ARTIFICIAL INTELLIGENCE IN SOFTWARE ENGINEERING: AUTOMATED CODE GENERATION, TESTING, AND SELF-HEALING SYSTEM DESIGN

Abstract

Artificial Intelligence (AI) significantly transformed software engineering by introducing intelligent automation into software development, testing, and system maintenance processes. This study examined the role of AI in automated code generation, AI-driven software testing, and self-healing system design within modern software engineering environments. The research adopted a quantitative research design and collected data from a sample of 320 software engineers, developers, quality assurance specialists, and IT professionals working in technology organizations. A structured questionnaire measured respondent perceptions regarding AI integration in software engineering practices. The findings revealed that AI technologies improved software development efficiency, coding accuracy, software reliability, and operational continuity. Automated code generation recorded a mean value of 4.18, indicating strong agreement regarding the effectiveness of AI-assisted programming systems in reducing repetitive coding activities and improving software maintainability. AI-driven software testing achieved a mean value of 4.11, demonstrating significant improvement in defect detection accuracy and software quality assurance processes. Self-healing system design produced a mean value of 4.06, reflecting positive perceptions regarding autonomous fault detection and intelligent recovery mechanisms. Software development efficiency recorded the highest mean value of 4.22, while software reliability achieved a mean score of 4.14. The study concluded that AI-powered software engineering practices enhanced productivity, scalability, and software resilience. Cybersecurity concerns, ethical challenges, and transparency issues remained critical factors requiring responsible AI governance and continuous human oversight.