Collaborative Research: Elements: Software: Software Health Monitoring and Improvement Framework

协作研究：要素：软件：软件健康监控和改进框架

• 批准号: 1835292
• 负责人: Yuanfang Cai
• 金额: $ 29.97万
• 依托单位: Drexel University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-11-01 至 2023-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1835292&HistoricalAwards=false
• 关键词: Collaborative; Research; Elements; Software; Health

Software underpins every aspects of modern life, with significant impact in society. Poor quality software can cause huge financial losses, even threatening people's lives. Software quality is even more critical within the scientific community. The reproducibility of research results and sustainability of the research itself, heavily depend on the quality of the software developed by scientists, who usually acquire basics of software programming but are not aware of the best design practices. As a consequence, several existing open access scientific software packages are known to be hard to use and evolve due to their poor quality, as highlighted in recent studies. This project will integrate and enhance recent advances in software issue detection and refactoring techniques, created by the PIs and sponsored by NSF, in order to serve diverse scientific and engineering domains, detecting and fixing software quality issues effectively. This proposal seeks to bridge the gap between software engineering community and other science and engineering community in general. It will provide quantitative comparisons of software projects against an industrial benchmark, enable users to pinpoint software issues responsible for high maintenance costs, visualize the severity of the detected issues, and refactor them using the proposed interactive refactoring framework. The proposed framework will bring together software users and software developers by enabling non software experts to post software challenges for the software community to solve, which will, in turn, boost the research and advances in software research.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

软件支撑着现代生活的各个方面，对社会产生重大影响。质量差的软件会造成巨大的经济损失，甚至威胁到人们的生命安全。软件质量在科学界甚至更为重要。研究结果的可重复性和研究本身的可持续性在很大程度上取决于科学家开发的软件的质量，他们通常获得软件编程的基础知识，但不知道最佳设计实践。因此，正如最近的研究所强调的那样，一些现有的开放获取科学软件包由于质量差而难以使用和发展。该项目将整合和增强由PI创建并由NSF赞助的软件问题检测和重构技术的最新进展，以服务于不同的科学和工程领域，有效地检测和修复软件质量问题。这个建议旨在弥合软件工程社区和其他科学和工程社区之间的差距。它将提供软件项目与工业基准的定量比较，使用户能够查明造成高维护成本的软件问题，可视化检测到的问题的严重性，并使用拟议的交互式重构框架对其进行重构。该框架将把软件用户和软件开发人员聚集在一起，使非软件专家能够发布软件社区解决的软件挑战，这反过来又会促进软件研究的研究和进步。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。

项目成果

Evaluating the Impact of Possible Dependencies on Architecture-Level Maintainability

• DOI: 10.1109/tse.2022.3171288
• 发表时间: 2023-03
• 期刊: IEEE Transactions on Software Engineering
• 影响因子: 7.4
• 作者: Wuxia Jin;Dinghong Zhong;Yuanfang Cai;R. Kazman;Ting Liu

Exploring the Architectural Impact of Possible Dependencies in Python Software

• DOI: 10.1145/3324884.3416619
• 发表时间: 2020-09
• 期刊: 2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE)
• 作者: Wuxia Jin;Yuanfang Cai;R. Kazman;Gang Zhang;Q. Zheng;Ting Liu

On the Lack of Consensus Among Technical Debt Detection Tools

论技术债务检测工具缺乏共识

• DOI: 10.1109/icse-seip52600.2021.00021
• 发表时间: 2021
• 期刊: 10.1109/ICSE-SEIP52600.2021.00021
• 作者: Lefever, Jason;Cai, Yuanfang;Cervantes, Humberto;Kazman, Rick;Fang, Hongzhou
• 通讯作者: Fang, Hongzhou

Software design analysis and technical debt management based on design rule theory

基于设计规则理论的软件设计分析与技术债务管理

• DOI: 10.1016/j.infsof.2023.107322
• 发表时间: 2023
• 期刊: Information and Software Technology
• 影响因子: 3.9
• 作者: Cai, Yuanfang;Kazman, Rick
• 通讯作者: Kazman, Rick

SAIN: A Community-Wide Software Architecture INfrastructure

• DOI: 10.1109/icse-companion58688.2023.00095
• 发表时间: 2023-05
• 期刊: 2023 IEEE/ACM 45th International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)
• 作者: Joshua Garcia;Mehdi Mirakhorli;Lu Xiao;S. Malek;R. Kazman;Yuanfang Cai;N. Medvidović