Self-Healing Software: Leveraging AI for Automated Bug Detection and Real-Time Code Correction
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Abstract
The emerging software engineering paradigm of self-healing software makes use of artificial intelligence (AI) to allow systems identify and automatically diagnose and fix software failures independently. Current debugging and maintenance processes openly depend on people yet the manual interventions limit their effectiveness on extensive and dynamic systems. The integration of machine learning algorithms alongside deep learning models along with natural language processing techniques through AI-driven self-healing software helps to boost software reliability and security. This paper examines the main elements of self-healing software through static and dynamic bug detection systems and live code repair processes as well as artificial intelligence that helps create software solutions. The article examines the performance issues which occur with AI-powered self-healing systems including false positives and computational burden and security vulnerabilities. This paper identifies upcoming developments which cover DevOps workflow integration with AI systems and explains how advanced AI techniques improve debugging performance through improved explanations and how self-healing AI can apply to big distributed systems. This article investigates software maintenance transformations under AI along with automated debugging and real-time error correction changes.
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