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The changing dynamics in software testing with AI
09 Feb, 2018

The changing dynamics in software testing with AI

The industry has come a long way over the years in transforming technology from its very roots. Sophia, the humanoid robot has become the ‘living’ example of the progressive nature of technology who not only uses Artificial Intelligence (AI) and facial recognition but is the first to be accorded citizenship by Saudi Arabia. This goes onto show the changing dynamics in technology itself today, thus, amplifying the need for testing.

Software Testing with AI

With automation in the picture today, the scope of software testing has broadened ever so with a shift towards making AI an integral part of the process. By incorporating machine learning, analyzing the results becomes more effective and predictable (Predictive Analysis), thus, the chances to err reduce. With Natural Processing Language built into the test framework, communicating the test effort in the business language helps in enhancing the results. A combinatorial effort of automation and NPL helps in reducing the dependency on manual coding, thus economizing time as well. To cover the major problem areas, whether it be of optimizing the test suite, maintaining the whole framework or effectively basing decisions according to events rather than assumptions, AI helps software testing in transcending its limits and moving onto a more concise and coherent approach. Thus, by amplifying the whole stratagem, software testing has undergone a dimensional change in itself.

This however, does not go on to show that the role of manual testing is insignificant in any way. The coming future may essentially give a paramount importance to AI and its relevance in software testing but this would not eliminate manual testing altogether since intuition is a trait less likely to be a part of AI so swiftly. The case with Sophia for example, echoes the same wherein the robotic chatbot is unable to answer certain questions that is beyond its comprehension. Therefore, the need to maintain a balance between the two, automation as well as manual testing, comes into being wherein resources are optimally utilized and results are augmented.

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