Artificial Intelligence in Quality Assurance for Software Systems
DOI:
https://doi.org/10.55544/sjmars.2.2.2Keywords:
Software Quality Assurance, Artificial Intelligence, Machine Learning, Defect Detection, Automated Testing, User Experience, QA ChallengesAbstract
The rapid advancement in software development has taken place with the invention of a new quality assurance (QA) process for producing robust, reliable, and efficient systems. Artificial Intelligence is a "force of change" that promises automating most QA activities with promising predictive insight into the generation of dynamic test cases and intelligent detection of defects. This paper covers the theme of integrating AI with SQA through techniques such as Machine Learning, Natural Language Processing, and Neural Networks. The paper covers automation of testing, AI-driven management of defects, and enhancement of user experience as well as challenges and limitation that is encountered while implementing AI within QA. A glimpse of emerging trends illustrates the dynamic landscape of AI-driven QA.
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