Maryam Hasan, Eleni Stroulia, Denilson Barbosa, Manar H. Alalfi
{"title":"Analyzing natural-language artifacts of the software process","authors":"Maryam Hasan, Eleni Stroulia, Denilson Barbosa, Manar H. Alalfi","doi":"10.1109/ICSM.2010.5609680","DOIUrl":null,"url":null,"abstract":"Software teams, as they communicate throughout the life-cycle of their projects, generate a substantial stream of textual data. Through emails and chats, developers discuss the requirements of their software system, they negotiate the distribution of tasks among them, and they make decisions about the system design, and the internal structure and functionalities of its code modules. The software research community has long recognized the importance and potential usefulness of such textual information. In this paper, we discuss our recent work on systematically analyzing several textual streams collected through our WikiDev2.0 tool. We use two different text-analysis methods to examine five different sources of textual data. We report on our experience using our method on analyzing the communications of a nine-member team over four months.","PeriodicalId":101801,"journal":{"name":"2010 IEEE International Conference on Software Maintenance","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Conference on Software Maintenance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSM.2010.5609680","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
Software teams, as they communicate throughout the life-cycle of their projects, generate a substantial stream of textual data. Through emails and chats, developers discuss the requirements of their software system, they negotiate the distribution of tasks among them, and they make decisions about the system design, and the internal structure and functionalities of its code modules. The software research community has long recognized the importance and potential usefulness of such textual information. In this paper, we discuss our recent work on systematically analyzing several textual streams collected through our WikiDev2.0 tool. We use two different text-analysis methods to examine five different sources of textual data. We report on our experience using our method on analyzing the communications of a nine-member team over four months.