Testing is a crucial process in the whole software development lifecycle. The quality assurance process should be established in the early stages of a software product development. Quality assurance helps to decrease financial and reputation risks for a company, ensure that functionality meets requirements, and brings business value.
Manual testing is an inevitable part of the whole quality assurance process. However, some automated testing tools and technologies help to speed up the feature validation process and verify huge amounts of test cases without human interaction. For sure, manual testing cannot be entirely replaced by algorithms, but at the same time in the modern era of artificial intelligence, machine learning, and other cutting-edge technologies, a lot of manual work can be eliminated. This releases a lot of engineering resources for other more business-facing activities and helps organizations utilize the resources wisely.
There are several tips how use software testing tools to make testing process effective:
- Start using the tools as early as possible in the software development lifecycle.
- Review the existing project toolset for test automation: some of them can bring less revenue from testing than their yearly license cost.
- Look for new AI and ML-based market solutions for automated testing to develop smart tests.
- Verify how much manual intervention is still required to maintain your test scripts.
- Make sure that reporting of your tests and bug tracking is provided by your tools.
The earlier quality assurance process is established and properly planned, less defects leak to production environments. Many modern companies: from start-ups to enormous corporations try to establish the shift-left testing approach. In this approach quality assurance engineers are involved in the software development lifecycle in the very initial steps: starting from the discovery phases, where a business analyst learns business objectives and writes the high-level requirements that could be tested even on this point. If defects are identified earlier, they are less costly in terms of fixing, and therefore, the product time to market is reduced.
Consequently, if a team follows the Scrum approach, shift-left testing is worth implementing for each iteration. If functionality is still being developed during a sprint, test automation engineers could draft tests according to the API specifications and requirements. Then, when the business features are developed, the tests could be slightly modified and they are implemented in the same sprint as functionality itself. This approach helps to have in-sprint test automation which is more effective in terms of defects detection than having gaps between feature implementation and test scripts development.
Once the shift-left approach is implemented, it’s crucial that the testing is an effective process itself. Automated tests implementation is only one side of a medal. Test maintenance is more important and sometimes is a more time-consuming process. Test results analysis might take the whole working day of an automation engineer. In this case, especially when there are thousands of tests already implemented, this analysis might take days. Test automation becomes less effective than manual testing. Hopefully, test communities contribute a lot to the test automation tools development. There are a lot of AI-based tools that are capable to analyse the results of the test runs independently without human intervention and providing feedback if it was a test failure or a product defect.
Software Testing Tools That Help To Make Your Testing Easier
Some modern test tools provide an ability for tests to self-heal, depending on the DOM structure changes, machine learning algorithms, etc. Let’s learn some of these tools in more detail.
There are several recent solutions:
- Functionize is a brand new approach to testing that provides codeless test automation capabilities powered by AI. It makes the debugging and analysis of results easier, and fixes tests dynamically. Functionize uses machine learning to help the tests learn from failures. One of the most exciting features of this solution is live test debugging that allows pausing, changing locators, verifications, and the whole test workflow while tests are running.
- Helenium is a tool that helps Selenium tests to be less flaky. It uses mechanisms that fix locators on the fly. So heals the tests immediately during the runtime. As a result, Helenium provides detailed reporting for the fixed controls.
- Report Portal is an AI-based dashboard for test automation runs and results. Makes the defects reporting process easier and more clear as there is a possibility to submit defects right from the failed test.
To sum up, software testing tools and technologies continue getting more intelligent. More frequently they use artificial intelligence and machine learning. This is good news for test automation engineers as their daily professional life becomes easier: there is no more need today to spend days on routine tasks as automated scripts debugging and fixing. Businesses also benefit from new tools and technologies: they spend less money on automated tests scripts maintenance by teams and decrease their software product time to production. It doesn’t mean that manual or automated test engineers are not required anymore. On the contrary, they can spend their time on more business-facing tasks. Let technologies do this job.