Software Testing Basics: Automated Functional Testing FAQs

Automated functional testing allows software teams to save time in executing frequently repeated tests that rarely change. Learn more about how automated testing fits into a comprehensive digital quality program.

What is automated functional testing and how does it differ from manual functional testing?

Automated functional testing is a type of software testing that uses automated tools to execute tests and verify the functionality of a software application. Automated functional testing runs test scripts to evaluate software functionality, while in manual functional testing, a human tester manually executes tests and verifies the results. 

Key differences between automated functional testing and manual functional testing include:

• Speed: Automated functional testing is much faster than manual functional testing, as it can execute hundreds of tests in a matter of minutes. This can help to reduce the time it takes to complete a testing cycle and ensure that new features are tested quickly and thoroughly.
• Accuracy: For certain types of tests, automated functional testing eliminates the possibility of human error. This can help to ensure that defects are identified and fixed before they reach production.
• Repeatability: Automated functional testing is more repeatable than manual functional testing, as it can be executed multiple times with the same results. This can help to ensure that tests are consistent and reliable.
• Cost: Automated functional testing can be more cost-effective than manual functional testing, as it can reduce the need for human testers. This can help to save time and money in the long run. 
• Scope: Automated functional testing can be used to test a wider range of features and scenarios than manual functional testing. This can help to ensure that all aspects of the software application are tested thoroughly.

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What tools are commonly used for automated functional testing?

Some commonly used test automation tools covering different types of applications and development environments include: 

• Selenium: An open-source tool for web application testing that supports multiple browsers, programming languages, and operating systems..
• Cucumber: A tool for behavior-driven development (BDD) uses plain language (Gherkin) to describe application behavior, making it easy to understand for non-technical stakeholders.
• Appium: Another open-source tool for automating mobile applications, Appium supports native, hybrid, and mobile web applications for iOS and Android.
• SoapUI: A tool for testing SOAP and REST web services that allows functional, regression, and load testing.
• Postman: This tool provides a user-friendly interface for building and testing API requests.
• Robot Framework: This generic open-source automation framework uses a keyword-driven testing approach, supporting easy-to-read and write test cases.
• Playwright: A tool that enables end-to-end testing for web applications across any browser or platform. 
• Cypress: Focused on test-driven development for end-to-end web application testing, Cypress brings together multiple tools to enable simultaneous testing and development.  
• Tosca: This tool offers codeless, model-based automation for functional and regression testing.
• Test Complete: A tool that allows testers to build scriptless or keyword-driven tests for desktop, web and mobile apps.

What are the benefits and limitations of automated functional testing?

Automated testing offers many benefits in terms of efficiency, coverage, cost savings, consistency and scalability. Once tests are automated, they require minimal human intervention and can be executed repeatedly. This can be valuable for regression testing to ensure changes don’t interfere with existing functionality. Automated tests provide consistency and multiple tests may be run concurrently, reducing testing time. In many cases, automated tests take less time to execute, providing additional speed. 

While automated tests can be integrated into CI/CD pipelines, find defects earlier in the SDLC, reduce human error and help increase coverage, they do have limitations. The initial set-up costs and learning curve can be steep, and running a large suite of automated tests can be resource-intensive, demanding significant hardware and software resources. In addition, tests need to be updated and maintained as applications evolve. Automated tests can only check scenarios that have been explicitly programmed, potentially missing unexpected behaviors. They’re also not suitable for all types of testing. Tests requiring human creativity and judgment, like exploratory testing, and subjective tests, like usability testing, simply cannot be automated. 

How do you choose the right automation tool for your needs?

Choosing the right test automation tool involves several considerations to ensure it fits the specific needs of your project and organization. Here are some steps to help you make an informed decision:

1. Understand your project requirements: Consider what type of application you’re developing, your technology stack (including the frameworks, languages and tools used in your application) and what types of tests you want to automate. Factor in your available budget, team expertise and resource constraints.
2. Evaluate tool features: Assess the interface – is it user-friendly? How easy is it to create and maintain scripts? Check compatibility with your development languages and CI/CD pipelines, as well as integration with version control systems, test management tools and other DevOps tools. Determine whether the tool offers sufficient cross-platform support and extensibility – can it test across all the various browsers, devices, and operating systems you need? How well does it support plugins, extensions, and custom code? 
3. Consider non-functional aspects: What type of training, documentation and support options are available? Is there an active user community? What about scalability, maintenance and ongoing costs and fees?
4. Assess reporting and analytics: Look at the quality, clarity, and customization options of the test reports, as well as the insights available on test coverage, defect trends, and overall test performance.
5. Examine long-term viability: Research the vendor and tool’s reputation and stability, as well as the frequency and quality of updates and new feature releases. How well does the tool adapt to emerging technology and trends?

How do you write effective test cases for automated functional testing?

Well-crafted test cases are crucial to getting accurate and reliable results from your automated tests. To write effective test cases for automated functional testing, start by clearly defining the test objective. Before writing a test case, identify the specific functionality or feature you want to test. Ensure that the test objective is concise, measurable, and achievable. 

Keep it simple and focused.  Avoid complex test cases that cover multiple scenarios or functionalities. Instead, break down tests into smaller, independent test cases that focus on a specific aspect of the application.

Follow a standard template or format for writing test cases. This will help ensure consistency and make it easier to review and maintain test cases. A typical template includes sections for test case ID, description, preconditions, steps, expected results, and test data. Use user stories and acceptance criteria as a basis for writing test cases — this ensures that your automated tests align with the application’s functional requirements and user expectations.

Next, identify and prioritize critical scenarios. Focus on high-risk, high-impact scenarios that could significantly affect the application’s functionality or user experience. Prioritize test cases based on business requirements, user workflows and potential failure points. Make sure to include multiple input scenarios and edge cases. Include test cases that cover various input scenarios, such as valid and invalid data, boundary values, and error handling. This helps validate that your application can handle unexpected inputs and edge cases.

Regularly review and refine your test cases to ensure they remain relevant and effective. Update test cases to reflect changes in the application, new features, or modified functionality. Involve cross-functional teams in the test case development process. Involve developers, product owners, and other stakeholders to see to it that test cases are accurate, comprehensive, and aligned with the application’s requirements.

How can teams integrate automated functional testing into the development process?

Integrating automated functional testing into the development process involves several key steps to ensure it complements and enhances the development workflow effectively. Once you’ve defined the objectives and scope for automation and selected your tools, develop a testing strategy. Create a comprehensive test plan that includes automated and manual testing, and identify and prioritize test cases for automation. Focus on high-impact areas such as regression tests, critical functionalities, and repetitive tests.

Integrate with your CI/CD pipeline by setting up a CI server (e.g., Jenkins, GitLab CI, Travis CI) to automatically run tests on every code commit. Integrate automated tests into the deployment pipeline to ensure only tested code is deployed.

Develop and maintain your test scripts. Write automated test scripts using your chosen tools. Follow best practices for readability, maintainability, and reusability. Make sure to store test scripts in a version control system (e.g., Git) alongside the application code.

Create a stable and consistent test environment that mirrors the production environment. In addition, you’ll need to ensure the availability of required test data and consider using tools for test data generation and management. Determine whether you want to schedule regular test runs (e.g., nightly builds) to catch issues early, or automatically trigger tests on specific events like code commits, pull requests, or before deployments.

Monitor and analyze test results. Set up automated test reporting to provide clear and actionable insights, using tools that integrate with your CI/CD pipeline to visualize test results. Configure alerts for test failures to ensure timely attention and resolution.

To foster continuous improvement, encourage feedback from developers, testers, and other stakeholders. Periodically review and update test cases and scripts to accommodate changes in the application and to optimize test coverage. Provide ongoing training and support to team members to keep up with new tools, technologies, and best practices.

Follow these best practices for successful integration: 

• Incorporate testing early in the development cycle to identify and fix issues sooner.
• Foster collaboration between developers, testers, and other stakeholders to ensure a shared understanding of the testing process and goals.
• Start with a small, manageable set of tests and gradually expand the scope of automation.
• Design tests to be modular and reusable to minimize maintenance efforts.
• Execute tests in parallel to reduce test cycle time and improve efficiency.

What are some best practices for automating functional tests?

Before automating functional tests, clearly define what you want to achieve with each test case. Identify the specific functionality or feature you want to validate and the expected outcomes so you can create focused and relevant test cases.

Prioritize test cases based on business criticality, risk, and frequency of execution. Focus on automating high-priority test cases that provide maximum coverage and ROI. Use a modular approach. Break down complex test scenarios into smaller, independent modules, which enables easier maintenance, updates, and reuse of test cases, reducing overall automation efforts.

Implement data-driven testing. Data-driven testing allows you to execute multiple test cases with varying input data, increasing test coverage and reducing test maintenance. Use data-driven testing to automate functional tests that require different input parameters or scenarios. 

Leverage Page Object Model (POM) — the POM design pattern separates test logic from element identification, making test maintenance more efficient. By using POM, you can easily update test cases when UI changes occur, reducing test automation overhead.

Regularly monitor and analyze test results to identify trends, patterns and areas for improvement. This helps refine test automation strategies, optimize test suites, and improve overall test efficiency. In addition, regularly review and refactor test automation code to prevent technical debt and improve test reliability.

Finally, continuously refine and improve your test automation strategy based on lessons learned, new technologies, and changing project requirements. Stay up to date with industry trends and best practices to maximize the benefits of automated functional testing.

What are some ways to measure the success and ROI of automated functional testing?

Some key metrics and strategies to help you evaluate the effectiveness of your automated functional testing efforts include: 

• Test coverage: measure the percentage of automated tests covering critical functionality, user journeys, or business processes. This metric helps you identify gaps in testing and prioritize automation efforts.
• Test automation ratio: calculate the ratio of automated tests to manual tests – a higher ratio indicates greater efficiency and cost savings.
• Defect detection rate: track the number of defects detected by automated tests versus manual tests. This metric highlights the effectiveness of automated testing in identifying defects early in the development cycle.
• Test cycle time reduction: measure the reduction in test cycle time you achieve with automation. Faster testing cycles enable quicker release times and improved time-to-market.
• Cost savings: calculate the cost savings achieved through automated testing, including reduced labor costs, infrastructure expenses, and minimized rework.
• Mean time to detect (MTTD): measure the average time taken to detect defects through automated testing. Lower MTTD indicates faster defect detection and resolution.
• Mean time to resolve (MTTR): Track the average time taken to resolve defects detected through automated testing. Lower MTTR indicates faster defect resolution and improved overall quality.