CRI: CI-P: Collaborative: Towards a Program Analysis Collaboratory

CRI：CI-P：协作：迈向程序分析协作实验室

• 批准号: 1823294
• 负责人: Robert Dyer
• 金额: $ 4.65万
• 依托单位: Bowling Green State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-01 至 2020-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1823294&HistoricalAwards=false
• 关键词: CRI; CI; Collaborative; Towards; Program

Benchmark programs play an important role in evaluating the advances in program analysis research. Thus, the confidence of the evaluation depends on the quantity and the quality of the benchmark programs. The larger their number and the closer they resemble real-world programs, the higher confidence in the evaluation. Currently, research in the field of program analysis often relies on a few outdated or deficient benchmark programs for evaluation purposes. The difficulty in obtaining sufficient benchmark programs comes from the requirements imposed on the benchmark programs by program analyzers. Usually researchers manually obtain, inspect, and transform potential benchmark programs to create benchmark programs that meet those requirements. Such an unscalable approach often fails to produce adequate benchmark programs. The goal of this research is to automate this process and make it available through an online, public infrastructure. The infrastructure facilitates obtaining, selecting, and transforming open-source software projects for use as benchmark programs. In addition, the infrastructure gives researchers the ability to easily curate benchmark programs for program analysis and share the results of running their analyzers on those benchmarks. The objectives of this project are to solicit requirements and feedback from the program analysis community on automating benchmark program generation, and to prototype a Program Analysis Collaboratory (PAClab) research infrastructure that implements that process. Using researchers' specifications for adequate benchmark program generation, PAClab locates and obtains potential benchmark programs in open-source repositories; performs necessary program transformations as specified by researchers; and outputs the adequate benchmark programs. In addition, PAClab enables researchers to share their program analyzers using container technology, the transformed benchmark programs, and the results of running their analyzers on those benchmark programs. The intellectual merit of the project lies in investigating techniques for specifying and automating program transformations for targeted program analyzers. The broader impacts of the project stem from its potential to broaden adaptation of program analysis advances through the increased confidence of their evaluations; to lower the entry barrier for new program analysis researchers; and to accelerate the pace in program analysis research. PAClab's educational benefits include the ability for students to easily locate real-world programs and evaluate their implementations of program analyzers.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.

基准计划在评估程序分析研究的进步方面起着重要作用。因此，评估的信心取决于基准计划的数量和质量。他们的数量越大，它们的距离越大，它们类似于现实世界的计划，对评估的信心就越高。目前，计划分析领域的研究通常依赖于一些过时或缺陷的基准计划来评估目的。获得足够的基准计划的困难来自计划分析仪对基准计划施加的要求。通常，研究人员手动获得，检查和改变潜在的基准计划，以创建满足这些要求的基准计划。这种不可估量的方法通常无法产生足够的基准计划。这项研究的目的是自动化此过程，并通过在线公共基础架构提供。基础架构有助于获取，选择和转换开源软件项目作为基准程序。此外，基础架构使研究人员能够轻松地策划基准计划进行程序分析，并分享其分析仪在这些基准测试上的结果。该项目的目标旨在从计划分析社区征求有关基准计划生成的要求和反馈，并原型制作了实施该过程的计划分析协作（PACLAB）研究基础架构。 Paclab使用研究人员的规格来生成足够的基准计划，并在开源存储库中找到并获得了潜在的基准计划；执行研究人员指定的必要程序转换；并输出足够的基准计划。此外，PACLAB使研究人员能够使用容器技术，转换的基准程序以及在这些基准计划上运行分析仪的结果。该项目的智力优点在于调查针对目标计划分析仪指定和自动化程序转换的技术。该项目的更广泛的影响源于其通过增强评估信心扩大计划分析的适应性的潜力；降低新计划分析研究人员的进入障碍；并加速程序分析研究的步伐。帕克拉布（Paclab）的教育福利包括学生轻松地定位现实世界计划并评估其计划分析仪的实施的能力。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子和更广泛影响的评估评估标准来通过评估来获得支持的。

项目成果

Software engineering collaboratories (SEClabs) and collaboratories as a service (CaaS)

软件工程合作实验室 (SEClabs) 和合作实验室即服务 (CaaS)

• DOI: 10.1145/3236024.3264839
• 发表时间: 2018
• 期刊: Proceedings of the 2018 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering
• 作者: Sherman, Elena;Dyer, Robert
• 通讯作者: Dyer, Robert