Machine learning (ML) falls under Artificial Intelligence (AI), enabling computers or programs to perform tasks without explicit programming. This involves teaching systems to recognize patterns, analyze diverse data sets, and forecast future outcomes. ML aims to emulate human-like thinking: learning from experience, adapting to new situations, and preemptively solving complex problems.
In software testing, integrating machine learning offers numerous benefits. It can significantly reduce testing time, enhance result accuracy and reliability, minimize human errors, automate repetitive tasks, and promptly detect bugs and errors, thereby preventing potential escalation.
This article explores software testing fundamentals, the application of machine learning in software testing, and strategies for integrating machine learning into your software testing processes.
