The promise of Large Language Models (LLMs) in automated software engineering is often measured by functional correctness, overlooking the critical issue of long-term maintainability. This paper presents a systematic audit of technical debt in AI-generated software, revealing that AI does not eliminate flaws but rather...
Yue-Cai Zhu, Nikolaos Tsantalis, Peter C. Rigby· Proceedings of the 41st IEEE...· 0 citations
ARCTIC, an AI-powered Code Critique system that reframes code review around three capabilities: intent prediction, which infers why a change was made from conversation logs and metadata; drift detection, which measures divergence between the developer's intent and the agent's output via backtranslation; and code spotli...
C. Maddila, Mashrur Rashik, E. Khan et al.· arXiv.org· 0 citations
Developing a GenAI agent that autonomously formulates, prioritizes, and completes a limited set of code improvement tasks enterprise-wide is reported, and a Difference-in-Differences analysis found that automated improvements had an effect on the reduction of future maintenance effort that was as strong as or stronger...
