{"title":"An information visualization feature model for supporting the selection of software visualizations","authors":"Renan Vasconcelos, Marcelo Schots, C. Werner","doi":"10.1145/2597008.2597796","DOIUrl":null,"url":null,"abstract":"Software development comprises the execution of a variety of tasks, such as bug discovery, finding reusable assets, dependency analysis etc. A better understanding of the task at hand and its surroundings can improve the development performance in general. Software visualizations can support such understanding by addressing different issues according to the necessity of stakeholders. However, knowing which visualizations better fit a given task in progress is not a trivial skill. In this sense, a feature model, intended for organizing the knowledge of a given domain and allowing the reuse of components, can support the identification, categorization and selection of information visualization elements. This work presents an ongoing domain analysis performed for building an information visualization feature model, whose goal is to support the process of choosing and building proper, suitable software visualizations.","PeriodicalId":6853,"journal":{"name":"2019 IEEE/ACM 27th International Conference on Program Comprehension (ICPC)","volume":"30 1","pages":"122-125"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE/ACM 27th International Conference on Program Comprehension (ICPC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2597008.2597796","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
Software development comprises the execution of a variety of tasks, such as bug discovery, finding reusable assets, dependency analysis etc. A better understanding of the task at hand and its surroundings can improve the development performance in general. Software visualizations can support such understanding by addressing different issues according to the necessity of stakeholders. However, knowing which visualizations better fit a given task in progress is not a trivial skill. In this sense, a feature model, intended for organizing the knowledge of a given domain and allowing the reuse of components, can support the identification, categorization and selection of information visualization elements. This work presents an ongoing domain analysis performed for building an information visualization feature model, whose goal is to support the process of choosing and building proper, suitable software visualizations.