{"title":"自动生成提交注释的挖掘版本控制系统","authors":"Yuan Huang, Qiaoyang Zheng, Xiangping Chen, Yingfei Xiong, Zhiyong Liu, Xiaonan Luo","doi":"10.1109/ESEM.2017.56","DOIUrl":null,"url":null,"abstract":"Commit comments increasingly receive attention as an important complementary component in code change comprehension. To address the comment scarcity issue, a variety of automatic approaches for commit comment generation have been intensively proposed. However, most of these approaches mechanically outline a superficial level summary of the changed software entities, the change intent behind the code changes is lost (e.g., the existing approaches cannot generate such comment: \"fixing null pointer exception\"). Considering the comments written by developers often describe the intent behind the code change, we propose a method to automatically generate commit comment by reusing the existing comments in version control system. Specifically, for an input commit, we apply syntax, semantic, pre-syntax, and pre-semantic similarities to discover the similar commits from half a million commits, and recommend the reusable comments to the input commit from the ones of the similar commits. We evaluate our approach on 7 projects. The results show that 9.1% of the generated comments are good, 27.7% of the generated comments need minor fix, and 63.2% are bad, and we also analyze the reasons that make a comment available or unavailable.","PeriodicalId":213866,"journal":{"name":"2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"37","resultStr":"{\"title\":\"Mining Version Control System for Automatically Generating Commit Comment\",\"authors\":\"Yuan Huang, Qiaoyang Zheng, Xiangping Chen, Yingfei Xiong, Zhiyong Liu, Xiaonan Luo\",\"doi\":\"10.1109/ESEM.2017.56\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Commit comments increasingly receive attention as an important complementary component in code change comprehension. To address the comment scarcity issue, a variety of automatic approaches for commit comment generation have been intensively proposed. However, most of these approaches mechanically outline a superficial level summary of the changed software entities, the change intent behind the code changes is lost (e.g., the existing approaches cannot generate such comment: \\\"fixing null pointer exception\\\"). Considering the comments written by developers often describe the intent behind the code change, we propose a method to automatically generate commit comment by reusing the existing comments in version control system. Specifically, for an input commit, we apply syntax, semantic, pre-syntax, and pre-semantic similarities to discover the similar commits from half a million commits, and recommend the reusable comments to the input commit from the ones of the similar commits. We evaluate our approach on 7 projects. The results show that 9.1% of the generated comments are good, 27.7% of the generated comments need minor fix, and 63.2% are bad, and we also analyze the reasons that make a comment available or unavailable.\",\"PeriodicalId\":213866,\"journal\":{\"name\":\"2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"37\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ESEM.2017.56\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ESEM.2017.56","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Mining Version Control System for Automatically Generating Commit Comment
Commit comments increasingly receive attention as an important complementary component in code change comprehension. To address the comment scarcity issue, a variety of automatic approaches for commit comment generation have been intensively proposed. However, most of these approaches mechanically outline a superficial level summary of the changed software entities, the change intent behind the code changes is lost (e.g., the existing approaches cannot generate such comment: "fixing null pointer exception"). Considering the comments written by developers often describe the intent behind the code change, we propose a method to automatically generate commit comment by reusing the existing comments in version control system. Specifically, for an input commit, we apply syntax, semantic, pre-syntax, and pre-semantic similarities to discover the similar commits from half a million commits, and recommend the reusable comments to the input commit from the ones of the similar commits. We evaluate our approach on 7 projects. The results show that 9.1% of the generated comments are good, 27.7% of the generated comments need minor fix, and 63.2% are bad, and we also analyze the reasons that make a comment available or unavailable.