Detecting and Recommending Mitigations for Impactful Risky Software Changes

检测有影响的风险软件变更并提出缓解措施

• 批准号: RGPIN-2015-06545
• 负责人: Shihab, Emad
• 金额: $ 2.48万
• 依托单位: Concordia University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=685216
• 关键词: Detecting; Recommending; Mitigations; Impactful; Risky

Software systems play an important role in our daily lives, making the quality of software systems of paramount importance. To ensure the quality of software systems, a large amount of research focused on the detection of source code packages, files and changes that contain defects. However, the adoption and usefulness of such approaches in practice remains limited. Some of the most commonly cited reasons for the lack of adoption are 1) metrics used in the detection are not actionable, 2) the impact of defects is not taken into consideration and 3) no guidance is given on how to mitigate the detected defects.******The aim of the proposed research is to address the aforementioned limitations, making defect detection techniques more pragmatic. To do so, we plan to propose models that use actionable metrics to detect impactful risky changes. Furthermore, we will use historical data and employ qualitative and quantitative approaches on the fixes of the impactful risky changes in order to propose mitigations for the detected impactful risky changes. ******The successful completion of this proposed project will enable software researchers and practitioners to better understand the key development factors that enable pragmatic defect detection. The novel contributions of the proposed research are: 1) the proposal of models that use actionable metrics to effectively detect impactful risky changes and 2) a catalog of mitigations that can be applied to address these impactful risky changes. Large-scale empirical studies will be performed using large open source and industrial projects, to determine the effectiveness of the proposed models, actionable metrics and proposed mitigations.*******The proposed research will have a direct impact on the software engineering research and practice since it will advance the field by providing pragmatic detection techniques, proposing novel mitigation strategies and providing an extensible tooling framework. Furthermore, the proposed research will expose, train and enable highly qualified personnel (HQP) to contribute to the state-of-the-art in software quality research.**

软件系统在我们的日常生活中扮演着重要的角色，因此软件系统的质量至关重要。为了确保软件系统的质量，大量的研究集中在检测包含缺陷的源代码包、文件和更改上。然而，这种做法在实践中的采纳量和有用性仍然有限。没有采用的一些最常引用的原因是：1)检测中使用的度量不可操作，2)没有考虑缺陷的影响，3)没有就如何减轻检测到的缺陷提供指导。*建议研究的目的是解决上述限制，使缺陷检测技术更加实用。为了做到这一点，我们计划提出使用可操作的指标来检测有影响的风险变化的模型。此外，我们将使用历史数据，并采用定性和定量的方法来确定有影响的风险变化，以便为检测到的有影响的风险变化提出缓解措施。*这个拟议项目的成功完成将使软件研究人员和从业者能够更好地了解实现实用缺陷检测的关键开发因素。拟议研究的新贡献是：1)提出了使用可操作的度量来有效地检测影响的风险变化的模型，以及2)可以应用于应对这些影响的风险变化的缓解措施的目录。将使用大型开源和工业项目进行大规模的实证研究，以确定建议的模型、可操作的度量和建议的缓解措施的有效性。*建议的研究将对软件工程研究和实践产生直接影响，因为它将通过提供实用的检测技术、提出新的缓解策略和提供可扩展的工具框架来推动该领域的发展。此外，拟议的研究将暴露、培训和使高素质人员(HQP)能够为软件质量研究的最新水平做出贡献。**