. However, within each operating system lies a vast array of device variations, including screen sizes, resolutions, hardware specifications, and custom user interfaces from various manufacturers.

Proper testing ensures that your app remains stable and functional and delivers a high-quality experience across the diverse range of devices potential users use.

Categories of Mobile App Testing Frameworks

Mobile app testing frameworks are categorized into three main types:

1. Strictly Android testing frameworks.
2. Strictly iOS testing automation frameworks.
3. Cross-platform testing frameworks applicable to both Android and iOS.

To make it easier to navigate, we have divided this blog into three sections, aligning each with the respective mobile app testing frameworks category.

Choosing the Right Mobile App Testing Tool

Mobile app testing ensures high-quality user experiences across diverse devices and operating systems. With the competitive landscape of the mobile app industry, selecting the right mobile testing automation tool is essential.

Consider the following when choosing a tool:

• Testing Needs: Determine your app’s type (native, hybrid, or web) and scope (functionality, performance, or security) to match the tool’s features to your requirements.
• Platform Compatibility: Ensure the tool supports your target operating systems (Android, iOS, or both) and offers compatibility with various devices, including real devices and emulators.
• Features and Integrations: Look for a tool that aligns with your team’s scripting language, provides robust reporting and analytics, and integrates seamlessly with your development tools and CI/CD pipeline.
• Budget Considerations: Choose between open-source or commercial tools based on your budget. Consider licensing and pricing models, and ensure the tool offers adequate support and training.
• Trial Before Commitment: Always test the tool before committing. Utilize free trials or demos and seek feedback from other users through online reviews and forums.

By carefully evaluating these factors, you can select a mobile testing tool that meets your needs and helps deliver exceptional apps to your users.

Popular Android Test Automation Frameworks

Several popular automation tools for mobile testing are available, each with unique features and advantages. Here, we’ll explore some of the best options:

Espresso

Key Features:

• Developed by Google, Espresso is known for its high performance and simplicity.
• Offers quick integration with Android Studio.
• Based on JUnit, it is easy for testers to become familiar with JUnit.
• Capable of identifying idle main threads to ensure efficient test execution.

Selendroid

Key Features:

• Utilizes Selenium 2.0 for writing test scripts.
• Supports testing on Android emulators, real devices, and Selenium Grid.
• Offers advanced user interaction support APIs, such as swipe and drag-and-drop.
• Comes with an advanced inspector for quick UI element detection.

Robotium

Key Features:

• Focuses on simplicity, versatility, and speed.
• Supports testing for both native and hybrid Android applications.
• Facilitates black-box testing, allowing testers to focus on testing without knowing the source code.
• Handles multiple Android activities automatically.

MonkeyRunner

Key Features:

• Enables control of Android applications outside the Android code.
• Uses Jython language, implementing Python using Java, for easy test development.
• Can be attached to multiple emulators or real devices simultaneously.
• Provides a complete start-to-end test script for an Android application.

Each framework offers unique advantages, so choosing the right one depends on your specific testing needs and preferences.

Top iOS App Testing Frameworks

For iOS app testing, several specialized frameworks offer unique features:

XCTest

Key Features:

• Primary iOS automation testing framework, offering unit, performance, and UI testing.
• Compatible with Objective-C and Swift.
• Provides control over continuous integration and UI interface enhancement.

Earlgrey

Key Features:

• Developed by Google for native iOS UI automation testing.
• Supports both white and black-box testing.
• Offers strong synchronization capabilities with UI and network requests.
• Integrates smoothly with Xcode.

OCMock

Key Features:

• It focuses on testing with mock objects and providing partial, dynamic, and stub mocks.
• Offers detailed documentation and examples.
• Uses Objective-C, making it easy for iOS developers.
• Active open-source framework with a strong community.

KIF

Key Features:

• iOS automation framework for UI testing.
• Builds tests using XCTest targets.
• Integrates directly into Xcode.
• Mimics user actions for realistic testing scenarios.

Detox

Key Features:

• Focuses on end-to-end testing to eliminate flakiness.
• Writes test cases in Javascript.
• Tests the app after running it on the simulator/emulator.
• Integrates with CI tools like Travis and is test runner independent.

These iOS testing frameworks cater to various testing needs, offering a range of features for iOS app developers and testers.

Cross-Platform Testing Frameworks for iOS and Android

Various cross-platform frameworks provide versatility and user-friendly options for testing mobile apps on both iOS and Android platforms:

Calabash

Key Features:

• Open-source framework for testing mobile apps on Android and iOS.
• Uses Ruby language for test execution, with optional Cucumber integration for non-coders.
• Supports real devices and emulators.
• Highly stable and suitable for behavior-driven development (BDD).
• Easily integrates with continuous integration tools like Jenkins.

Appium

Key Features:

• A versatile framework for automating mobile apps on iOS and Android.
• Supports multiple programming languages and frameworks, allowing testers to use familiar tools.
• Promotes code reusability by using the same APIs for multiple platforms.
• Large and active community for support.
• Works with real devices, emulators, and simulators.
• Doesn’t require compiling the Application in the Appium environment, ensuring compatibility with the development environment.
• Easy integration with CI/CD tools.

These frameworks offer robust solutions for testing mobile applications across both iOS and Android platforms, catering to the needs of testers and developers alike.

Critical Considerations for Choosing a Mobile Test Automation Framework

Selecting the appropriate mobile test automation framework is daunting due to the multiple options available. To make an informed decision, consider the following criteria:

• Platform Compatibility: Ensure the framework supports the mobile app platform and its versions, whether iOS, Android, or both.
• Integration Capabilities: The framework should seamlessly integrate with other tools and your CI/CD pipeline to facilitate efficient testing processes.
• Ease of Use: Opt for a framework with a user-friendly interface and support for programming languages that your team is familiar with, enhancing productivity and collaboration.
• Device Compatibility: Verify that the framework supports test execution on various devices, accommodating different screen sizes, resolutions, and hardware specifications.
• Reporting and Analytics: Look for a framework that offers robust reporting and analytics features, enabling testers to monitor progress and identify potential issues effectively.
• Support: Ensure the framework has an active community of users, developers, or experts who can support and assist, enhancing reliability and troubleshooting capabilities.

Best Practices for Automated Mobile App Testing

To ensure effective automated mobile app testing, engineering teams should adhere to the following best practices:

1. Make Application Testable: Collaborate with testing teams to set guidelines that make applications ready for testing. For example, developers should assign unique IDs to elements for easy testing.
2. Avoid Overusing XPath: While XPath can be useful for navigating elements, excessive usage can impact performance—order selectors so that more efficient locators like ID are prioritized over XPath.
3. Utilize Accessibility IDs: Instead of relying heavily on XPath, use accessibility ID locators where possible. Setting accessibility IDs on elements makes them more testable and expands the testing scope.
4. Consider View States: Set up the Application’s view state to avoid duplication in test cases. This ensures that testing begins at the necessary point, saving time and resources.
5. Emulators and Simulators: While useful for initial testing, emulators, and simulators have limitations in replicating real user conditions—test apps in less-than-ideal circumstances to ensure satisfactory user experiences.

Following these best practices can lead to more efficient and effective automated mobile app testing, resulting in higher-quality applications.

Streamlining Mobile App Testing with HeadSpin

In the competitive realm of automated app testing tools, HeadSpin shines with its unique features tailored to enhance the testing experience.

• Global Device Cloud: Developers can test their apps on thousands of real devices across various locations, ensuring comprehensive coverage.
• AI-driven Insights: HeadSpin aids in identifying performance bottlenecks and optimizing apps for superior user experiences.
• Integration Capabilities: Seamless integration with frameworks like Appium and Selenium facilitates smooth testing workflows.
• Real-time Data and Performance Metrics: HeadSpin provides valuable real-time data and performance metrics for delivering high-quality mobile applications.

Selenium WebDriver Automation with HeadSpin

• Leveraging Real Device Cloud: Run Selenium WebDriver scripts on numerous real devices and browsers for accurate and reliable test results.
• Performance Monitoring and Optimization: Analyze key performance metrics during tests to ensure optimal web application performance.
• Scalability and Parallel Testing: Execute multiple tests simultaneously across devices and cross-browser testing, reducing test suite completion time.
• Seamless CI/CD Integration: Effortlessly incorporate tests into CI/CD pipelines with popular tools like Jenkins, CircleCI, and Travis CI.
• Comprehensive Reporting and Analytics: Gain insights into test outcomes for informed decision-making and continuous improvement.

Summing Up

The demand for mobile app testing frameworks continues to rise in response to the evolving software development and delivery needs. While numerous frameworks exist, we’ve focused on the top four in each category, providing insights into their features and benefits. However, a framework’s value is truly realized when it meets the needs of testers in their daily workflows. We invite you to share your favorite mobile app testing framework and why you prefer it in the comments below.

Tools like HeadSpin can significantly enhance your testing endeavors, ensuring that your mobile applications deliver exceptional user experiences across various browsers, devices, and operating systems.

Article Source:

This article was originally published on:

https://www.headspin.io/blog/best-mobile-app-testing-frameworks-for-android-ios

Mobile applications and websites play a crucial role in helping organizations connect with their customers; this makes it essential to build an application or website that functions well. A critical aspect that makes this possible is testing.

Testing helps ensure the application is stable, its code works well and meets all the users’ requirements. However, there are different software testing types with their unique purpose. These software testing types affect various aspects of the development process, from inception to production.

With so many different software testing types, it’s essential to get a clear understanding of each one. This blog will explore two fundamental software testing types: Functional and Non-Functional, and all the tests under them.

What are The Different Types of Testing?

Unit Testing

Developers run unit tests during the application’s development phase to ensure individual components or sections of code function well. This software testing type helps developers catch bugs and uncover specific issues before the app can go to the QA teams. 

The simplest example of a unit test is when a developer runs a unit test on a calculator app. The purpose of this test will show the developer if entering two numbers produces the correct response. Two types of tests that come under Unit testing are:

a) White Box Testing

White box tests help developers check the output of an action on an app and the code that is responsible for the output. Developers run this test to check for faults in the business logic and verify the code’s integration with the app’s infrastructure.

b) Gorilla Testing

Developers run Gorilla tests to ensure the practical functionality of specific modules within an application. The main objective is to check for faults in module installation and address them. Developers run this test manually.

Integration Testing

Integration testing usually involves testing a group of modules of an application. The goal of this software testing type is to check for any defects or bugs in the interfaces between these modules. This type of testing adds value to the Unit tests.

A test that comes under Integration testing is:

a) Gray box testing

Gray box testing is a testing technique developers use to test an application. It involves having partial knowledge of the structure of the application. It helps developers identify problems with code or the use of the application.

System Testing

System testing involves running tests on the entire system to check if it meets specific requirements. System tests evaluate all the modules that have passed the integration tests. System testing includes these software testing types:

a) End to End Testing

Testers run end-to-end tests to check the app’s capabilities in real-world settings, like using network communications, interacting with a database, applications, or other hardware. These test results help the tester validate an app and its internal systems before launch. 

b) Black Box Testing

Black box testing involves testing the functionalities of an app without knowing the internal design, code, system, or structure. Its primary focus is on the input and output of the app based on software specifications and requirements.

c) Smoke Testing

Smoke testing ensures the stability of the deployed software build. It is a confirmation to the QA teams that the build is ready for further testing. The main goal is to check if the app’s essential features work perfectly well and that there aren’t any bugs in the software. 

d) Sanity Testing

Sanity testing, a subset of regression tests, is a software test that ensures that bug fixes or newly added functionalities work fine. Testers run sanity tests to confirm the stability of the build. 

e) Happy path Testing

Happy path testing involves testing an application through a positive flow. The tester runs scripted test scenarios that a user would perform to check if the application generates expected outputs without breaking functionality. 

f) Monkey Testing

Monkey tests run with the assumption that a monkey is using the app. If this were the case, a monkey would use the app, entering random values and inputs without understanding the application.

This test aims to check if the application crashes when testers provide it with random values/inputs. Testers perform this test at random; they do not have scripted test cases and do not have to be fully aware of the system functionality.

Acceptance Testing

Acceptance testing helps check the app’s functionality concerning business requirements and assess if it’s ready for delivery. The client can accept that app if it meets specific acceptance criteria. User Acceptance Testing (UAT) is the last software testing phase before production.

a) Alpha Testing

Alpha testing helps validate the functionality of a new app. The internal staff carries out alpha tests early on in the development process. The goal is to identify and eliminate defects before releasing the software.

b) Beta Testing

The clients/customers/users run beta tests. They perform these tests in real environments before the organization officially releases the product into the market. This test aims to ensure that no errors remain in the product and that it meets all business requirements from the user’s perspective.

An example of a beta test is when games are pre-released on the Play or App Store. The developers release these games to get user feedback, identify glitches, fix the errors, and release the app with all issues resolved.

c) Operational acceptance testing (OAT)

Operational acceptance testing, or OAT, helps system administrators ensure their systems continue to work well. They test the backup and restore features, user management, maintain the software, update recovery processes, keep tabs on the installing and uninstalling aspects, and ensure software upgrades.

Non-Functional Testing

Security Testing

Security testing involves identifying flaws in the security systems of an app or website. This software testing type helps prevent security breaches and keeps the software secure from viruses and malicious programs. It also helps check the security and strength of the authentication and authorization processes. 

a) Penetration Testing

Penetration testing, also called Pen testing, is the intentional authorization of a cyberattack on the system. The idea behind this is to find out the system’s vulnerabilities regarding security. 

Ethical hackers usually perform Pen testing, which is also called ethical hacking. They perform URL manipulation, session expiry, SQL injection, Privilege Elevation, and more.

Performance Testing

Performance testing tests an application’s response time and stability under load. Testers run performance tests to check app speed, reliability, and overall health. This test aims to eliminate performance bottlenecks and ensure the app meets the required service levels and a positive user experience. 

a) Load testing

As the name suggests, load testing involves putting an application through a specific load to check its stability and response time. This load helps identify the app’s behavior when multiple users simultaneously access it. 

For example, if your application can handle 1000 users with a response time of 3 seconds, you would run load testing to check if your app meets this expectation or falls short.

b) Stress Testing

Stress testing tests an application’s ability to maintain its level of effectiveness under stress or load. With stress testing, testers run an application through extreme conditions to check its functionality.

Continuing the earlier example of your application handling 1000 users at a response time of 3 seconds, you would test your application’s performance with 10,000 users and track its stability and response time with stress testing.

c) Scalability Testing

As the name suggests, scalability testing tests the application’s ability to scale up or down in response to more users. To put it simply, it checks the application’s performance when the number of users drastically increases or decreases.

If your application can handle 1000 users at a response time of 3 seconds, what happens when you introduce 1500 or 5000 users? Would this affect the response time? Scalability testing helps note under what load the application crashed so that the team can work to fix it.

d) Volume testing

Volume testing subjects software to massive volumes of data to analyze the system’s performance. The goal is to check the impact on response time and system stability. 

e) Endurance Testing

Endurance testing tests an application’s ability to endure heavy loads for long periods. The goal is to check if the application’s performance drops or if it loses its stability. 

Automobile companies run endurance tests to check if their users can use the particular automobile without experiencing difficulties, continuously for hours.

Usability Testing

Usability testing helps testers check if their application is user-friendly and easy to use. The test focuses on the users and if they can use the application with ease. 

a) Exploratory testing

Exploratory testing relies on an individual tester and his ability to explore the application to identify otherwise not easily found defects. Testers will need to use their business domain knowledge to explore the application.

This testing allows users to explore the user story by themselves. They can add assertions, annotate defects, and create voice memos and documentation to help QA teams better understand the faults in the application. 

b) Cross-browser testing

Testers running cross-browser tests use it to test their application on different operating systems, browsers, and mobile devices. This test aims to check how the application performs on various platforms. Cross-browser testing is essential because users access apps and websites on different devices. If your application has bugs on one platform, you can lose many users. 

The HeadSpin Platform gives you access to real devices so you can connect to different browsers and operating systems. It integrates into your CI/CD workflows, enabling functional and performance testing pre and post-release. It also fully supports all testing frameworks, including native Appium.

c) Accessibility Testing

Making applications accessible for ones with disabilities is very important. Accessibility testing ensures that your application meets all the requirements for accessibility.

It is essential to check if your application meets the disability requirements for mental disability, visual impairment, deafness, and others.

Compatibility testing

As the name suggests, compatibility testing helps check if your application runs well on different browsers, databases, configurations, network environments, web servers, hardware, and more.

Principles of Software Testing

Software testing principles are foundational guidelines that help conduct various types of testing effectively. These principles ensure testing efforts are focused and aligned with the SDLC’s goals.

1. Testing Shows Presence of Defects: Testing can only confirm the presence of defects, not their absence. Even when no defects are found, claiming flawless software is impossible. Each type of testing you employ should aim to uncover different issues, thereby increasing the quality of the product.
2. Exhaustive Testing is Impossible: Testing every possible scenario is challenging. Instead, focusing on the most critical and high-risk areas through different types of testing can help identify significant issues without overextending the testing process.
3. Early Testing: Initiating testing early in the software development lifecycle, particularly using methods like unit and integration testing, can significantly reduce the cost and time required to fix defects. Different types of testing at various stages ensure comprehensive coverage.
4. Defect Clustering: Experience shows that most defects are often found in a few modules. Prioritizing these modules for testing, particularly through regression and functional testing, can lead to more effective bug detection.‍
5. Pesticide Paradox: Repeating tests eventually leads to diminishing returns as the same defects are found. To counter this, it’s important to continually update and diversify test cases, exploring different types of testing to uncover new issues.

What are Software Testing Techniques and How are They Different from Testing Types?

Introduction to Software Testing Techniques

Testing techniques are specific procedures used to ensure that software behaves as expected. Unlike testing types, which categorize tests based on what they evaluate (like functionality, performance, or security), testing techniques focus on how testing is conducted. Techniques can apply across different testing types, optimizing tests’ efficiency and effectiveness.

Overview of Various Techniques and Their Relation to Testing Types

• Static vs. Dynamic Testing: Static testing involves reviewing the code without executing it (e.g., walkthroughs, and inspections), whereas dynamic testing involves executing the code and observing outputs.
• Black-box Testing: This technique focuses on the input and output of software systems without knowing the application’s internal workings. It applies to most types, such as functional, integration, and system testing.
• White-box Testing: Known as clear or glass box testing, it involves looking inside the software structure and is based on coverage of code statements, branches, paths, and conditions.

Examples of Technique Applications

• Equivalence Partitioning: Used in functional testing to reduce the number of test cases by dividing inputs into groups expected to exhibit similar behavior.
• Boundary Value Analysis: Often used in performance testing to explore the limits of software capabilities by testing at the upper and lower ends of input values.

Manual vs. Automated vs. Continuous Testing

Definition and Differences

• Manual Testing: Testers manually operate and verify the software for defects. It’s flexible but time-consuming and can be prone to human error.
• Automated Testing: Uses software tools to run tests automatically, repeat them, and compare expected and actual outcomes. Ideal for regression tests and large-scale tests but can be expensive to set up.
• Continuous Testing: Part of the Continuous Integration/Continuous Delivery (CI/CD) pipeline, where tests are automatically triggered every time a change is made to the codebase.

Pros and Cons

• Manual Testing: Pro: Allows for real user feedback; Con: Less efficient.
• Automated Testing: Pro: Faster and more reliable over multiple iterations; Con: High upfront cost.
• Continuous Testing: Pro: Immediate feedback on the impact of changes; Con: Requires a mature development process.

Choosing the Right Approach

Selecting between these methods depends on several factors like: project size, budget, criticality, and the stage of development. A combination of these approaches is often used to leverage their benefits.

Seven Principles of Software Testing

Introduction to the Principles

The seven software testing principles are guidelines that help testers manage the complexities of testing activities and improve testing effort quality.

Exploring Each Principle

1. Testing Shows Presence of Defects: Testing can show defects are present but cannot prove that no defects exist.
2. Exhaustive Testing is Impossible: Instead of attempting to test everything, prioritize tests based on risk and importance.
3. Early Testing: The earlier testing is started in the SDLC, the more cost-effective it is to fix defects.
4. Defect Clustering: Defects are often grouped; identifying one defect means more may be nearby.
5. Pesticide Paradox: Running the same tests repeatedly will stop finding new bugs; tests must be reviewed and revised.
6. Testing is Context Dependent: Testing is influenced by the context in which the software operates, like safety-critical software vs. commercial software.
7. Absence-of-Errors Fallacy: Just because no defects are found doesn’t mean the software is ready for production.

Implications

Understanding these principles helps testers optimize their strategy, ensuring thorough and effective testing practices that align with business goals and project requirements.

Conclusion

Testing to check if your users can use your application smoothly is essential. However, it is equally important to test your application’s functionality in unexpected scenarios. Anticipating human errors is fundamental to creating a good user experience.

Remember, tests are code. So, it’s essential to review them. Testing your application’s security is vital to building trust with the user. And finally, testing your application beyond its limit will help you understand its actual capability.

The HeadSpin Platform provides you with a global device infrastructure that can help you test your website & apps on real devices across the world.

And finally, tests are code too! So don’t forget them during code review, as they might be the final gate to production.

Article Source:

This article was originally published on:

https://www.headspin.io/blog/types-of-software-tests-and-what-you-need-to-know-about-them

In the ever-evolving world of mobile app development, providing a seamless user experience is paramount to success. Android UI testing ensures your application meets user expectations by validating its visual elements and interactions. Implementing a test automation strategy can help developers save time, improve efficiency, and uncover potential bugs or usability issues before the app reaches the hands of end users.

This blog delves into Android UI testing, exploring its importance, different approaches, benefits, challenges, tools, and best practices. Additionally, we’ll provide step-by-step instructions on how to get started with Espresso for Android UI testing and share tips for setting up automated tests.

Automated UI Testing: Exploring the Process and Significance

Android automated UI testing refers to automating interactions with an application’s user interface to validate its behavior and appearance across various scenarios. By simulating user actions, such as button clicks, text input, and gestures, automated UI testing ensures that the app functions as intended and maintains a consistent user experience.

The importance of automated UI testing cannot be overstated. It helps identify critical issues early in the development cycle, avoiding costly fixes and negative user experiences. By automating repetitive test cases, developers can allocate more time to focus on enhancing app functionality and delivering new features. Additionally, UI testing boosts overall software quality and instills confidence in the application’s performance.

What are the Different Approaches to Android UI Testing?

When it comes to Android UI testing, developers have the option to choose between manual testing and automated testing. Each approach has its own advantages and considerations, and understanding the differences can help you make an informed decision on the basis of your project requirements. Let’s explore these two approaches in more detail:

1. Manual Testing: Manual testing involves human testers interacting with the application’s user interface to validate its behavior, visual elements, and user experience. Here are some key aspects of manual testing in Android UI testing:

• Test Scenarios: Testers manually execute predefined test scenarios, following steps and recording their observations.
• User Interaction: Manual testing allows testers to mimic user actions and evaluate the app’s responsiveness, intuitiveness, and overall usability.
• Visual Inspection: Testers visually inspect the app’s UI elements, layouts, and design consistency across different devices and screen sizes.
• Exploratory Testing: Manual testing enables testers to explore the app freely, identifying unexpected behaviors and potential usability issues.
• Usability Assessment: Testers can assess the app’s ease of use, navigation flow, and adherence to design guidelines.

While manual testing provides a hands-on approach and allows for flexibility in test execution, it can be time-consuming, labor-intensive, and subject to human error. It best suits initial exploratory testing, usability assessment, and ad-hoc scenario validations.

‍2. Automated Testing: Automated testing involves using specialized software tools and frameworks to automate interactions with the application’s user interface and validate its behavior. Here’s what you need to know about Android automated UI testing:

• Test Scripts: Testers or developers write test scripts using testing frameworks like Espresso, UI Automator, or Appium. These scripts define the steps, expected outcomes, and assertions for automated test execution.
• Test Execution: The testing framework runs the test scripts, simulating user interactions and verifying the app’s response. Automated tests can cover many scenarios and achieve greater test coverage than manual testing.
• Repeatability: Automated tests can be executed repeatedly, ensuring consistent and reliable results. This is particularly useful when regression testing is required after making changes or adding new features to the app.
• Faster Feedback: Automated tests provide faster feedback on the app’s functionality and UI behavior, allowing developers to identify issues early in the development cycle and address them promptly.
• Cross-Platform Testing: Some automation frameworks, such as Appium, support cross-platform testing, enabling testing on both Android and iOS platforms using the same test scripts.

Automated testing offers several advantages over manual testing, including faster test execution, wider coverage, repeatability, and reduced human error. However, setting up and maintaining automated test scripts can be time-consuming, requiring expertise in testing frameworks and programming languages.

What are the Benefits and Challenges of Android UI Testing?

Android UI testing is an invaluable resource for developers looking for a way of guaranteeing their apps perform optimally upon launch. By taking advantage of automated as well as manual tests and pre-built scripts, they can save time and money while delivering a top-notch user experience every time.

Benefits

• Improved efficiency: Automated UI testing allows quicker execution of repetitive test cases, saving valuable development time.
• Increased test coverage: Automation enables testing across multiple devices, screen sizes, and operating system versions, ensuring consistent performance across a diverse user base.
• Early bug detection: By identifying issues in the early stages, automated UI testing helps prevent bugs from propagating further into the development cycle.
• Enhanced user experience: Thorough UI testing ensures a smooth and intuitive user interface, fostering positive user interactions and engagement.

However, it’s important to understand that UI testing requires time and effort due to its sensitivity to changes in the interface. Deciding what elements need testing and how frequently these tests should occur could be challenging.

Challenges

• Test maintenance: As applications evolve, UI changes may require corresponding test script updates, leading to increased maintenance efforts.
• Test script creation: Developing robust and reliable test scripts can be complex and time-consuming, requiring expertise in testing frameworks and programming languages.
• Device fragmentation: The vast array of Android devices, with different screen sizes, resolutions, and hardware configurations, poses challenges in achieving consistent UI testing results across devices.

Delving into Tools for Conducting Android UI Testing

Android UI testing is an important part of the development process, and various tools are available to help developers test their applications. Espresso, Robotium, and Appium are the most popular Android UI testing tools. Each has its own unique features and capabilities that can be used to create efficient tests for different scenarios.

• Espresso is Google’s official UI testing tool for Android. It provides a fast and reliable way to write automated tests by executing them on your application’s device or emulator. Espresso makes it easy to build test scripts by using Java-like syntax that allows developers to rapidly generate code snippets and build complex tests in no time.
• Robotium is another popular choice for Android UI testing due to its ease of use and powerful scripting capabilities. It has a range of useful features, such as automatic synchronization with activities, integration with JUnit4, support for multiple devices, access to multiple views within an activity, etc., making it ideal for writing comprehensive tests quickly.
• Appium is a popular cross-platform framework used for automating mobile application testing. It allows developers to write automated tests using various programming languages, including Python, JavaScript, Ruby, PHP, and more. This versatility makes Appium a preferred choice compared to other testing frameworks like Espresso and Robotium, which are primarily focused on Java.
  ‍
  One of the key advantages of Appium is its support for multiple drivers, including the Espresso driver and UI Automator driver. The Espresso driver is a part of the Appium project and allows you to write tests using Espresso’s APIs, which are specifically designed for Android UI testing. The UI Automator driver, on the other hand, leverages the UI Automator framework provided by Android to interact with the application under test. These drivers provide additional capabilities and flexibility when testing Android applications.
  ‍
  By using Appium, developers can benefit from its cross-platform compatibility, as it supports both Android and iOS platforms. This means you can write a single test script and execute it on multiple devices and platforms without modifying the code extensively.
  ‍
  Appium also offers parallel execution, which enables you to run tests on multiple devices simultaneously. This feature significantly speeds up the testing process, as you can execute tests concurrently across different devices or simulators/emulators.
• ‍UI Automator is a testing framework provided by Google for automating user interface interactions on Android devices. It allows developers to write automated tests that interact with the UI elements of an application across different apps and activities. UI Automator provides a rich set of APIs to simulate user actions, such as clicking buttons, entering text, and swiping gestures. It also offers powerful features like UI element identification using attributes and XPath expressions, making it easier to locate and interact with specific UI elements during testing. With its ability to work across apps and extensive functionality, UI Automator is a valuable Android UI testing tool.

Embarking on the UI Testing Tool for Android – Espresso

Getting started with Espresso Android UI testing can be intimidating initially, but with the right tools and guidance, it can become an invaluable part of your development process. Here are some tips to help you get started.

The first step is understanding the Android Activity Lifecycle and how it affects UI testing. This will give you a better understanding of when certain tests should be executed and how they can be automated. After that, you’ll need to set up your test environment for automated tests by installing the necessary UI testing tools for Android, such as Espresso, Robotium, and Appium. You’ll also want to become familiar with Espresso’s APIs and capabilities and create basic tests covering the most common scenarios.

Lastly, you should consider continually integrating these tests into a continuous integration system to test them throughout the development process. This will ensure that errors are caught quickly and that your application performs optimally upon launch.

Following these steps gives you a strong foundation for successful Espresso Android UI testing. With the right resources, you can quickly start creating powerful automated tests for your applications.

How Can You Set Up Your Android UI Automation Tests with Espresso?

Setting up your Android UI automation tests with Espresso, a native testing framework provided by Google, requires careful planning and attention to detail. Espresso is specifically designed for writing concise and reliable UI tests for Android applications. It provides a fluent and expressive API for interacting with user interface components and validating their behavior. Espresso tests can be written in either Java or Kotlin, making it flexible for developers to choose their preferred programming language.

In this section, we will explore step-by-step instructions and provide code snippets to help you set up Espresso for Android UI testing. By following best practices and leveraging the power of Espresso, you can streamline the setup process and achieve effective test automation for your Android applications.

1. Set up your testing environment:

• Add the necessary dependencies to your project’s build.gradle file. Include the Espresso core library, Espresso-contrib for additional capabilities, and Espresso-intents for testing intents and UI navigation.

androidTestImplementation ‘androidx.test.espresso:espresso-core:<version>’

androidTestImplementation ‘androidx.test.espresso:espresso-contrib:<version>’

androidTestImplementation ‘androidx.test.espresso:espresso-intents:<version>’

2. Set the instrumentation runner:

• To configure your project to use the appropriate instrumentation runner for UI automation testing with Espresso, you need to specify it in your app’s build.gradle file. This instrumentation runner is responsible for executing your UI tests on an Android device or emulator.

Open the app’s build.gradle file (file: app/build.gradle) and locate the android.defaultConfig section. Within this section, add the following line:

testInstrumentationRunner “androidx.test.runner.AndroidJUnitRunner”

By adding this line, you are instructing the Android system to utilize the AndroidJUnitRunner provided by the androidx.test.runner package as the instrumentation runner for your UI automation tests.

Make sure to place this line within the android.defaultConfig block to ensure that it is applied correctly.

3. Define your test class:

Create a new test class that extends the androidx.test. Espresso.Espresso class. This class serves as the entry point for interacting with the UI elements in your tests.

import androidx.test.espresso.Espresso;

public class MyUITest {

// Test methods and assertions go here

}

4. Write your test methods:

• Define individual test methods that represent different test scenarios. Use Espresso’s API to interact with UI elements and perform actions like clicking buttons, entering text, or validating text content.

import androidx.test.espresso.action.ViewActions;

import androidx.test.espresso.matcher.ViewMatchers;

import androidx.test.espresso.assertion.ViewAssertions;

public class MyUITest {

@Test

public void testButtonClick() {

        Espresso.onView(ViewMatchers.withId(R.id.button_id))

             .perform(ViewActions.click());

     // Add assertions here

}

}

5. Add assertions to validate UI elements:

• Use Espresso’s ViewAssertions class to add assertions that verify the state or content of UI elements. This helps ensure that your app’s UI behaves as expected during testing.

import static androidx.test.espresso.assertion.ViewAssertions.matches;

import static androidx.test.espresso.matcher.ViewMatchers.withText;

public class MyUITest {

@Test

public void testButtonClick() {

     Espresso.onView(ViewMatchers.withId(R.id.button_id))

                .perform(ViewActions.click());

        Espresso.onView(ViewMatchers.withId(R.id.text_view_id))

                .check(matches(withText(“Hello, Espresso!”)));

}

}

6. Run your tests:

• Execute your Espresso tests using Android Studio’s built-in testing tools or the command-line interface. Ensure that you have a connected device or emulator for test execution.
• In Android Studio, right-click on your test class or test method and select “Run” or “Debug” to execute the tests.
• Using the command-line interface, navigate to your project’s root directory and run the following command:

./gradlew connectedAndroidTest

7. Analyze test results:

• After running your tests, review the test results to identify any failures or issues. Android Studio provides a detailed test report highlighting the status of each test method.
• If a test fails, examine the failure stack trace and logs to identify the cause. Update your test code or application code accordingly to resolve the issues.

Following these steps, you can effectively set up your Android UI automation tests with Espresso. Remember to create comprehensive test scenarios and leverage Espresso’s powerful API to interact with and validate your app’s UI elements.

What are the Drawbacks of Using Espresso? 

While Espresso offers several advantages, it’s important to consider its drawbacks as well. Here are a few limitations of Espresso:

1. Limited support for programming languages: Espresso primarily focuses on supporting Java and Kotlin for Android app development. This can be a significant drawback if you prefer working with other programming languages like Swift (for iOS development) or JavaScript (for cross-platform development using frameworks like React Native or Flutter). Espresso’s limited language support restricts its applicability to specific platforms and development scenarios.

2. Limited support for non-native apps: Espresso is primarily designed for testing native Android applications. If you’re working on a project that involves non-native apps, such as hybrid or web-based applications, Espresso might not be the most suitable choice. Other testing frameworks and tools like Appium or Selenium WebDriver may offer more comprehensive support for testing non-native apps across different platforms.

3. Learning curve: While Espresso provides a robust testing framework for Android, it does have a learning curve. If you’re new to Espresso or testing in general, it might take some time to grasp its concepts, understand its APIs, and effectively write tests. This learning curve could potentially slow down your testing process, especially if you’re working on tight deadlines or have limited resources for training team members.

4. Test execution speed: Depending on the complexity of your test suite, Espresso’s test execution speed may vary. Running a large number of tests or tests with heavy interactions can sometimes result in longer execution times. This can impact your overall testing efficiency, especially if you need to execute tests frequently or run them in parallel.

5. Limited tooling ecosystem: Although Espresso has gained popularity within the Android testing community, its tooling ecosystem is still relatively limited compared to other frameworks. While there are plugins and extensions available, the overall availability and variety of tools might be less extensive than what you’d find for other testing frameworks.

How HeadSpin’s Advanced UI Testing Capabilities Empower Businesses to Deliver Perfect Digital Experiences

In the realm of Android UI testing, HeadSpin emerges as a leading mobile testing Platform, offering developers a comprehensive suite of tools and real devices to ensure seamless testing and optimization of their applications. With HeadSpin’s cutting-edge capabilities, developers can overcome the challenges associated with Android UI testing and deliver high-quality apps.

Let’s delve into the four key capabilities that HeadSpin provides:

1. Comprehensive Device Coverage: One of the standout features of HeadSpin is its extensive inventory of real cloud devices—global device infrastructure. Developers can access various devices, spanning multiple hardware configurations, screen sizes, and operating system versions. This device diversity empowers developers to conduct thorough tests and validate their app’s UI across various real-world scenarios. HeadSpin enables developers to deliver an exceptional user experience by ensuring compatibility and consistency across different devices.
2. Network and Performance Testing: Understanding how an app performs under different network conditions is vital for success. HeadSpin allows developers to evaluate their app’s performance under various network scenarios, simulating different connection speeds, network strengths, and latency conditions. Developers can identify potential bottlenecks by conducting network and performance tests, optimizing their app’s performance, and enhancing user satisfaction. HeadSpin’s network testing capabilities empower developers to deliver an app that performs reliably across diverse network conditions.
   In addition to network testing, HeadSpin also offers a powerful audio-visual Platform. With HeadSpin’s audio-video offerings, developers can assess how their OTT apps handle audio and video streaming, ensuring a seamless and high-quality media experience for users.
3. Remote Debugging and Troubleshooting: HeadSpin simplifies debugging and troubleshooting by enabling remote access to real devices. With this feature, developers can remotely debug their applications on actual devices, eliminating the need for physical access. This capability streamlines the debugging process, allowing developers to identify and resolve issues more efficiently. HeadSpin saves developers time and effort by offering remote debugging and troubleshooting, facilitating faster issue resolution, and accelerating the app development cycle.
4. Analytics and Insights: HeadSpin goes beyond just providing access to real devices by offering powerful analytics and insights. Developers gain access to in-depth performance monitoring tools and analytics dashboards, providing actionable insights into app performance and user behavior. By leveraging these analytics, developers can make informed decisions to optimize their app’s UI, improve user engagement, and enhance overall app performance. HeadSpin’s analytics and insights empower developers to create data-driven strategies and continuously improve the user experience.

By leveraging HeadSpin’s AI-driven testing Platform, developers can optimize their app’s UI, enhance user experience, and stay ahead in the competitive world of mobile app development

Wrapping Up

Mastering Android UI testing is crucial for delivering a seamless user experience and ensuring the success of your mobile application. By embracing automated testing using tools like Espresso, developers can save time, increase test coverage, and enhance overall software quality.

Additionally, leveraging a robust mobile testing platform like HeadSpin empowers developers to access real devices and optimize their UI testing efforts. With HeadSpin’s comprehensive capabilities, developers can confidently test, analyze, and improve their Android apps’ performance.

Experience the power of seamless Android UI testing with HeadSpin.

Article Source:

This article was originally published on:

https://www.headspin.io/blog/a-comprehensive-guide-to-android-ui-testing-with-espresso

Continuous Integration (CI) and Continuous Delivery (CD) methodologies have significantly evolved over the past decade, paving the way for more streamlined, efficient, and effective software development practices. Commonly referred to as CI CD, these interconnected methodologies form the blueprint of contemporary software development. Today, CI/CD are the two most popular methods of DevOps development. They enable developers to collaborate on projects more efficiently and deliver better-quality software faster. Businesses strive to establish and refine their CI/CD pipelines regardless of size. The aim is not just to continually update their software but also to stay agile and responsive to the dynamic market trends and demands. By embracing CI/CD, organizations can foster a culture of rapid innovation, resulting in accelerated time to market, improved product quality, and an edge over the competition. However, as DevOps teams look to streamline their processes and increase the speed of software development, several enterprises struggle to master this approach. As mentioned in a post by Forbes, ‘Solving CI/CD’s Delivery Problem, ‘ only 4% of enterprises believe themselves to be experts in CI/CD, while 11% consider their existing CI/CD infrastructure reliable.

What are CI CD tools in DevOps?

Continuous Integration and Continuous Delivery are rapidly becoming a cornerstone of successful DevOps projects. This process enables teams to automate their workflow from code development to deployment, reducing the time required to deliver new features, bug fixes, and other software updates. With CI CD tools, teams can easily integrate changes into their codebase, test them, and deploy them quickly. CI/CD also helps teams ensure their applications are always up-to-date with the latest features and bug fixes. This is especially important for organizations whose customers or users rely on products that require frequent updates or changes – such as software applications. By using CI CD tools, developers can regularly update their applications without manually managing every change individually.

Benefits of using CI CD tools

Implementing CI/CD tools in DevOps project not only streamlines processes and increases productivity but also fundamentally enhances operational dynamics. They foster collaboration, accelerate release times, and assure high-quality output. Let’s explore why CI/CD is important.

• Improved automation for quicker workflows: Automation is at the core of what these tools provide, streamlining the software release process and reducing manual effort. This leads to faster deployments, fewer errors due to human involvement, improved quality control, and more efficient deployment across multiple environments.
• Enhanced accuracy: CI CD tools in DevOps operate within a highly controlled environment, conducting numerous tasks concurrently. The high degree of automation these tools provide reduces the chances of errors from manual processes. In essence, these tools dramatically decrease error rates by eliminating the inconsistencies that arise from individual variations, thus ensuring the delivery of a stable and reliable product.
• Boosted collaboration: The visibility provided by CI CD tools in DevOps also makes it easier for developers and teams to collaborate on their projects while maintaining quality standards. Additionally, these powerful applications enable teams to detect bugs or performance issues in the early stages of development so that they can be addressed before they become problems in production environments.
• Improved cost-effectiveness: Utilizing CI CD tools in DevOps drastically reduces costs associated with manual processes like testing and debugging applications by eliminating time-consuming tasks humans would have had to perform manually. Automation ensures that each task is performed accurately and consistently across all environments, helping reduce human error while increasing efficiency and reliability.
• Seamless integration with third-party platforms: With CI CD, users can easily integrate third-party services into their workflow without having to write custom code or configure complex systems manually. This makes it simpler for teams to deploy applications quickly while taking advantage of existing services such as logging frameworks or cloud provider APIs.
• Improved real-time monitoring: CI/CD tools in DevOps are equipped with capabilities for real-time system monitoring, offering a clear, up-to-the-minute snapshot of the system’s status. This continuous visibility allows teams to promptly detect any anomalies or issues in the system, enabling immediate action and swift rectification. As a result, these tools expedite issue resolution and ensure the overall health and robustness of the system.

Choosing the right CI CD tool for your DevOps project

Choosing the right CI/CD tool for your DevOps project is essential to ensure success. There are a few key points to consider when selecting the best tool for your project.

• First, evaluate what features and capabilities you require from a CI CD tool and which of those features are most important. Different tools offer different levels of automation, integration with third-party services, cost optimization, performance detection, bug detection, collaboration tools, and more. Prioritizing these needs will help you narrow down the tools that could work for your project.
• Second, it is important to consider each tool’s total cost of ownership. This includes not only the initial cost but also any additional costs associated with using a particular tool over another. It’s also crucial to factor vendor support and documentation availability into this calculation because ease of use is crucial to realize an ROI on your CI/CD investment.
• Third, make sure all stakeholders are on board with the chosen tool before beginning implementation. This means that everyone involved should be aware of how the chosen tool meets their individual goals and expectations as it relates to their role in the DevOps process. Additionally, stakeholders need to understand how they can contribute throughout implementation and beyond in order for there to be a true collaboration between them and their teams during development cycles.

By taking these factors into consideration when selecting a CI/CD solution for your DevOps project, you can ensure that you select one that best meets your requirements while optimizing cost efficiency and ensuring collaborative success among all stakeholders involved throughout the process.

Common characteristics of CI/CD tools

CI/CD tools make the development process from code commit to deployment faster and more efficient. They integrate features that facilitate both Continuous Integration (CI) and Continuous Delivery (CD), which enable teams to produce higher-quality output in a shorter time frame. Automated builds and tests are essential components of CI/CD tools in DevOps. These enable developers to quickly detect any issues or bugs in their code before they reach production environments, as well as check that all commits pass through a series of tests.

Continuous delivery pipelines provide an end-to-end view of the development process, which helps teams identify bottlenecks so they can reduce cycle times and improve performance. A dashboard is necessary for managing projects, giving everyone involved in the project clear visibility into what needs to be done next while providing an overview of tasks, milestones, deadlines, and others. Integrations with other DevOps tools help teams get more out of their toolchain than using multiple separate applications for each task.

By leveraging these features together, CI CD tools in DevOps can help streamline DevOps processes while increasing visibility into project progress and improving collaboration between stakeholders – all leading to better software delivered faster without compromising quality.

A closer look at the top 10 CI CD tools

When it comes to DevOps projects, CI CD tools are an essential part of the equation. These services automate processes and simplify collaboration between stakeholders, helping reduce costs in the long run. Let us delve into the tools and their key features.

1. Jenkins: An open-source stalwart in the CI/CD space, Jenkins is renowned for its extensibility and versatility, thanks to a robust plugin ecosystem. A popular choice for developers, Jenkins can fit into nearly any CI/CD toolchain.

• Offers an extensive plugin ecosystem with over 1500 plugins, extending the functionality of Jenkins for a variety of tasks
• Free and open-source, making it preferable for startups and large-scale organizations
• Backed by a vibrant community that regularly contributes updates and innovations
• Seamlessly integrates with popular cloud platforms such as AWS, Azure, Google Cloud, Digital Ocean, and more
• Supports a myriad of software versions and platforms and can be configured as per project needs
• Allows distribution of tasks across multiple machines for faster builds, tests, and deployments

2. Azure DevOps: Microsoft’s Azure DevOps is a comprehensive platform providing a range of developer services that cater to all stages of the software lifecycle.

• Includes Azure Boards, Azure Pipelines, Azure Repos, Azure Test Plans, and Azure Artifacts.
• Integrates well with existing systems and services, including other Microsoft products.
• Offers features like Version Control Systems, Code Repository Management, Build Automation, and integration with Visual Studio Team Service
• Integrates easily with the code of different programming languages and application types
• Allows efficient scaling of resources as per requirements
• Leverages Microsoft’s security model, offering high levels of data protection

3. GitHub Actions: A relative newcomer, GitHub Actions allows developers to create custom software development lifecycle workflows directly within their GitHub repositories.

• Enables users to create CI CD pipelines without leaving the GitHub interface.
• Enables users to build, test, and deploy their code right from GitHub, making workflows highly customizable.
• Allows to perform multi-container testing by adding support for Docker
• Provides 2000 free build minutes/month for all your private repositories
• Works with any platform that runs Node.js, Python, Java, Ruby, PHP, Go, Rust, .NET, and more

4. GitLab: Integrated within the GitLab ecosystem, GitLab CI CD eliminates the need for connections with external repositories and offers highly efficient workflows.

• Offers developer APIs – leveraging which third-party developers can create a deeper integration into their products
• Allows parallel execution of code to reduce build times significantly.
• Easy to start with owing to the web app’s intuitive design
• Supports a wide array of languages and frameworks with no plugin requirements
• Allows easy migration from a tool like Jenkins or CircleCI to GitLab CI

5. CircleCI: As a cloud-first CI/CD tool, CircleCI offers easy setup and smooth integration with GitHub and Bitbucket, ensuring efficient build, test, and deploy processes.

• Easy setup and configuration via a simple YAML file
• Offers CI/CD pipelines as ‘Workflows’
• Seamlessly integrates with GitHub and Bitbucket
• Allows simultaneous execution of tests for quick results
• Helps run tests in parallel across different executors
• Supports most of the popular programming languages out of the box
• Helps automate repetitive processes and accelerate the integration with third-party tools with CircleCI Orbs, which are reusable snippets of code

6. Travis CI

• Travis CI helps automate testing and deployment processes. It’s highly integrated with GitHub, making it popular among open-source projects.
• Supports multiple languages, easy to set up with a .travis.yml file, and offers a matrix of build environments.
• Best for projects that require seamless integration with GitHub and a straightforward, easy-to-configure CI/CD process.

7. Bamboo

• Bamboo is Atlassian’s CI/CD tool that integrates deeply with other products like JIRA and Bitbucket, providing a cohesive experience for users already in the Atlassian ecosystem.
• Real-time visibility into builds, deployment projects, and environments. It supports various languages and frameworks.
• Best for teams already using Atlassian products looking for deep integration and a robust CI/CD tool.

8. TeamCity

• Developed by JetBrains, TeamCity is known for its powerful build management and continuous integration features. It supports many languages and frameworks.
• Comprehensive version control system support, build history, and detailed real-time reporting of build progress and server health.
• Best for organizations requiring a customizable and scalable CI/CD solution with extensive build management features.

9. Spinnaker

• Spinnaker is an open-source, multi-cloud continuous delivery platform best for releasing high-velocity software changes.
• Supports multiple cloud providers, integrates with various CI tools, and offers advanced deployment strategies.
• Best for teams looking for a CD platform that excels in managing complex deployments across different cloud environments.

10. Concourse

• Concourse is an open-source CI/CD tool focusing on pipelines, offering a unique approach to automation and integration.
• Treats pipelines as first-class citizens, offering a clear visualization and easy configuration via YAML files.
• Best for teams valuing simplicity, configuration as code, and a strong emphasis on pipeline-based workflows.

Choosing the Right CI CD Tool

When selecting a CI CD tool, consider these factors:

• Compatibility: Ensure the tool supports your tech stack and integrates smoothly with your existing tools and workflows.
• Ease of Integration and Setup: Look for tools that offer straightforward setup processes and easy integration with your repositories, testing suites, and deployment platforms.
• Scalability: Choose a tool that scales with your project, handling increased workloads without performance degradation.
• Community Support and Documentation: A strong community and comprehensive documentation can significantly ease the tool’s adoption and troubleshooting.
• Cost: Consider the tool’s pricing structure and ensure it aligns with your budget, especially as your needs evolve.
• Security and Compliance: Ensure the tool meets your security requirements and complies with relevant industry standards.

Your choice should enhance your team’s efficiency, align with your development practices, and support your automation and continuous delivery goals.

How does HeadSpin seamlessly integrate with your CI/CD pipeline?

One of the key considerations when selecting a CI CD tool is how seamlessly it can integrate with your existing processes. HeadSpin stands out in this regard, offering smooth and straightforward integration with your CI/CD pipeline.

HeadSpin’s data science driven advanced testing platform is designed to fit right into your existing ecosystem without disrupting your workflows. It supports a wide range of integration options, including popular CI CD tools like Jenkins, GitLab, and CircleCI. This way, you can use HeadSpin’s advanced performance monitoring and testing capabilities right from your CI CD tool.

Additionally, with its API-driven approach, HeadSpin enables you to automate your workflows and extend your DevOps capabilities. Its comprehensive REST API allows you to programmatically manage your tests, data, and insights, giving you the flexibility and control you need over your pipeline.

HeadSpin’s mission is to make testing and performance monitoring a seamless part of your development process, and its integration capabilities reflect this. With HeadSpin, enterprises get robust support that enhances the existing CI/CD processes rather than complicating them.

Wrapping up

When selecting a CI CD tool, it is essential to consider various factors such as features desired by the team, total cost of ownership, scalability, integration options, user experience, level of support, and ease of setup. Therefore, it is essential to conduct extensive research to ensure the best fit for your requirements.

Article Source:

This article was originally published on:

https://www.headspin.io/blog/ci-cd-tools-for-devops

Selenium WebDriver has revolutionized the way we approach browser automation. This powerful tool allows developers and testers to automate web applications for testing purposes, ensuring their applications work as expected across different browsers and platforms. This Selenium WebDriver tutorial will delve into the essentials of mastering Selenium WebDriver automation effectively.

What is Selenium WebDriver?

Selenium WebDriver is an open-source tool that automates web browser interactions. It allows you to execute tests against various browsers, mimicking the actions of a real user. WebDriver can perform complex tasks such as form submissions, navigation, and interaction with dynamic web elements. It supports many programming languages making it a versatile choice for various projects.

Setting Up Selenium WebDriver

To master Selenium WebDriver automation effectively, the first step is to set up your environment correctly. This involves installing the necessary software, configuring your Integrated Development Environment (IDE), and downloading the appropriate browser drivers. Follow this detailed guide to set up Selenium WebDriver for your testing needs.

Prerequisites

Before you start, ensure you have the following prerequisites installed on your machine:

• Java Development Kit (JDK): Selenium WebDriver requires JDK to run Java-based scripts.
• Integrated Development Environment (IDE): An IDE like Eclipse or IntelliJ IDEA will help you write, debug, and manage your test scripts.
• Browser Drivers: Selenium WebDriver interacts with web browsers through specific drivers like ChromeDriver for Chrome, GeckoDriver for Firefox, and more.
• Selenium WebDriver Library: The core library provides the necessary classes and methods for WebDriver interactions.

Step-by-Step Installation Guide

1. Install JDK

Install JDK from the Oracle website. Follow the instructions to set up the JDK on your operating system. Ensure that the JAVA_HOME environment variable is set correctly.

2. Setup IDE

Choose an IDE such as Eclipse or IntelliJ IDEA. Download and install your preferred IDE:

• Eclipse: Download from the Eclipse website.
• IntelliJ IDEA: Download from the JetBrains website.

After installation, open your IDE and configure it for Java development.

3. Download Browser Drivers

Selenium WebDriver requires specific drivers to control different browsers. Download the appropriate driver for the browser of your choice:

• ChromeDriver: Download from the ChromeDriver website.
• GeckoDriver: Download from the Mozilla GeckoDriver GitHub for Firefox.
• EdgeDriver: Download from the Microsoft Edge Developer site.

After downloading, place the driver executable in a suitable location on your system and note the path.

4. Add Selenium WebDriver Library

Download the Selenium WebDriver library from the Selenium official website.

• In Eclipse:
  1. Right-click on your project.
  2. Select Build Path > Add External Archives.
  3. Browse and select the Selenium WebDriver JAR files you downloaded.
• In IntelliJ IDEA:
  1. Right-click on your project in the Project view.
  2. Select Open Module Settings.
  3. Go to Libraries and click the + icon.
  4. Browse and select the Selenium WebDriver JAR files you downloaded.

Configuring Browser Drivers

To ensure your Selenium WebDriver scripts can interact with your chosen browser, configure the path to the browser driver in your test scripts. This can be done by setting the system property for the respective browser driver.

Verifying the Installation

You can write and run a simple Selenium WebDriver script to verify that everything is set up correctly. The script should initialize the WebDriver, navigate to a website, and print the page title. 

Troubleshooting Common Issues

While setting up Selenium WebDriver, you may encounter some common issues:

• Path Issues: Ensure your script sets the path to the browser driver executable correctly.
• Incompatible Browser and Driver Versions: Verify that the browser driver’s version matches the installed browser’s version.
• Java Version: Ensure you use a compatible version of JDK as Selenium WebDriver requires.

These steps can help you set up Selenium WebDriver effectively, allowing you to automate web browser interactions easily. This comprehensive Selenium WebDriver tutorial will equip you with the foundational knowledge needed to start with Selenium WebDriver automation.

Writing Your First Selenium WebDriver Script

Example in Java:

Here’s a simple example of a Selenium WebDriver script written in Java:

import org.openqa.selenium.WebDriver;

import org.openqa.selenium.chrome.ChromeDriver;

public class SeleniumWebDriverExample {

public static void main(String[] args) {

// Set the path to the ChromeDriver executable

System.setProperty(“webdriver.chrome.driver”, “/path/to/chromedriver”);

// Initialize WebDriver

WebDriver driver = new ChromeDriver();

// Navigate to a website

driver.get(“https://www.example.com”);

// Get the title of the page

String pageTitle = driver.getTitle();

System.out.println(“Page title is: ” + pageTitle);

// Close the browser

driver.quit();

}

}

This simple script sets up the WebDriver, navigates to a website, prints the page title, and then closes the browser.

Advanced Selenium WebDriver Techniques

Handling Web Elements

Selenium WebDriver lets you interact with various web elements using different locator strategies such as:

• By ID
• By Name
• By Class Name
• By Tag Name
• By CSS Selector
• By XPath

Example: Clicking a Button

WebElement button = driver.findElement(By.id(“submit-button”));

button.click();

Managing Waits

Dealing with dynamic web pages requires handling waits to ensure elements are available before performing actions. Selenium WebDriver provides different wait strategies:

• Implicit Wait: Waits for a specified time before throwing an exception.
• Explicit Wait: Waits for certain conditions to be met before proceeding.‍
• Fluent Wait: A more flexible version of explicit wait, allowing you to define the polling frequency and exceptions to ignore.

Example: Explicit Wait

WebDriverWait wait = new WebDriverWait(driver, 10);

WebElement element = wait.until(ExpectedConditions.visibilityOfElementLocated(By.id(“element-id”)));

Best Practices for Selenium WebDriver Automation

To master Selenium WebDriver automation effectively, following best practices that enhance code quality, maintainability, and reliability of your test scripts is crucial. Below are some essential best practices for Selenium WebDriver automation:

1. Modularize Your Code

Breaking down your test scripts into smaller, reusable functions helps maintain the code. Modularization allows you to group related actions and assertions into methods, making your test scripts easier to read and manage. For instance, you can create separate login, form submission, and validation methods.

2. Use Page Object Model (POM)

The Page Object Model (POM) design pattern enhances the readability and maintainability of your code by separating the test logic from the page-specific actions. A class represents each web page in your application, and methods represent the actions on that page.

3. Leverage TestNG or JUnit

Testing frameworks like TestNG or JUnit help manage test cases, execute them in a defined order, and generate comprehensive reports. These frameworks annotate test methods, setup, and teardown operations.

4. Handle Exceptions Gracefully

Implementing robust error handling ensures your tests can manage unexpected issues without failing abruptly. Use try-catch blocks to catch and log exceptions, allowing for better debugging and test resilience.

5. Keep Browser Drivers Updated

Regularly updating your browser drivers ensures compatibility with the latest versions and helps avoid potential issues. Outdated drivers can lead to failures and inaccuracies in your test results.

6. Implement Logging

Logging frameworks like Log4j or SLF4J help track the execution of your test scripts and identify issues. Logging provides insights into the test flow and helps debug problems more efficiently.

7. Use Explicit Waits Over Implicit Waits

Explicit waits are more reliable than implicit waits as they wait for specific conditions to be met before proceeding. This ensures that elements are available and ready for interaction, reducing flakiness in your tests.

How HeadSpin Can Help with Selenium WebDriver Automation

Leveraging Real Device Cloud

One of the biggest challenges in Selenium WebDriver automation is ensuring that your tests are comprehensive and cover many devices and browsers. HeadSpin’s Real Device Cloud allows you to run your Selenium WebDriver scripts on many real devices and browsers. This capability ensures that your web applications are tested under real-world conditions, providing more accurate and reliable test results. By accessing a diverse set of devices, you can catch device-specific issues early in the development cycle, enhancing the overall quality of your web application.

Performance Monitoring and Optimization

Testing is not just about verifying functionality; it’s also about ensuring optimal performance. HeadSpin provides advanced performance monitoring tools that allow you to analyze key performance metrics during your Selenium WebDriver tests. These metrics include page load times, responsiveness, and resource utilization. By integrating performance monitoring with your automated tests, you can locate and fix performance bottlenecks, ensuring that your web application delivers a smooth and fast user experience.

Scalability and Parallel Testing

Running tests efficiently and at scale is crucial in a fast-paced development environment. HeadSpin supports parallel testing, allowing you to execute multiple Selenium WebDriver tests simultaneously across different devices and browsers. This parallel execution capability significantly reduces the time required to complete your test suite, enabling faster feedback and quicker releases. Scalability is a key advantage of using HeadSpin, as it allows you to run extensive test suites without being limited by local infrastructure.

Seamless Integration with CI/CD Pipelines

CI/CD practices are essential for modern software development. HeadSpin integrates seamlessly with popular CI/CD tools such as Jenkins, CircleCI, and Travis CI. This integration enables you to effortlessly incorporate Selenium WebDriver tests into your CI/CD pipelines. Automated tests can be triggered with every code commit or deployment, ensuring that new changes are thoroughly tested before production. This continuous testing approach helps maintain high code quality.

Comprehensive Test Reporting and Analytics

Effective test reporting is crucial for understanding test outcomes and making informed decisions. HeadSpin provides detailed test reports and analytics for your Selenium WebDriver tests. These reports include information on test execution status, identified issues, performance metrics, and more. The intuitive dashboard lets you quickly analyze test results, track trends over time, and generate custom reports for stakeholders. With comprehensive reporting, you can gain deep insights into your testing efforts and continuously improve your test strategies.

Conclusion

Mastering Selenium WebDriver automation involves understanding its core concepts, setting up the environment correctly, writing effective test scripts, and following best practices. Leveraging tools like HeadSpin can elevate your testing efforts, ensuring your web applications deliver exceptional user experiences across various browsers and devices. This Selenium WebDriver tutorial has covered the essential aspects of Selenium WebDriver, providing you with the knowledge to automate your web testing effectively.

Article Source:

This article was originally published on:

https://www.headspin.io/blog/selenium-webdriver-tutorial-to-conduct-efficient-webdriver-automation-testing

Hi everyone. Welcome to HeadSpin Webinar. I’m Joe Chasinga, a Software Engineer at HeadSpin. I work on device instrumentation and also the biometrics SDK for both the iOS and Android platforms.

Today, we’re going to be talking about biometric authentication Android. This topic mainly focuses on Android biometrics SDK and how to use the library package to effectively run your biometrics test.

Let’s start with talking about what really are biometrics. Biometrics are the use of users’ body measurements and calculations, like metrics or keys, as authentication, identification, or control methods. The most common forms today are fingerprint scanning –  that’s really popular face recognition, iris scanning, and skeleton detection, as you might have seen with the Xbox Kinect sensors.

Here’s a little reference from quite a popular film – Back To The Future 2 – from back in 1989, 30 years ago. In the movie, it envisions that in 2015, we would be using fingerprint [scanning] to access or to unlock doors, instead of door knobs or locks, and even use [fingerprint scanning] to pay for taxis, or Uber, for that matters. Now, we’ve been lagging behind just a little bit, but we’re getting there.

Here comes the issues with biometric authentication Android. The obvious problem here is that it’s quite impossible to interact with or sidestep the biometric prompt in the test flow without a physical intervention, because it’s not true, or even possible to programmatically intervene with the secure processor that stores the raw fingerprint data or the fingerprint scanner hardware. So, that’s really a problem, right? That’s really obvious.

There is a huge gig economy around clicking mobile devices – they’re called click farms and they are all over the world in many parts of the world. However, I don’t think it’s a good idea to have a gig worker run a fingerprint on the apps that we want to test.

So, let’s dive into a very high level flow of biometrics process in Android here. It usually start with either a full-view activity or a dialogue component in the UI, usually triggered by some kind of user interaction, like tapping on a button or changing to a new activity. And then, it runs the fingerprint manager that implicitly talks to the fingerprint service that runs in the background. And then, the service will communicate with the fingerprint scanner hardware. Let’s see how that works out.

Here, I can see that programmatically, when the UI is loaded, it’s going to instantiate the fingerprint manager, or it’s going to ask for the readiness of the fingerprint manager. Afterward, when we call a “Authenticate” method on this instance of fingerprint manager and pass along relevant parameters like the crypto object and call back object, it will implicitly talk to the fingerprint service. And then the service will ask the fingerprint scanner to warm itself up. What that means is the scanner will start running and pulling for the user’s fingerprint.

And once there’s the fingerprint here, as you can see here, a nice, dark fingerprint impression is captured properly by the scanner. Just so you know, there’s a few conditions when the fingerprint impression might not be registering properly. Like for instance, the scanner is dirty or the angle of the impression is not really optimal.

But, that being said, when the sensor gets a pretty good impression of a fingerprint, it will validate the fingerprint with the one that’s stored in another part of Android called the Trust Zone, which is an isolated hardware with its own operating system and it can never be accessed directly from Android. Once everything is validated, it’s going to return “Result” to the service and then the service will tell the fingerprint manager to run the relevant callback based on the result and pass back here.

Either it’s “onSucceeded,” “onFailed” or “onError.” In the case of onSucceeded, the action is likely to dismiss the UI prompt or dialog, and then maybe fetch the user’s data from the database or the device cache, and then populate the next activity with the data, and then move the user to the next activity, creating a sense of the user of being signed in.

With onFailed or onError, a good fallback or a good default would be to show a prompt or maybe a toast that tells the user about the error or the failure, and always make sure to provide good feedback and graceful fallback in the case of failure or errors, so that the user knows where to go to just enter the username, email, or password.

Here’s a little video demo of myself: I’m testing out an app here called “healthtest” – it doesn’t do much, but just enough. Whenever we tap the log-in button, it’s going to display a dialog asking for the fingerprint. And once it can validate a fingerprint, it’ll just dismiss the dialog. Let’s see what happens here. [Pause.]

So at this point, I am tapping the log-in button, and then I am going to use my finger to log in, and that’s it. There’s some audio there. [Repeat of video.] It’s a very simple flow, but it’s a flow that’s normally not easy to automate.

Here’s another video demo of the same app, but this time it’s using our HeadSpin fingerprint SDK or biometrics SDK. There’s no fingerprint involved here. All I’m doing is sending a post request – as you can see here, it looks like a token, but it’s the post request for the payload here, and that’s the prompt. And then again, that’s your 200 status code – success, true. And then, it just dismissed the prompt.

Before we go on and talk about how to install this awesome library, be reminded that this only works with Android API level 23 and later. This is not specific to the library – just the versions or the ones that support the fingerprint feature. And then secondly, the test device should have a valid fingerprint on the role – the SDK is not doing anything magical, so the target device needs to be able to authenticate with your fingerprint. And last but not least, this goes without saying, do not distribute your test build in the wild. You run the risk of somebody hijacking your users biometrics by using external connection. So please, we recommend only using our test build with our highly secure devices.

Installing HeadSpin’s Android biometrics SDK

So without further ado, let’s head over to headspin.io Settings page. If you are already a HeadSpin costumer, you should be able to get access to the download link and the documentation link, which talks in more detail about what we are discussing right now.

Then, head over to your Android studio editor. Hopefully, this is how your Android studio environment looks for most of you guys. First of all, create a directory called “source/main/libs” under your apps directory. This is pretty optional – if you already know what you’re doing, you don’t have to do it – just make sure you have a nice safe directory for the library.

And then, you download it: instruments-release.arr file to the newly-created “libs” directory. Again, it can be right in the directory. In your app module “build.gradle” – the line “implementation(name: ‘instruments-release’ , ext: ‘aar’) under dependencies block. And last but not least, sometimes, your environment might not be able to find the library. In that case, add this “flatDir” and then provide it with your libraries directory under the “Repositories” block, and you should be good to go.

Okay. So now let’s walk through some code. This is the code for the fingerprint dialog segment. It’s the code for the UI that you’ve already seen on the test app that’s part of the biometrics. These are all pretty standard – really up to how you write your code.

Please notice the two lines here. For your test build, to integrate our biometrics SDK:

Import io.headspin.instruments.HSFingerprintManager

So io.headspin.instruments is the package name.

It’s helpful to also import HSFingerprintAuthCallback, which is a helpful wrapper around the original authentication callback that provides useful defaults for all the cases that you may get from the authentication process.

Now, let’s go through this class. You’ll notice here I actually define the HSFingerprintManager variable here early within the class. And I also define my custom callback here that inherits the HSFingerprintAuthCallback that I imported from the library. So, as you can see, I only care about customizing the “onAuthenticationSucceeded” case. So, I only override this method here, and what I wanted to do is to just dismiss the dialog, which is exactly what I’m doing here, and I don’t really care about onFailed or onError.

The HSFingerprintAuthCallback provides defaults – it will display a toast with some helpful message of the failure or the error, but of course you can still override those.

Okay. Let’s move on. In the onAttach method here, this gets run when the view is loaded, or the dialog in this case is loaded. This is where you usually want to instantiate your HSFingerprintManager instance and assign it to your HSFingerprintManager variable.

If you’re using an activity instead of a dialog, the method is probably going to be onCreate or something else, but the concept here is the same. You want to instantiate HSFingerprintManager here when the view gets loaded.

Moving on here, onDetach is equivalent to the onDestroy method. Before we clean up, we’ll want to view HSFingerprintManager with the close method. What this does is it cleans up any TCP connections in the background that are communicating with the external or, in this case, the HeadSpin platform http server.

This is the onCreate dialog method. We’d assign our custom callback to a helper. And then, this is where we create cryptoObject.

And then, this is a very important part. We call authenticateMethod on HSFingerprintManager, then passed the cryptoObject, and then the handler or the Callback as parameters.

Remember, this is the part when it starts to warm up the fingerprint scanner. So, when you call this, it’s going to load the scanner and the scanner will start to pull for the fingerprint from the user.

This is where you actually set some useful messages and [do] some button styling. The majority of the code will be about creating a relevant key in order to create the secure cryptoObject. We won’t get into that, but please make sure you don’t copy these algorithms here because they are not recommended for production.

These are all about generating keys, very standard. Something to note here: you might want to check for permission first and [whether] your device has permission to use fingerprint at all. Otherwise, there’s no use in authenticating. You should just provide a meaningful toast with a message to the user.

This is how you actually test hasEnrolledFingerprints on your device. If [it’s not on the device], you’re better [off] just flashing a toast or a message: something like, “Register at least one fingerprint in the settings.”

If there’s anything else that is unclear to you and you want to get more information, please feel free to consult are awesome documentation. This concludes our webinar for today. We have a couple extra minutes for a Q&A session, so I’m going to check for some questions here. By the way, now is the time, if you’re interested, you can get in touch with us. Head over to headspin.io/contact, include this promo code [ROCKSPIN] in your message to get your free trial.

Article Source:

This article was originally published on:

https://www.headspin.io/blog/automating-biometric-authentication-in-android