| 知识驱动的相似缺陷报告推荐方法 |
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| 引用本文： | 余笙,李斌,孙小兵,薄莉莉,周澄.知识驱动的相似缺陷报告推荐方法[J].计算机科学,2021,48(5):91-98. |
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| 作者姓名： | 余笙 李斌 孙小兵 薄莉莉 周澄 |
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| 作者单位： | 扬州大学信息工程学院 江苏 扬州225127;江苏省知识管理与智能服务工程研究中心 江苏 扬州225127 |
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| 基金项目： | 国家自然科学基金(61972335,61872312);扬州市校合作项目(YZU201803);江苏省六大人才高峰项目(RJFW-053);2020年度重庆市出版专项资金资助项目。 |
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| 摘 要： | 软件缺陷在软件开发过程中不可避免,提交的缺陷报告则是分析和修复缺陷的重要信息来源。开发人员常通过借鉴相似的历史缺陷报告和修复信息来辅助对当前新缺陷的分析和修复。文中提出了一种知识驱动的相似缺陷报告推荐方法。该方法首先利用信息检索和Word Embedding技术构建缺陷知识图谱;然后利用TF-IDF和Word Embedding技术计算缺陷报告之间的文本相似度,同时综合考虑缺陷的各项属性,从而得到缺陷报告之间的主次要属性相似度;最后将上述相似度融合成综合相似度,利用综合相似度推荐相似缺陷报告。实验结果表明,与基线方法相比,在Firefox数据集上所提方法的性能平均提高了12.7%。
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| 关 键 词： | 相似缺陷报告 信息检索 词嵌 知识图谱 推荐系统 |
Approach for Knowledge-driven Similar Bug Report Recommendation |
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| YU Sheng,LI Bin,SUN Xiao-bing,BO Li-li,ZHOU Cheng.Approach for Knowledge-driven Similar Bug Report Recommendation[J].Computer Science,2021,48(5):91-98. |
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| Authors: | YU Sheng LI Bin SUN Xiao-bing BO Li-li ZHOU Cheng |
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| Affiliation: | (School of Information Engineering,Yangzhou University,Yangzhou,Jiangsu 225127,China;Jiangsu Engineering Research Center of Knowledge Management and Intelligent Service,Yangzhou,Jiangsu 225127,China) |
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| Abstract: | Software bug is inevitable in the process of software development,and the submitted bug reports are important source of information for bug analysis and fixing.Developers usually refer to similar historical bug reports and fixing solutions to analyze and fix the new bug at hand.This paper proposes an approach for knowledge-driven similar bug report recommendation.Based on the combination of information retrieval and Word Embedding,it constructs a bug knowledge graph.Then,it uses TF-IDF and Word Embedding to calculate the text similarity between bug reports,and generates the similarity of primary and secondary attributes between the bug reports.Finally,the above similarities are merged into a comprehensive similarity,and similar bug reports are recommended based on the comprehensive similarity.Experimental results show that the proposed approach improves the performance by an average of 12.7%on the Firefox dataset compared to the baseline method. |
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| Keywords: | Similar bug report Information retrieval Word embedding Knowledge graph Recommendation systems |
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