Accelerating Sprints with AI in Testing and Quality: Test Generation, Defect Analysis, and Failure Prediction - MICHAŁ OPALSKI / AI-AGILE.ORG
Abstract The modern software development lifecycle emphasizes speed and quality, with agile methodologies particularly focused on iterative and incremental progress. A critical challenge in fast-paced Agile environments such as Scrum is how to maintain or improve product quality without slowing down delivery. Traditional testing approaches increasingly struggle to keep pace with rapid sprint cadences. Recently, advancements in Artificial Intelligence (AI) and Machine Learning (ML) have transformed quality engineering, enabling smarter test creation, more effective defect detection and classification, and the ability to predict failures before they occur. This article explores how AI accelerates sprints by augmenting the testing and quality assurance processes. It discusses automated test generation, AI-driven defect analysis, and failure prediction models. Real-world examples illustrate practical applications and measurable benefits. The combination of academic insights with industry...
