Impact of Large Language Models of Code on Fault Localization

Identifying the point of error is imperative in software debugging. Traditional fault localization (FL) techniques rely on executing the program and using the code coverage matrix in tandem with test case results to calculate a suspiciousness score for each method or line. Recently, learning-based F...

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Veröffentlicht in:	2025 IEEE Conference on Software Testing, Verification and Validation (ICST) S. 302 - 313
Hauptverfasser:	Ji, Suhwan, Lee, Sanghwa, Lee, Changsup, Han, Yo-Sub, Im, Hyeonseung
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 31.03.2025
Schlagworte:	Benchmark testing Codes Computer architecture Deep Learning Fault Localization Feature extraction Fine-Tuning Large Language Model of Code Large language models Location awareness Software debugging Software engineering Software testing Source coding Vulnerability Detection
Online-Zugang:	Volltext
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