CAREER: Quality Matters: Dynamic, Static and Proactive Analyses for Automated Program Repair

职业：质量很重要：自动程序修复的动态、静态和主动分析

• 批准号: 1750116
• 负责人: Claire Le Goues
• 金额: $ 52.5万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-03-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1750116&HistoricalAwards=false
• 关键词: CAREER; Quality; Matters; Dynamic; Static

Society is increasingly reliant on software that affects human safety, privacy, and other important concerns. Software engineers have many tools at their disposal to identify errors and write correct code. However, programmer productivity and software quality are serious problems due to the number of open bugs, the negative impact of these bugs, and limited time available to developers to fix them. A recently emerging area of research develops techniques for automatic program repair. This project will advance the state of software testing and repair by addressing some of the challenges that must be overcome if automatic program repair is to become a common tester's tool. The outcomes of this research will reduce the cost of software defects, improve the quality of software, and improve productivity of programmers.To attack this problem, the project will develop repair techniques that synthesize new code based on Hoare logic and provide better patch guidance for developers through automatic reduction of false negatives. The research will extend separation logic-based bug-finding analyses to construct verified fixes. This involves dynamic strategies that search for and then compose diverse solutions to a given bug repair problem into measurably general patches, also static techniques that construct patches for previously undiscovered bugs that are difficult to find via testing.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.

社会越来越依赖于影响人类安全、隐私和其他重要问题的软件。软件工程师有许多工具可以用来识别错误并编写正确的代码。然而，程序员的生产力和软件质量是严重的问题，由于开放错误的数量，这些错误的负面影响，以及开发人员修复它们的时间有限。最近出现的一个研究领域开发了自动程序修复技术。 这个项目将通过解决一些挑战来推进软件测试和修复的状态，如果自动程序修复要成为一个通用的测试工具，这些挑战必须被克服。该研究成果将降低软件缺陷的成本，提高软件质量，提高程序员的生产力。为了解决这个问题，该项目将开发修复技术，基于Hoare逻辑合成新代码，并通过自动减少误报为开发人员提供更好的补丁指导。该研究将扩展基于分离逻辑的错误查找分析，以构建经过验证的修复程序。这包括动态策略，即搜索并将给定错误修复问题的各种解决方案组合成可测量的通用补丁，也包括静态技术，即为以前未发现的、难以通过测试发现的错误构建补丁。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

Common Statement Kind Changes to Inform Automatic Program Repair

• DOI: 10.1145/3196398.3196472
• 发表时间: 2018-05
• 期刊: 2018 IEEE/ACM 15th International Conference on Mining Software Repositories (MSR)
• 作者: Mauricio Soto;Claire Le Goues

ROSDiscover: Statically Detecting Run-Time Architecture Misconfigurations in Robotics Systems

ROSDiscover：静态检测机器人系统中的运行时架构错误配置

• DOI: 10.1109/icsa53651.2022.00019
• 发表时间: 2022
• 期刊: 2022 IEEE 19th International Conference on Software Architecture (ICSA
• 作者: Timperley, Christopher S.;Durschmid, Tobias;Schmerl, Bradley;Garlan, David;Le Goues, Claire
• 通讯作者: Le Goues, Claire

An Empirical Study of OSS-Fuzz Bugs

• DOI: 10.1109/msr52588.2021.00026
• 发表时间: 2021-03
• 期刊: 2021 IEEE/ACM 18th International Conference on Mining Software Repositories (MSR)
• 作者: Zhen Yu Ding;Claire Le Goues

Semantic Crash Bucketing

• DOI: 10.1145/3238147.3238200
• 发表时间: 2018-09
• 期刊: 2018 33rd IEEE/ACM International Conference on Automated Software Engineering (ASE)
• 作者: Rijnard van Tonder;John Kotheimer;Claire Le Goues

Quality of Automated Program Repair on Real-World Defects

• DOI: 10.1109/tse.2020.2998785
• 发表时间: 2022-02
• 期刊: IEEE Transactions on Software Engineering
• 影响因子: 7.4
• 作者: Manish Motwani;Mauricio Soto;Yuriy Brun;René Just;Claire Le Goues