Learning based and Context Aware Non-Informative Comment Detection

被引：2

作者：

Liu, Mingwei ^{[1
,2
]}

Yang, Yanjun ^{[1
,2
]}

Peng, Xin ^{[1
,2
]}

Wang, Chong ^{[1
,2
]}

Zhao, Chengyuan ^{[1
,2
]}

Wang, Xin ^{[1
,2
]}

Xing, Shuangshuang ^{[1
,2
]}

机构：

[1] Fudan Univ, Sch Comp Sci, Shanghai, Peoples R China

[2] Fudan Univ, Shanghai Key Lab Data Sci, Shanghai, Peoples R China

来源：

2020 IEEE INTERNATIONAL CONFERENCE ON SOFTWARE MAINTENANCE AND EVOLUTION (ICSME 2020) | 2020年

基金：

中国国家自然科学基金;

关键词：

API Documentation; Text Classification; Deep Learning;

D O I：

10.1109/ICSME46990.2020.00115

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

This report introduces the approach that we have designed and implemented for the DeClutter challenge of DocGen2, which detects non-informative code comments. The approach combines both comment based text classification and code context based prediction. Based on the approach, our "fduse" team achieved the best F1 score (0.847) in the competition.

引用

页码：866 / 867

页数：2

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