Ganesh Gopal Masti Jayaram, Infosys
Software testing is an imperative process of validating and verifying that a computer program/application/product meets the requirements that guided its design and development, works as expected and satisfies the needs of stakeholders. This process would be considered effective only when the resulting product is free of defects, is reliable in addition to being associated with low cost, easy to be incorporated and requires low maintenance. A study conducted by NIST in 2002 reports that software bugs cost the U.S. economy $59.5 billion annually. Software testing itself comes with a cost associated with a variety of challenges including but not limited to availability of resources (human/infrastructure) , industry wide tools/licenses and the most important of all being “Time”. Hence it becomes necessary to develop new business models and find innovative ways to do software testing that in turn can help achieve a WIN-WIN scenario from both the Client & Industry point of view. Challenges manifest themselves as inherent characteristics of the software testing process that can be resolved through the use of Artificial Intelligence techniques. Thus a software testing model that is based on the incorporation of Artificial Intelligence methodologies for the products being developed would truly stand the test of time and help pave the way for the industry that has been long spending billions of dollars in order to carry out software testing at a lower cost and help customers achieve more flexibility through the self testing of software using AI methodologies thereby ensuring quality deliverables. This paper proposes to conceptualize a business model that would help both vendors & client manage their testing needs by making use of Artificial Intelligence in the software testing space. We’ll take a look how the new model would work in comparison to the current model that the industry uses.
