What are some of the best practices for test automation in agile testing?

The very first thing is to understand the needs of project, its architecture, kind of scenarios that are must for automation to have. This helps in getting to right tool and framework ,programming language Define a test automation strategy document, continously evolve it. This helps down in identifying what all the framework should have like pipelines set up ci integration, executions, data creation, environment setup.

The most important aspect is don’t make Automation the first thing to track and focus on. Focus should be on a good testing strategy , Automation workflows will automatically flow in once we capture the complete test strategy. Automation should be good to have but not must have in the initial rial stages of test planning.

It's a good practice to create a User Story first before you automate a certain test case. This allows you create sub-tasks and specify your acceptance criteria to help you track your progress. Jira allows you to do both and allows you to create a feature branch that corresponds to your automated test case. When your automation script is ready, go ahead and create a Pull Request using Bitbucket to have your code reviewed and later on merged to the main branch.

Some best practices for test automation in agile testing include: prioritizing test cases, maintaining a balance between manual and automated testing, ensuring test scripts are reusable and maintainable, integrating testing early in the development cycle, leveraging continuous integration and continuous delivery (CI/CD) pipelines, and regularly reviewing and updating automation strategies.

Considering Agile testing strategy , we should not be jumping into automation rightaway instead there should be a clear focus, defined test strategy and plan. Automation can be implemented as we mature down the iterations, and should be only for the necessary ones and not all .

The test automation pyramid recommends having the most automated tests at the unit test level, testing individual components in isolation. As you move up the pyramid there should be progressively fewer integration tests, testing how components work together, and end-to-end tests simulating user journeys across the whole system. This distribution allows fast feedback through isolated tests targeting where changes occur, while still verifying business logic flows. It replaces traditional test phases with continuous, targeted testing to provide fast feedback aligned to agile delivery.

I would say not to deviate from the very goals of test automation. I've seen people keep automating tests but do not actually have a plan to execute them on a timely basis. I've seen teams automating everything which is a bad choice. It is also important to automate the right number of tests and achieving the right coverage. You cannot afford to miss out critical scenarios and keep automating crap. Overall, you need to have optimum number of tests at unit, Integration and E2E level, with a goal of implementing the best quality practices. I'd rather say quality practices rather than automation practices just to remind the purpose.

In agile testing, adhering to the test automation pyramid is crucial. It emphasizes prioritizing unit tests over integration tests and end-to-end tests. This approach ensures higher coverage, faster execution, and lower maintenance. Unit tests validate individual components, integration tests verify interactions between components, and end-to-end tests simulate user journeys. Balancing these layers optimizes testing efficiency and effectiveness.

TDD is often referred to unit tests only -> so we can also apply ATDD in test automation, to automate tests which are derived from teh acceptance criteria.

In agile testing, employing the test-driven development (TDD) approach is paramount. TDD entails writing tests prior to code, ensuring expected behavior is defined upfront. It fosters clean, maintainable code, discouraging over-engineering. By writing focused tests, automation becomes easier, facilitating frequent testing iterations and enhancing overall development efficiency.

Rather than distinct testing phases, continuously evolve a living model of system behaviour spanning project stages. Kickstart with collaboration to explore examples. Focus test design on encoding expectations in the model for validation. Facilitate sessions across roles to refine semantics. Generate tests from examples. Shift left builds shared understanding early on. Shift right by linking models to production monitoring. Analyse drift between usage and expectations. Regression test via updated models. Accelerates learning essential for value as complexity grows.

I’ve found that metrics collected from development can give effective visibility into how to adopt these two strategies. Shift-left: If the data is showing a spike in bugs pertaining to product robustness or reliability, I work with the product team to see how we can improve testing early on and ensure full-scale testing is taking place before moving releases to production. Shift-right: If the data shows increased change requests from end users post-release, I work with the product team to ensure we are gathering detailed requirements so informative time estimations for development are collected and help continue delivering value. Benefits of metrics: - Informed Decision Making - Quality Assurance - Efficiency - Customer Satisfaction

In agile testing, implementing both shift-left and shift-right strategies is crucial. Shift-left involves starting testing early in the development process, while shift-right extends testing post-deployment. These approaches ensure alignment with business needs, faster defect detection, reduced testing effort, and improved user satisfaction. By integrating testing throughout the software lifecycle, you enhance quality and minimize costs effectively.

Involve stakeholders, including developers, testers, product owners, and users, in test automation efforts from the early stages of the project. Maintain open communication channels to ensure alignment on automation goals, priorities, and progress.

Successful test automation requires early, ongoing team collaboration rather than siloed efforts. Engage product experts to define requirements. Involve developers in frameworks and code reviews. Review tests jointly across roles. Demo capabilities hands-on, not just written reports. Measure and communicate automation coverage to justify priorities amidst competing demands. For maximum business alignment, collaborate early on test models, seek continuous feedback during development, report post-release on effectiveness.

In agile testing, effective collaboration and communication with stakeholders are paramount. Engage with developers, testers, product owners, and others regularly using diverse methods like meetings, reviews, and feedback loops. Share automation goals, results, and challenges to ensure alignment with project vision and priorities. This fosters transparency, trust, and accountability, enhancing the success of test automation endeavors.

The biggest trap in test automation is scripts that provide little ongoing value. Instead, develop living examples that form part of the system model. Facilitate regular modelling sessions to build examples collaboratively around the latest insights. Maintain value by linking examples directly to the production code under test. Generate executable tests from the models to optimize coverage. Review analytics on assertion failures and production incidents to highlight areas of model drift. Updating the single source of truth this way keeps your examples relevant as the system evolves. This intrinsic maintenance aligns the testing focus with the current system behaviour, avoiding solely outdated UI test automation approaches.

Integration Automation Frameworks with Test Data Management Incorporate the tests you define during your sprints into the test data management framework or tool. It is crucial to enable running test scripts multiple times without relying on specific test data. As test scripts consume data during execution, the data's state changes with each run. Integrating the automation framework with synthetic data generation tools like Genrocket enables on-demand test data generation, enhancing the script's overall test coverage. This integration empowers efficient test execution and eliminates dependencies on fixed data, contributing to a more comprehensive testing approach.

In agile testing, maintaining and optimizing test automation is ongoing. Regular review and updates are essential for relevance and reliability. Monitor performance using metrics like test coverage and execution time to identify and address issues. Utilize data to improve quality, efficiency, and ROI of test automation continuously.

Invest in training and skill development for team members involved in test automation to ensure proficiency with chosen tools and frameworks. Continuously evaluate and evolve test automation practices based on feedback, lessons learned, and changes in project requirements or technology landscape. Integrate test automation into the continuous integration/continuous delivery (CI/CD) pipeline to enable automated testing as part of the software delivery process.

Prioritizing reusability is crucial in the design of automated test frameworks and scripts. It involves crafting modular and generic test components that can be utilized across various test cases, promoting efficiency. The key steps include recognizing common patterns, dedicating efforts to initially develop shared test modules, maintaining discipline to actively use reusable elements, and consistently refining them based on feedback. Reusability plays a pivotal role in ensuring that test automation functions at its optimal efficiency

Consider the scalability of your test automation framework. Ensure it can handle increasing test suites and evolving project requirements. Additionally, prioritize cross-functional collaboration, fostering shared ownership of testing responsibilities among team members. Encourage a culture of continuous learning and improvement, where feedback is welcomed and used to refine testing processes. Lastly, remember the importance of balancing automation with manual testing, as some scenarios may be better suited for human evaluation.