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
This paper presents a comprehensive catalogue of 57 test-specific refactoring types, out of which only 33 were previously documented in the literature, using a mixed-method approach grounded on three sources of data.
SemaDiff, a novel approach for identifying semantic-preserving commits through behaviour-based analysis, is proposed, and results show that SemaDiff distinguishes accurately semantic-preserving from -- changing commits in about 76% of the cases, with a 100% precision in semantic-changing commit detection.
Maha Ayub, Michael Konstantinou, Ahmed Khanfir et al.· arXiv.org· 0 citations
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