{"title":"通过方法上下文的源代码摘要自动生成文档","authors":"P. McBurney, Collin McMillan","doi":"10.1145/2597008.2597149","DOIUrl":null,"url":null,"abstract":"A documentation generator is a programming tool that creates documentation for software by analyzing the statements and comments in the software's source code. While many of these tools are manual, in that they require specially-formatted metadata written by programmers, new research has made inroads towards automatic generation of documentation. These approaches work by stitching together keywords from the source code into readable natural language sentences. These approaches have been shown to be effective, but carry a key limitation: the generated documents do not explain the source code's context. They can describe the behavior of a Java method, but not why the method exists or what role it plays in the software. In this paper, we propose a technique that includes this context by analyzing how the Java methods are invoked. In a user study, we found that programmers benefit from our generated documentation because it includes context information.","PeriodicalId":6853,"journal":{"name":"2019 IEEE/ACM 27th International Conference on Program Comprehension (ICPC)","volume":"40 1","pages":"279-290"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"203","resultStr":"{\"title\":\"Automatic documentation generation via source code summarization of method context\",\"authors\":\"P. McBurney, Collin McMillan\",\"doi\":\"10.1145/2597008.2597149\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A documentation generator is a programming tool that creates documentation for software by analyzing the statements and comments in the software's source code. While many of these tools are manual, in that they require specially-formatted metadata written by programmers, new research has made inroads towards automatic generation of documentation. These approaches work by stitching together keywords from the source code into readable natural language sentences. These approaches have been shown to be effective, but carry a key limitation: the generated documents do not explain the source code's context. They can describe the behavior of a Java method, but not why the method exists or what role it plays in the software. In this paper, we propose a technique that includes this context by analyzing how the Java methods are invoked. In a user study, we found that programmers benefit from our generated documentation because it includes context information.\",\"PeriodicalId\":6853,\"journal\":{\"name\":\"2019 IEEE/ACM 27th International Conference on Program Comprehension (ICPC)\",\"volume\":\"40 1\",\"pages\":\"279-290\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-06-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"203\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE/ACM 27th International Conference on Program Comprehension (ICPC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2597008.2597149\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE/ACM 27th International Conference on Program Comprehension (ICPC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2597008.2597149","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automatic documentation generation via source code summarization of method context
A documentation generator is a programming tool that creates documentation for software by analyzing the statements and comments in the software's source code. While many of these tools are manual, in that they require specially-formatted metadata written by programmers, new research has made inroads towards automatic generation of documentation. These approaches work by stitching together keywords from the source code into readable natural language sentences. These approaches have been shown to be effective, but carry a key limitation: the generated documents do not explain the source code's context. They can describe the behavior of a Java method, but not why the method exists or what role it plays in the software. In this paper, we propose a technique that includes this context by analyzing how the Java methods are invoked. In a user study, we found that programmers benefit from our generated documentation because it includes context information.