CRII: SHF: An Automated and User-centered Framework for Reproducing System-level Concurrency Bugs by Analyzing Bug Reports

CRII：SHF：通过分析错误报告来重现系统级并发错误的自动化且以用户为中心的框架

• 批准号: 2348277
• 负责人: Tarannum Shaila Zaman
• 金额: $ 17.5万
• 依托单位: SUNY Polytechnic Institute
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-06-01 至 2026-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2348277&HistoricalAwards=false
• 关键词: CRII; SHF; Automated; User; centered

Reproducing a software bug is necessary to ensure that the bug exists and to observe its behavior. It is also essential for further analysis to fix the bug. Reproducing system-level concurrency bugs requires not only input data but also the interleaving order of system calls. Manually reproducing this type of bug from bug reports is challenging due to its elusive nature and the need for supplementary details. Moreover, bug reports composed in natural language are frequently unstructured, posing a challenge when it comes to extracting essential information. Existing bug reproduction tools are incompatible with this type of bug due to their inability to deal with the specific interleaving schedule at the system call level. To address these challenges and improve the efficiency of reproducing these bugs from bug reports, a novel framework named RepSON will be developed. It will lessen the manual burden of the software developers to debug system-level concurrency bugs that happen frequently in modern software systems. Furthermore, this project will develop a technique for extracting information and generating executable inputs from bug reports that can also be applied to other types of software bugs.The technical goals of the project are divided into two major tasks. First, an empirical study will be conducted on open-source bug repositories to identify system-level concurrency bug reports and summarize their characteristics for guiding the automated debugging process. Second, an automated framework RepSON will be developed for reproducing bugs in multi-process applications by analyzing bug reports. Natural language processing, data mining, and dynamic program analysis techniques will be employed in the development of RepSON. It will take a bug report as input and reproduce the associated bug by generating input and instrumentation location. To achieve this, RepSON will analyze the bug report to generate the input script and extract system call names that may cause the bug. Subsequently, it will run the program, collect the system call trace to identify potential buggy interleaving, and instrument the code to run it again and reproduce the bug.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.

重现软件错误对于确保错误存在并观察其行为是必要的。进一步分析以修复错误也很重要。重现系统级并发错误不仅需要输入数据，还需要系统调用的交错顺序。由于其难以捉摸的性质并且需要补充详细信息，从错误报告中手动重现此类错误具有挑战性。此外，以自然语言编写的错误报告通常是非结构化的，这在提取基本信息时构成了挑战。现有的错误重现工具与此类错误不兼容，因为它们无法处理系统调用级别的特定交错调度。为了应对这些挑战并提高从错误报告中重现这些错误的效率，将开发一个名为 RepSON 的新颖框架。它将减轻软件开发人员调试现代软件系统中经常发生的系统级并发错误的手动负担。此外，该项目将开发一种从错误报告中提取信息并生成可执行输入的技术，该技术也可以应用于其他类型的软件错误。该项目的技术目标分为两个主要任务。首先，将对开源错误存储库进行实证研究，以识别系统级并发错误报告并总结其特征，以指导自动化调试过程。其次，将开发一个自动化框架 RepSON，用于通过分析错误报告来重现多进程应用程序中的错误。 RepSON的开发将采用自然语言处理、数据挖掘和动态程序分析技术。它将错误报告作为输入，并通过生成输入和检测位置来重现相关错误。为此，RepSON 将分析错误报告以生成输入脚本并提取可能导致错误的系统调用名称。随后，它将运行该程序，收集系统调用跟踪以识别潜在的错误交错，并检测代码以再次运行并重现错误。该奖项反映了 NSF 的法定使命，并通过使用基金会的评估进行评估，被认为值得支持。智力价值和更广泛的影响审查标准。