Towards Understanding the Characteristics of Code Generation Errors Made by Large Language Models

Large Language Models (LLMs) have demonstrated unprecedented capabilities in code generation. However, there remains a limited understanding of code generation errors that LLMs can produce. To bridge the gap, we conducted an in-depth analysis of code generation errors across six representative LLMs...

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Veröffentlicht in:	Proceedings / International Conference on Software Engineering S. 2587 - 2599
Hauptverfasser:	Wang, Zhijie, Zhou, Zijie, Song, Da, Huang, Yuheng, Chen, Shengmai, Ma, Lei, Zhang, Tianyi
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 26.04.2025
Schlagworte:	Code Generation Codes Complexity theory Correlation Empirical Study Encoding Large language models Semantics Software engineering Software reliability Syntactics Taxonomy
ISSN:	1558-1225
Online-Zugang:	Volltext
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