CAREER: Toward Effective, Predictable, and Consistent Software Testing

职业：实现有效、可预测和一致的软件测试

• 批准号: 1942055
• 负责人: Rene Just
• 金额: $ 55万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1942055&HistoricalAwards=false
• 关键词: CAREER; Toward; Effective; Predictable; Consistent

Billions of people depend on software systems every day, but software remains buggy and vulnerable. Software testing is the predominant approach for software quality assurance (QA), and hundreds of thousands of developers are involved in QA activities on a daily basis. Developers heavily rely on intuition, experience, and familiarity with a code base when developing tests, and when reasoning about test effectiveness and consistency. However, experience varies widely, which has negative impacts on software quality and developer productivity. Addressing these challenges, this project develops practical end-to-end solutions for effective and consistent software testing that integrate well with existing QA practices. It aims to substantially increase the quality of the software that pervades modern technology, by providing developers with a framework and methodology for systematic software testing with quantifiable efficacy.The overall goal of this project is to advance software quality by making software testing more effective, predictable, and consistent. To achieve this goal, the proposed research co-develops a new mutation-based testing approach along with a methodology to quantify its efficacy. Specifically, this project (1) develops models for program context and test goal utility, (2) builds upon these models and develops a learning-based approach for context-sensitive predictions of test goal utility and ranking test goals, and (3) develops a probabilistic method that assesses how representative a set of test goals is for bugs encountered during software development. In addition to the research artifacts, this project will provide publicly available artifacts that enable training of a new generation of software engineers.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.

数十亿人每天都依赖软件系统，但软件仍然存在缺陷且容易受到攻击。软件测试是软件质量保证 (QA) 的主要方法，每天都有数十万开发人员参与 QA 活动。在开发测试以及推理测试有效性和一致性时，开发人员严重依赖直觉、经验和对代码库的熟悉程度。然而，经验差异很大，这对软件质量和开发人员生产力产生负面影响。为了应对这些挑战，该项目开发了实用的端到端解决方案，以实现有效且一致的软件测试，并与现有的 QA 实践很好地集成。它旨在通过为开发人员提供具有可量化功效的系统软件测试框架和方法，大幅提高现代技术中软件的质量。该项目的总体目标是通过使软件测试更加有效、可预测来提高软件质量，并且一致。为了实现这一目标，拟议的研究共同开发了一种新的基于突变的测试方法以及量化其功效的方法。具体来说，该项目 (1) 开发程序上下文和测试目标效用的模型，(2) 基于这些模型并开发基于学习的方法，用于测试目标效用的上下文敏感预测和对测试目标进行排名，以及 (3) 开发一种概率方法，用于评估一组测试目标对于软件开发过程中遇到的错误的代表性。除了研究成果之外，该项目还将提供公开可用的成果，以培训新一代软件工程师。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

How do Java mutation tools differ?

Java 变异工具有何不同？

• DOI: 10.1145/3526099
• 发表时间: 2022-12
• 期刊: Communications of the ACM
• 影响因子: 22.7
• 作者: Amalfitano, Domenico;Paiva, Ana C.;Inquel, Alexis;Pinto, Luís;Fasolino, Anna Rita;Just, René
• 通讯作者: Just, René

Prioritizing mutants to guide mutation testing

确定突变体的优先顺序以指导突变测试

• DOI: 10.1145/3510003.3510187
• 发表时间: 2022-05
• 期刊: Proceedings of the 44th International Conference on Software Engineering
• 作者: Kaufman, Samuel J.;Featherman, Ryan;Alvin, Justin;Kurtz, Bob;Ammann, Paul;Just, René
• 通讯作者: Just, René

Does mutation testing improve testing practices?

突变测试是否可以改善测试实践？

• 发表时间: 2021-04
• 期刊: Proceedings of the International Conference on Software Engineering
• 作者: Petrovic, Goran;Ivankovic, Marko;Fraser, Gordon;Just, René
• 通讯作者: Just, René

Revisiting the relationship between fault detection, test adequacy criteria, and test set size

重新审视故障检测、测试充分性标准和测试集大小之间的关系

• 发表时间: 2020-09
• 期刊: IEEEACM International Conference on Automated Software Engineering
• 作者: Chen, Yiqun;Gopinath, Rahul;Tadakamalla, Anita;Ernst, Michael;Holmes, Reid;Fraser, Gordon;Ammann, Paul;Just, René
• 通讯作者: Just, René