{"title":"从程序调查活动中自动推断关注代码","authors":"M. Robillard, G. Murphy","doi":"10.1109/ASE.2003.1240310","DOIUrl":null,"url":null,"abstract":"When performing a program evolution task, developers typically spend a significant amount of effort investigating and reinvestigating source code. To reduce this effort, we propose a technique to automatically infer the essence of program investigation activities as a set of concern descriptions. The concern descriptions produced by our technique list methods and fields of importance in the context of the investigation of an object-oriented system. A developer can rely on this information to perform the change task at hand, or at a later stage for a change that involves the same concerns. The technique involves applying an algorithm to a transcript of a program investigation session. The transcript lists which pieces of source code were accessed by a developer when investigating a program and how the different pieces of code were accessed. We applied the technique to data obtained from program investigation activities for five subjects involved in two different program evolution tasks. The results show that relevant concerns can be identified with a manageable level of noise.","PeriodicalId":114604,"journal":{"name":"18th IEEE International Conference on Automated Software Engineering, 2003. Proceedings.","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"70","resultStr":"{\"title\":\"Automatically inferring concern code from program investigation activities\",\"authors\":\"M. Robillard, G. Murphy\",\"doi\":\"10.1109/ASE.2003.1240310\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"When performing a program evolution task, developers typically spend a significant amount of effort investigating and reinvestigating source code. To reduce this effort, we propose a technique to automatically infer the essence of program investigation activities as a set of concern descriptions. The concern descriptions produced by our technique list methods and fields of importance in the context of the investigation of an object-oriented system. A developer can rely on this information to perform the change task at hand, or at a later stage for a change that involves the same concerns. The technique involves applying an algorithm to a transcript of a program investigation session. The transcript lists which pieces of source code were accessed by a developer when investigating a program and how the different pieces of code were accessed. We applied the technique to data obtained from program investigation activities for five subjects involved in two different program evolution tasks. The results show that relevant concerns can be identified with a manageable level of noise.\",\"PeriodicalId\":114604,\"journal\":{\"name\":\"18th IEEE International Conference on Automated Software Engineering, 2003. Proceedings.\",\"volume\":\"50 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-10-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"70\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"18th IEEE International Conference on Automated Software Engineering, 2003. Proceedings.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ASE.2003.1240310\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"18th IEEE International Conference on Automated Software Engineering, 2003. Proceedings.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASE.2003.1240310","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automatically inferring concern code from program investigation activities
When performing a program evolution task, developers typically spend a significant amount of effort investigating and reinvestigating source code. To reduce this effort, we propose a technique to automatically infer the essence of program investigation activities as a set of concern descriptions. The concern descriptions produced by our technique list methods and fields of importance in the context of the investigation of an object-oriented system. A developer can rely on this information to perform the change task at hand, or at a later stage for a change that involves the same concerns. The technique involves applying an algorithm to a transcript of a program investigation session. The transcript lists which pieces of source code were accessed by a developer when investigating a program and how the different pieces of code were accessed. We applied the technique to data obtained from program investigation activities for five subjects involved in two different program evolution tasks. The results show that relevant concerns can be identified with a manageable level of noise.