How will your Test Automation strategy change this year?

The global digital landscape has undergone a change in its dynamics. On one side, there is the advent of cutting edge technologies enhancing the quality, capacity and functionality of software. On the other side, there is an increased demand for software to be delivered off the shelves quickly. Furthermore, there is an additional scare of cyber security enveloping the entire digital landscape. Overall, businesses are caught up between delivering quick software products or services to the market and ensuring the ones delivered are qualitatively superior and secure. Can the two requirements be compatible and achievable? Yes, if a rigorous software testing methodology is followed in the mould of Agile-DevOps.

How can a test automation strategy be of help?

The growing complexity of software involving advanced technologies like AI and machine learning, IoT, virtual reality, big data, and cloud etc. has led to a paradigm shift in testing. It is no longer about manual testing alone but combining the same with automation testing. However, building a test automation strategy is not simple, for it requires taking into consideration a lot of factors. These can relate to the robustness of scripts, the compatibility of scripts across devices and platforms, or their ability to virtualize among others. Moreover, as the DevOps paradigm has become the new normal in software testing, engaging software test automation services has become important to ensure Continuous Integration and Delivery (CI/CD).

Let us find out how the year 2019 will turn out to be as far as delivering test automation solutions is concerned.

Trends in test automation solutions for the year 2019

• Increased use of AI in test automation and analysis: Enterprises often get bogged down in identifying the sources of bugs in software codes. They fail to determine if the bugs have ingressed due to system or coding issues. Test automation experts are hard pressed to find the sources of glitches leading to a delay in meeting the delivery schedules. This is where Artificial Intelligence (AI) and Machine Learning (ML) can play their part. For example, AI/ML can run through billions of lines of coding and analyze as to which pattern is out of the ordinary. They can even predict the areas where glitches are likely to sneak-in by mining and analysing the historical data. AI can provide robust data analytics vis-a-vis the opinions of test automation experts based on experience. The year will see the use of QA automation testing tools that incorporate elements of AI/ML to analyze tests such as regression, performance, functional, usability etc. The year shall see the exact number of tests to be executed for validating a module.
• Script maintenance will get easy? The biggest challenge for test automation experts is to create and maintain a test script beyond its usage date, browser, and operating system. Test scripts can fail if the application under test is changed without updating the scripts. This is where AI helps by updating the scripts whenever it detects any change in the application or its functionality. The year will see new test automation solutions undergoing self correction as and when there is a change in the user interface.

Moreover, everytime a testing exercise is conducted, the automation tool captures a humongous quantity of data comprising HTML data, images, and browser info among others. The data is then fed into the algorithm and incorporated by the tool as the normal application behaviour. Once there are deviations from the normal behaviour, the tool can correctly flag them thereby helping testers/builders to eliminate the glitch(es). Thus, AI/ML based tools can heal themselves and save testers from the drudgery of conducting complex regression tests.

#Is Selenium passe? Do other automation tools come into play?: In the last few years, Selenium has acquired the de facto status of being the most popular automation testing tool. However, test teams can adopt tools that are right for the testing job such as Cypress.io, TestCafe etc and the ones that meet the team’s styles and needs. Since the year will see more of AI based automation, there is a dire need to use AI based open source test tools other than Selenium.

Conclusion

With continuous testing becoming an integral part of software testing, the automated testing strategy needs to undergo a change to meet the testing objectives of the day. The year 2019 will see an increased use of AI and ML in analysing and executing complex test cases. The ultimate result will be a better software that delivers customer delight.

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Diya works for Cigniti Technologies, Global Leaders in Independent Software Testing Services Company to be appraised at Cmmi-Svc v1.3, Maturity Level 5, and is also Iso 9001:2015 & Iso 27001:2013 certified.