Tips to Improve Software Testing Reliability

Don’t Focus Too Much On Writing More Tests Too Soon 📌 Prioritize Quality over Quantity - Make sure the tests you have (and this can even be just a single test) are useful, well-written and trustworthy. Make them part of your build pipeline. Make sure you know who needs to act when the test(s) should fail. Make sure you know who should write the next test. 📌 Test Coverage Analysis: Regularly assess the coverage of your tests to ensure they adequately exercise all parts of the codebase. Tools like code coverage analysis can help identify areas where additional testing is needed. 📌 Code Reviews for Tests: Just like code changes, tests should undergo thorough code reviews to ensure their quality and effectiveness. This helps catch any issues or oversights in the testing logic before they are integrated into the codebase. 📌 Parameterized and Data-Driven Tests: Incorporate parameterized and data-driven testing techniques to increase the versatility and comprehensiveness of your tests. This allows you to test a wider range of scenarios with minimal additional effort. 📌 Test Stability Monitoring: Monitor the stability of your tests over time to detect any flakiness or reliability issues. Continuous monitoring can help identify and address any recurring problems, ensuring the ongoing trustworthiness of your test suite. 📌 Test Environment Isolation: Ensure that tests are run in isolated environments to minimize interference from external factors. This helps maintain consistency and reliability in test results, regardless of changes in the development or deployment environment. 📌 Test Result Reporting: Implement robust reporting mechanisms for test results, including detailed logs and notifications. This enables quick identification and resolution of any failures, improving the responsiveness and reliability of the testing process. 📌 Regression Testing: Integrate regression testing into your workflow to detect unintended side effects of code changes. Automated regression tests help ensure that existing functionality remains intact as the codebase evolves, enhancing overall trust in the system. 📌 Periodic Review and Refinement: Regularly review and refine your testing strategy based on feedback and lessons learned from previous testing cycles. This iterative approach helps continually improve the effectiveness and trustworthiness of your testing process.

Let’s Talk Automation Testing — The Real, Practical Stuff We Deal With Every Day. If you’re in QA or an SDET role, you know automation isn’t about fancy frameworks or buzzwords. It’s about making testing faster, more reliable, and easier for everyone on the team. Here’s what actually matters: 1. Stability first A fast test that fails randomly helps no one. hope, you would agree? Teams trust automation only when it consistently tells the truth. Fix flakiness before writing anything new. 2. Manual + Automation = Real Quality Not everything needs automation. Manual testing is still crucial for user experience checks, exploratory testing, and edge cases that require human intuition. Automation supports manual testing — it doesn’t replace it. 3.Automate with intention Prioritize high-risk, high-usage flows. Login, checkout, search, payments — these are where automation creates real value. 4.Keep the framework clean and maintainable ( very imp step) Readable tests win. If someone new can’t understand or extend your suite, you don’t really have automation — you have tech debt. 5.Integrate early into CI/CD Automation only works when it’s continuous. Quick tests on every commit. 6. Make decisions based on data Look at failure patterns, execution time, and actual coverage. Data keeps automation aligned with the product, not just the backlog. At the end of the day, good automation suite is quiet, stable, and dependable — and it frees up manual testers to do the real thinking. 👉 What’s one practical testing tip you think every QA/SDET should follow? #AutomationTesting #SoftwareTesting #SDET #TestAutomation #QualityEngineering #ManualTesting Drop your thoughts — always great learning from others in the field. 💬🙂

Here’s my step-by-step action plan whenever I work with a client to help them get a new automation project started. Maybe it’s useful to you, too. 0. Write a single, meaningful, efficient test. I don’t care if it’s a unit test, an integration test, an E2E test or whatever, as long as it is reliable, quick and produces information that is valuable. 1. Run that test a few times locally so you can reasonably assume that the test is reliable and repeatable. 2. Bring the test under version control. 3. Add the test to an existing pipeline or build a pipeline specifically for the execution of the test. Have it run on every commit or PR, or (not preferred) every night, depending on your collaboration strategy. 4. Trigger the pipeline a few times to make sure your test runs as reliably on the build agent as it does locally. 5. Improve the test code if and where needed. Run the test locally AND through the pipeline after every change you make to get feedback on the impact of your code change. This feedback loop should still be VERY short, as we’re still working with a single test (or a very small group of tests, at the most). 6. Consider adding a linter for your test code. This is an optional step, but one I do recommend. At some point, you’ll probably want to enforce a common coding style anyway, and introducing a linter early on is way less painful. Consider being pretty strict. Warnings are nice and gentle, but easy to ignore. Errors, not so much. 7. Only after you’ve completed all the previous steps you can start adding more tests. All these new tests will now be linted, put under version control and be run locally and on a build agent, because you made that part of the process early on, thereby setting yourself up for success in the long term. 8. Make refactoring and optimizing your test code part of the process. Practices like (A)TDD have this step built in for a reason. 9. Once you’ve added a few more tests, start running them in parallel. Again, you want to start doing this early on, because it’s much harder to introduce parallelisation after you’ve already written hundreds of tests. 10 - ∞ Rinse and repeat. Forget about ‘building a test automation framework’. That ‘framework’ will emerge pretty much by itself as long as you stick to the process I outlined here and don’t skip the continuous refactoring.

In an ideal world, we’d get instant feedback on software quality the moment a line of code is written (by AI or humans) (we’re working hard to build that world, but in the meantime); how do we BALANCE speed to market with the right level of testing? Here are 6 tips to approach it: 1 - Assess your risk tolerance: Risk and user patience are variable. A fintech app handling transactions can’t afford the same level of defects as a social app with high engagement and few alternatives. Align your testing strategy with the actual cost of failure. 2 - Define your “critical path”: Not all features are created equal. Identify the workflows that impact revenue, security, or retention the most; these deserve the highest testing rigor. 3 - Automate what matters: Automated tests provide confidence without slowing you down. Prioritize unit and integration tests for core functionality and use end-to-end tests strategically. 4 - Leverage environment tiers: Move fast in lower environments but enforce stability in staging and production. 5 - Shift Left: Catching defects earlier saves time and cost. Embed testing at the pull request, commit, and review stages to reduce late-stage surprises. 6 - Timebox your testing: Not every feature needs exhaustive QA. Set clear limits based on risk, business impact, and development speed to avoid getting stuck in endless validation cycles. The goal is to move FAST WITHOUT shipping avoidable FIRES. Prioritization, intelligent automation, and risk-based decision-making will help you release with confidence (until we reach a future where testing is instant and invisible). Any other tips?

I shipped 274+ functional tests at Amazon. 10 tips for bulletproof functional testing: 0. Test independence: Each test should be fully isolated. No shared state, no dependencies on other tests outcomes. 1. Data management: Create and clean test data within each test. Never rely on pre-existing data in test environments. 2. Error message: When a test fails, the error message should tell you exactly what went wrong without looking at the code. 3. Stability first: Flaky tests are worse than no tests. Invest time in making tests reliable before adding new ones. 4. Business logic: Test the critical user journeys first. Not every edge case needs a functional test - unit tests exist for that. 5. Test environment: Always have a way to run tests locally. Waiting for CI/CD to catch basic issues is a waste of time. 6. Smart waits: Never use fixed sleep times. Implement smart waits and retries with reasonable timeouts. 7. Maintainability: Keep test code quality as high as production code. Bad test code is a liability, not an asset. 8. Parallel execution: Design tests to run in parallel from day one. Sequential tests won't scale with your codebase. 9. Documentation: Each test should read like documentation. A new team member should understand the feature by reading the test. Remember: 100% test coverage is a vanity metric. 100% confidence in your critical paths is what matters. What's number 10? #softwareengineering #coding #programming

Flaky tests are the worst. They fail randomly, waste time, and make automation unreliable. I tried almost everything to fix them. Here’s what actually works: • Stabilize waits and selectors – Hardcoded sleeps are a disaster. Instead, use explicit waits and stable locators to handle dynamic elements. • Run tests in isolation – Shared test data and dependencies create flakiness. Reset the environment and avoid test interdependencies. • Log and retry strategically – Instead of blindly re-running failures, log failures, analyze patterns, and retry only known flaky steps. • Optimize test execution – Parallel execution can cause conflicts. Run tests in a clean environment to prevent resource contention. • Fix root causes, not symptoms – Don’t just ignore flaky tests. Investigate failures, improve test design, and fix unstable areas in the app. Flaky tests don’t just “happen.” They have causes. They can be fixed.