{"title":"SAA:通过基于可视化的软件分析来改进软件开发过程的框架","authors":"Lara Merdol, Eray Tüzün, Ugur Dogrusoz","doi":"10.1016/j.jss.2025.112589","DOIUrl":null,"url":null,"abstract":"<div><div>Software artifacts contain crucial information about a project. Analyzing these artifacts and their relationships yields valuable insights. During a software project’s lifecycle, software tracking tools are used to monitor artifacts. Mining metadata from modern software tracking tools provides extensive data for constructing comprehensive software artifact traceability graphs. These graphs aid decision-making in software development. While prior studies have used various software artifact graphs for analysis, comprehensive graphs are underexplored. Moreover, existing studies often lack interactive visualization for exploratory analysis. A unified traceability graph with interactive visualization can illuminate a broader range of issues and enhance understanding through visual cues. This article introduces the Software Artifact Analyzer (SAA) framework, leveraging artifact traceability graphs to support diverse analyses. A sample SAA tool demonstrates framework implementation, evaluated through quantitative and qualitative methods with focus groups and surveys. Participants praised its potential to improve software processes but noted challenges in graph complexity management. Based on the surveys, the tool’s usability score was 74.5 out of 100, which is above average on the System Usability Scale (SUS), indicating its practicality. The SAA framework offers broad applicability by enabling seamless implementation of new software analysis methods, providing project decision-makers with insightful visualizations of the analysis results.</div></div>","PeriodicalId":51099,"journal":{"name":"Journal of Systems and Software","volume":"231 ","pages":"Article 112589"},"PeriodicalIF":4.1000,"publicationDate":"2025-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"SAA: A framework for improving the software development process via visualization-based software analytics\",\"authors\":\"Lara Merdol, Eray Tüzün, Ugur Dogrusoz\",\"doi\":\"10.1016/j.jss.2025.112589\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Software artifacts contain crucial information about a project. Analyzing these artifacts and their relationships yields valuable insights. During a software project’s lifecycle, software tracking tools are used to monitor artifacts. Mining metadata from modern software tracking tools provides extensive data for constructing comprehensive software artifact traceability graphs. These graphs aid decision-making in software development. While prior studies have used various software artifact graphs for analysis, comprehensive graphs are underexplored. Moreover, existing studies often lack interactive visualization for exploratory analysis. A unified traceability graph with interactive visualization can illuminate a broader range of issues and enhance understanding through visual cues. This article introduces the Software Artifact Analyzer (SAA) framework, leveraging artifact traceability graphs to support diverse analyses. A sample SAA tool demonstrates framework implementation, evaluated through quantitative and qualitative methods with focus groups and surveys. Participants praised its potential to improve software processes but noted challenges in graph complexity management. Based on the surveys, the tool’s usability score was 74.5 out of 100, which is above average on the System Usability Scale (SUS), indicating its practicality. The SAA framework offers broad applicability by enabling seamless implementation of new software analysis methods, providing project decision-makers with insightful visualizations of the analysis results.</div></div>\",\"PeriodicalId\":51099,\"journal\":{\"name\":\"Journal of Systems and Software\",\"volume\":\"231 \",\"pages\":\"Article 112589\"},\"PeriodicalIF\":4.1000,\"publicationDate\":\"2025-08-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Systems and Software\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0164121225002584\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Systems and Software","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0164121225002584","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
SAA: A framework for improving the software development process via visualization-based software analytics
Software artifacts contain crucial information about a project. Analyzing these artifacts and their relationships yields valuable insights. During a software project’s lifecycle, software tracking tools are used to monitor artifacts. Mining metadata from modern software tracking tools provides extensive data for constructing comprehensive software artifact traceability graphs. These graphs aid decision-making in software development. While prior studies have used various software artifact graphs for analysis, comprehensive graphs are underexplored. Moreover, existing studies often lack interactive visualization for exploratory analysis. A unified traceability graph with interactive visualization can illuminate a broader range of issues and enhance understanding through visual cues. This article introduces the Software Artifact Analyzer (SAA) framework, leveraging artifact traceability graphs to support diverse analyses. A sample SAA tool demonstrates framework implementation, evaluated through quantitative and qualitative methods with focus groups and surveys. Participants praised its potential to improve software processes but noted challenges in graph complexity management. Based on the surveys, the tool’s usability score was 74.5 out of 100, which is above average on the System Usability Scale (SUS), indicating its practicality. The SAA framework offers broad applicability by enabling seamless implementation of new software analysis methods, providing project decision-makers with insightful visualizations of the analysis results.
期刊介绍:
The Journal of Systems and Software publishes papers covering all aspects of software engineering and related hardware-software-systems issues. All articles should include a validation of the idea presented, e.g. through case studies, experiments, or systematic comparisons with other approaches already in practice. Topics of interest include, but are not limited to:
•Methods and tools for, and empirical studies on, software requirements, design, architecture, verification and validation, maintenance and evolution
•Agile, model-driven, service-oriented, open source and global software development
•Approaches for mobile, multiprocessing, real-time, distributed, cloud-based, dependable and virtualized systems
•Human factors and management concerns of software development
•Data management and big data issues of software systems
•Metrics and evaluation, data mining of software development resources
•Business and economic aspects of software development processes
The journal welcomes state-of-the-art surveys and reports of practical experience for all of these topics.