What is the best way to avoid test automation framework maintenance risks?

To avoid test automation framework maintenance risks, prioritize modular design to enhance flexibility and ease of updates. Regularly review and refactor code to prevent technical debt. Implement version control for better tracking. Leverage robust error handling to minimize script failures. Invest in comprehensive documentation for easy onboarding and maintenance. Conduct periodic code reviews and encourage knowledge sharing within the team. Stay updated on tools and technologies to adapt the framework accordingly. Foster a proactive culture, addressing issues promptly to prevent them from escalating. A well-structured, documented, and adaptable framework minimizes maintenance challenges and ensures long-term sustainability.

- Avoid duplication and low-value tests: Too many automated tests sometimes are red flags that something is wrong with your automation approach. - Test workflows and not the features: It's important to test how different features interact and work together rather than testing individual features. - Know what developers already test on the unit and integration level: This can help avoid unnecessary overlap and redundancy in testing. Remember, the key to successful test automation is regular maintenance and updates. It's not a set-it-and-forget-it process.

To mitigate maintenance risks, the initial step is selecting a framework aligning with your project needs. Options like linear, modular, data-driven, keyword-driven, hybrid, and behavior-driven frameworks exist, each with distinct attributes. Evaluate these frameworks based on factors such as complexity, flexibility, reusability, readability, and reporting. For instance, with Robot Framework, a keyword-driven framework, focus on ensuring well-defined, consistent, and user-friendly keywords for effective implementation and long-term maintainability.

The answers to the following questions usually help me in choosing a framework: - What is the nature of my app? Consider the nature of the application you are testing. Some frameworks are better suited for web applications, while others may be more suitable for mobile, desktop, or API testing. - What languages do my colleagues use? Choose a language that aligns with the skills of your development and testing teams. - Is there a string community? A framework with a strong and active community can be a better choice. Community support ensures that you can find solutions to common issues, access forums for discussions. - How can I implement this? Check if the framework easily integrates with your CI and CD pipelines.

Don’t test features that are still in the beta phase or under development. This can help prevent wasting time and resources on testing unstable or changing functionalities that may not reflect the final product.

Automated tests are still the code so all rules for coding should apply for automated tests as well such as clean code - so readable, understandable without comments and duplications allowed only to increase readability.

The second step in mitigating maintenance risks is adhering to coding standards and conventions for an organized and readable framework. Establish rules for naming, formatting, commenting, structuring, and documenting code to maintain consistency. These standards prevent common errors like hard-coding values or using magic numbers, enhancing the code's clarity and longevity. By following these guidelines, your framework becomes easier to understand, debug, and modify, promoting effective collaboration among team members.

Do not select the framework based solely on the preferences of your test automation specialist. It's advisable not to do this for that reason alone. Choosing a rare technique may work well as long as that specialist is involved in the project. However, when maintenance is required by another person, opting for a more common framework increases the likelihood of finding someone capable of continuing the work.

I am a firm believer of substance over form, meaning that if all you care is that the code should look pretty but methods, efficiency, wrappers, test data management, locators .. etc are not efficient then what is the point?

basically, Adhering to coding standards and best practices ensures that the code is clean, well-structured, and easy to maintain.

VC like Git enables multiple team members to collaborate on the framework while keeping track of any modifications or updates made

To mitigate maintenance risks, the third step is implementing version control for your framework and test scripts, with systems like Git providing effective tracking and code management. Git enables seamless branch creation, conflict resolution, and collaboration among developers. This approach offers crucial features like code backup, history auditing, and deployment automation. Integrating Git with Robot Framework, for instance, is achieved through commands like git init and git commit, establishing organized version control for a streamlined development process.

Version control is also a critical component of Change Control. Having a clearly documented, organized audit trail is essential for data transparency, adequate regulatory compliance, and ultimately, safety of the End User.

While using a VC tool like Git where code review is encouraged before a merge, is always good practice to invite a developer to review the automation PR's as well as other relevant team members. This way the code remains coherent with the rest of the application and any errors can be caught early.

Use version control systems (e.g., Git, Bitbucket) to manage and track changes in your automation code. This facilitates collaboration and deployment, provides the ability to revert to previous versions, and helps identify what changes have been made.

Keep it simple, easy to adopt and versatile. Encourage more and more teams to use it...this will keep it updated and maintained.

The fourth step in mitigating maintenance risks is adopting modular and reusable code, reducing duplication and complexity. Modular code, organized into independent units like functions or classes, enhances clarity. Reusable code, such as variables or custom keywords, promotes efficiency and scalability. Leveraging Robot Framework's built-in or custom libraries exemplifies this approach, enabling the reuse of common functionalities across tests. This practice not only streamlines development but also ensures consistency and maintainability in the long run.

Don't bother with value checks, pull screenshots on every click, and compare them as color arrays across version runs. It's better to be aware of any difference, not just specific ones.

The use of POM(Page Object Model) is crucial for this step. Utilizing POM in your project makes it much easier to update when any of your selectors change.

Commonly used libraries should be well organized and a dedicated Tech team can make sure they remain up to date. Common libraries should always stay outside the regularly updated modules.

Address technical debt proactively by integrating refactoring into your work when code deviates from the current framework direction. During code reviews on platforms like Github, go beyond approved changes—review the entire file, provide feedback on pull requests, and ensure immediate adjustments. Implement linters and similar tools in your pipeline to maintain coding standards during code merges, eliminating the need for individuals to run them locally. This approach ensures a lean and easily manageable codebase for all parties involved.

The fifth step in mitigating maintenance risks is regularly reviewing and refactoring your code to enhance its quality and performance. Code reviews, employing tools like analyzers and debuggers, help identify errors and bugs. Refactoring involves simplifying and improving code readability without altering functionality. This process ensures a reliable, robust, and adaptable framework. For instance, using Robot Framework's dry-run mode allows script review, and the robot.tidy tool facilitates code refactoring, contributing to long-term code maintainability and effectiveness.

Version control: Use a version control system like Git to manage your codebase.Review the PullRequests Continuous integration: Implement a continuous integration (CI) system that automatically builds and tests your codebase. CI helps catch issues early Refactor the code by eliminating duplication, simplify complex logic, and improve the overall design of your test framework.

If frequent code review meetings are held in a team, all members can get equipped with the knowledge faster such that refactoring and reviewing becomes a piece of cake.

When the tools you use release a new version, apply the features of this version to your code. Check your locators at specific intervals to ensure your code runs faster. If there is a possibility of using a faster selector, modify your code accordingly. For instance, a CSS selector tends to work faster than Xpath.

Utilize tools like GitHub Dependabot to identify and address issues with dependencies promptly. If critical problems arise with updates, consider downgrading to a stable version temporarily and upgrading once the relevant issues are resolved.

Keeping dependencies updated can help mitigate the (often costly) penalties of the Cost of Nonconformance. Prioritizing and frame-shifting the expenses involved with the Cost of Conformance is a proactive approach toward generating and maintaining healthy, robust R&D and operational activities.

Use pom.xml in most cases to manage dependencies. This allows for easy maintenance and management of all dependencies for any given framework.

Desolving dependancies is a crutial point. Esp. when we are talking about e2e automayted test in serverless micro-services based architecture. If you have complicated architecture, lots of microservices, lots of product configuration preconditions to be met - it can easily turn into a nightmare. Cloud service provider is also important due the impact on tests run. Best way to avoid that - is to prepare pre-configured droplet and use it in your auto-tests fixtures.

Few things to consider: 1. Make sure application is ready for automation - no dynamic locators, elements have ids (or whatever you use) 2. Rule of thumb for test automation is independent, data-driven and as small as possible. So before starting to automate user acceptance tests take a step back (or down the testing pyramid) and focus on system or integration tests. Create data, specific state before tests using apis (or straight to DB, but not preferable) and then continue in UI 3. Learn the tool you use. Bad code happen because people try to create a solution based on previous knowledge and not seeking for new solutions which are probably already build in the tool

-Build the right coverage you need - focus on risk and avoid creating too many auto tests. Too many auto tests can be a red flag that something is wrong with your testing approach. -Avoid duplication and low-value tests - ensure that you are not duplicating tests or creating low-value tests that do not provide any additional value. -Test workflows and not the features - test the workflows of your app instead of individual features. This will help you identify issues that may arise when different features are combined. -Know what developers already test on the unit and integration level - ensure that you are not duplicating tests that developers are already testing. -Know what you can effectively be tested manually - no need for auto tests.

Avoid automating everything, not every scenario should be automated. You want to focus on the real e2e flows, the mirror of a real use case

1. create automated tests specifically for the framework to ensure its stability and reliability 2. Identify real issues on an early stages

Every Testing Automation framework has its own lifecycle. Inception > Design > Development > Maintenance > Decommission I don’t think any framework is future proof. So Maintenance cycle must be inbuilt into it.