Elements: Can Empirical SE be Adapted to Computational Science?

要素：经验SE可以适应计算科学吗？

• 批准号: 1931425
• 负责人: Timothy Menzies
• 金额: $ 59.21万
• 依托单位: North Carolina State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1931425&HistoricalAwards=false
• 关键词: Elements; Empirical; SE; Adapted; Computational

Today the computer is just as important a tool for chemists as the test tube. For example, the 2013 Nobel Prize was awarded to chemists using computer models to explore very fast chemical reactions during photosynthesis. Other scientific areas where software is used intensively are astronomy, astrophysics, chemistry, weather prediction, economics, genomics, molecular biology, oceanography, physics, political science, and many other engineering fields. It is important to ensure the quality of these software-driven fields since its results accelerate global innovations by improving quality and quantity of computational scientific studies. But many software developers in this area have not formally studied computer science or software engineering. This proposal will create SEnTRY, a workbench containing methods adapted from empirical software engineering, that would help bridge the skill gap via automatic agents by suggesting to developers when they should investigate or redo part of their code. Software is used intensively in scientific areas such as astronomy, astrophysics, chemistry, weather prediction, economics, genomics, molecular biology, oceanography, physics, political science, and many other engineering fields. It is important to ensure the quality of these software-driven fields since its results accelerate global innovations by improving quality and quantity of computational scientific studies. But many software developers in this area have not formally studied computer science or software engineering. This proposal will create SEnTRY, a workbench containing methods adapted from empirical software engineering, that would help bridge the skill gap via automatic agents by suggesting to developers when they should investigate or redo part of their code. To achieve these goals, methods developed for traditional kinds of software must be extensively adapted for computational science. For example, language models describing software defects must be created, especially for the computational science community; test case prioritization algorithms must be re-tuned to appropriately prioritize "tests" that are really "tests of scientific concepts"; and static code analysis warnings have to be re-engineered to manage the kinds of software tools used within the computational science community. To that end, this project will apply data miners, hyperparameter optimizers and active learning to project data from the computational science community. When successful, SEnTRY will reduce the associated cost (time, money, etc.) required to handle many of the large and more tedious aspects of software development. This will free up more time of the computational scientists, and allow them to focus on core scientific issues. As an additional benefit, SEnTRY will also ensure the reproducibility and credibility of the computational science researches which, in turn, will naturally encourage more adoption of current work as well as adaptation and innovation in future work.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.

今天，对于化学家来说，计算机是和试管一样重要的工具。 例如，2013年诺贝尔奖授予了使用计算机模型探索光合作用中非常快速的化学反应的化学家。软件被广泛使用的其他科学领域包括天文学、天体物理学、化学、天气预报、经济学、基因组学、分子生物学、海洋学、物理学、政治学和许多其他工程领域。重要的是要确保这些软件驱动的领域的质量，因为其结果 通过提高计算科学研究的质量和数量来加速全球创新。但是这个领域的许多软件开发人员并没有正式学习过计算机科学或软件工程。该提案将创建SENTRY，一个包含经验软件工程方法的工作台，通过自动代理向开发人员建议何时应该调查或重做部分代码，从而帮助弥合技能差距。软件广泛应用于科学领域，如天文学、天体物理学、化学、天气预报、经济学、基因组学、分子生物学、海洋学、物理学、政治学和许多其他工程领域。确保这些软件驱动领域的质量非常重要，因为其结果通过提高计算科学研究的质量和数量来加速全球创新。但是这个领域的许多软件开发人员并没有正式学习过计算机科学或软件工程。该提案将创建SENTRY，一个包含经验软件工程方法的工作台，通过自动代理向开发人员建议何时应该调查或重做部分代码，从而帮助弥合技能差距。为了实现这些目标，为传统软件开发的方法必须广泛适用于计算科学。例如，必须创建描述软件缺陷的语言模型，特别是对于计算科学社区;必须重新调整测试用例优先级算法，以适当地确定优先级 “测试”是真正的“科学概念的测试”;静态代码分析警告必须重新设计，以管理计算科学社区中使用的各种软件工具。为此，该项目将应用数据挖掘器，超参数优化器和主动学习来预测来自计算科学社区的数据。成功后，SENTRY将减少相关成本（时间、金钱等）。需要处理软件开发中的许多大型和更繁琐的方面。这将为计算科学家腾出更多的时间，使他们能够专注于核心科学问题。作为一个额外的好处，SENTRY还将确保计算科学研究的可重复性和可信度，这反过来自然会鼓励更多地采用当前的工作，以及在未来的工作中进行适应和创新。该奖项反映了NSF的法定使命，并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，被认为值得支持。

项目成果

DebtFree: minimizing labeling cost in self-admitted technical debt identification using semi-supervised learning

• DOI: 10.1007/s10664-022-10121-w
• 发表时间: 2022-01
• 期刊: Empirical Software Engineering
• 影响因子: 4.1
• 作者: Huy Tu;T. Menzies

Identifying Self-Admitted Technical Debts With Jitterbug: A Two-Step Approach

• DOI: 10.1109/tse.2020.3031401
• 发表时间: 2020-02
• 期刊: IEEE Transactions on Software Engineering
• 影响因子: 7.4
• 作者: Zhe Yu;F. M. Fahid;Huy Tu;T. Menzies

FRUGAL: Unlocking Semi-Supervised Learning for Software Analytics

• DOI: 10.1109/ase51524.2021.9678617
• 发表时间: 2021-08
• 期刊: 2021 36th IEEE/ACM International Conference on Automated Software Engineering (ASE)
• 作者: Huy Tu;T. Menzies

Mining Workflows for Anomalous Data Transfers

异常数据传输的挖掘工作流程

• DOI: 10.1109/msr52588.2021.00013
• 发表时间: 2021
• 期刊: MSR '21
• 作者: Tu, Huy;Papadimitriou, George;Kiran, Mariam;Wang, Cong;Mandal, Anirban;Deelman, Ewa;Menzies, Tim
• 通讯作者: Menzies, Tim