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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Bibliographic Details

Published in:	2025 IEEE Conference on Software Testing, Verification and Validation (ICST) pp. 302 - 313
Main Authors:	Ji, Suhwan, Lee, Sanghwa, Lee, Changsup, Han, Yo-Sub, Im, Hyeonseung
Format:	Conference Proceeding
Language:	English
Published:	IEEE 31.03.2025
Subjects:	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 Access:	Get full text
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