{"title":"Reverse Engineering Co-maintenance Relationships Using Conceptual Analysis of Source Code","authors":"Scott Grant, J. Cordy, D. Skillicorn","doi":"10.1109/WCRE.2011.20","DOIUrl":null,"url":null,"abstract":"In this work, we explore the relationship between topic models and co-maintenance history by introducing a visualization that compares conceptual cohesion within change lists. We explain how this view of the project history can give insight about the semantic architecture of the code, and we identify a number of patterns that characterize particular kinds of maintenance tasks. We examine the relationship between co-maintenance history and concept location, and visualize the distribution of changes across concepts to show how these techniques can be used to predict co-maintenance of source code methods.","PeriodicalId":350863,"journal":{"name":"2011 18th Working Conference on Reverse Engineering","volume":"132 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 18th Working Conference on Reverse Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCRE.2011.20","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15
Abstract
In this work, we explore the relationship between topic models and co-maintenance history by introducing a visualization that compares conceptual cohesion within change lists. We explain how this view of the project history can give insight about the semantic architecture of the code, and we identify a number of patterns that characterize particular kinds of maintenance tasks. We examine the relationship between co-maintenance history and concept location, and visualize the distribution of changes across concepts to show how these techniques can be used to predict co-maintenance of source code methods.