CAREER: Cooperative Program Analysis: Bridging the Gap Between User and Tool Reasoning

职业：合作程序分析：弥合用户和工具推理之间的差距

• 批准号: 1055066
• 负责人: Bor-Yuh Evan Chang
• 金额: $ 45.96万
• 依托单位: University of Colorado at Boulder
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-06-01 至 2018-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1055066&HistoricalAwards=false
• 关键词: CAREER; Cooperative; Program; Analysis; Bridging

While not perfect, the depth and breadth of what today's automated analysis tools can figure out about a program is truly remarkable. Yet, despite the prevalence and cost of software defects and despite the wealth of information such automated tools could provide, program analyzers are largely ignored by today's software engineers. This situation is not due to a lack of interest from software engineers or a lack of effort in deployment from analysis experts but rather a gap in the way a tool and its user reasons about the program, which results in, for example, a difficulty in providing analysis results understandable to the user. This research confronts closing this user-tool reasoning gap.The focus of the work is an effective approach to user-driven refinement of the analysis process. Novel techniques for generating explanations of program analysis results will be created. New approaches for trading off the exhaustiveness of compile-time verification and the simplicity of run-time checking will be developed. Together with prior work on user-centric analysis specifications, this project lays the foundation for tomorrow's tools where users and tools cooperate to reason effectively about programs. Significant potential impacts include the following: a change in the way software engineers view program analysis--replacing a magic box with a transparent reasoning assistant, improved software quality as a result of this change in view, and tools that engage students in algorithmic thinking in a hands-on manner.

虽然并不完美，但当今的自动化分析工具对程序的了解的深度和广度确实令人惊叹。 然而，尽管软件缺陷普遍存在且成本高昂，尽管此类自动化工具可以提供大量信息，但程序分析器在很大程度上被当今的软件工程师所忽视。 这种情况并不是由于软件工程师缺乏兴趣或分析专家在部署方面缺乏努力，而是由于工具及其用户对程序的推理方式存在差距，这导致例如难以提供用户可以理解的分析结果。 这项研究面临着缩小用户与工具推理差距的问题。工作的重点是用户驱动的分析过程细化的有效方法。 将创建用于生成程序分析结果解释的新技术。 将开发权衡编译时验证的详尽性和运行时检查的简单性的新方法。 与之前以用户为中心的分析规范的工作一起，该项目为未来的工具奠定了基础，用户和工具可以合作有效地推理程序。 重大的潜在影响包括以下内容：软件工程师看待程序分析的方式发生了变化——用透明的推理助手取代了魔盒，由于这种观点的改变而提高了软件质量，以及让学生以动手方式参与算法思维的工具。