On-the-fly Improving Performance of Deep Code Models via Input Denoising

Deep learning has been widely adopted to tackle various code-based tasks by building deep code models based on a large amount of code snippets. While these deep code models have achieved great success, even state-of-the-art models suffer from noise present in inputs leading to erroneous predictions....

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Veröffentlicht in:	IEEE/ACM International Conference on Automated Software Engineering : [proceedings] S. 560 - 572
Hauptverfasser:	Tian, Zhao, Chen, Junjie, Zhang, Xiangyu
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 11.09.2023
Schlagworte:	Code Model Codes Deep Learning Input Denoising Location awareness Noise measurement Noise reduction Predictive models Semantics Syntactics
ISSN:	2643-1572
Online-Zugang:	Volltext
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