CRII: SHF: RUI: Leroid: Bug Oracle and Environment Configuration Automation for Android Bug Report Reproduction

移动应用程序的开发人员严重依赖问题跟踪系统中的错误报告来重现故障。然而，故障再现过程通常由开发人员手动完成，这使得错误的解决效率低下且成本高昂，特别是因为错误报告通常是用自然语言编写的。例如，错误报告可能会遗漏复制信息所需的步骤，或者包含不明确的讨论。然而，现有的方法远远不能解决缺陷报告复制中的所有问题。第一个悬而未决的问题是Bug Oracle生成问题。目前的方法只能支持复制崩溃错误报告，而其他类型的错误仍然需要自动生成的Oracle来确定错误是否已复制。另一个悬而未决的问题是，复制环境配置(例如，Android SDK版本)仍然需要人工从错误报告中手动收集信息并进行配置。该项目将开发一种新的方法，通过自动生成先知和配置环境，支持复制更多类型的Android错误报告。这项研究使软件开发人员能够更快地复制错误报告并修复错误，这将提高软件质量。反过来，这将使我们严重依赖软件的现代社会受益。此外，该项目通过与课程课程整合、培训来自代表性不足的少数群体的学生以及组织旨在提高K-12女孩对STEM相关职业的兴趣的暑期研讨会，促进了多样化的劳动力队伍。为了通过支持Oracle生成和环境配置大幅提高自动化错误报告的复制，将开发新的技术和工具，以解决三个重要挑战：(1)在错误报告中提取观察/预期和环境信息语句；(2)生成可确定目标错误是否已被触发的Oracle断言代码；(3)配置复制环境。在这个项目中，基于技术组合的技术和工具包括静态/动态程序分析、深度学习、自然语言处理和网络爬行。该方法将嵌入到用户界面中，并通过公共错误报告和行业合作进行广泛评估。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Developers of mobile apps rely heavily on bug reports in issue-tracking systems to reproduce failures. However, the process of failure reproduction is often manually done by developers, making the resolution of bugs inefficient and costly, especially since bug reports are often written in natural language. For example, bug reports may miss necessary steps-to-reproduce information or include unclear discussions. However, existing approaches are far from solving all problems in bug report reproduction. The first open problem is the bug oracle generation problem. Current approaches can only support reproducing crash bug reports while other types of bugs still need automatic-generated oracles to determine whether the bug has been reproduced or not. Another open problem is that reproducing environment configurations (e.g., Android SDK version) still requires human effort to manually collect information from bug reports and configure them. This project will develop a novel approach that can support reproducing more bug types of Android bug reports by automatically generating oracles and configuring environments. This research allows software developers to more quickly reproduce bug reports and to fix bugs, which will increase software quality. This, in turn, will benefit our modern society, which greatly relies on software. Additionally, this project contributes toward a diverse workforce, through integration with course curricula, training of students from underrepresented minority groups, and organizing summer workshops aimed at increasing K-12 girls’ interest in STEM-related careers.To substantially improve automated bug report reproduction by supporting oracle generation and environment configuration, novel techniques and tools will be developed that address three important challenges: (1) extract observation/expectation and environment information sentences in a bug report, (2) generate oracle assertion codes that can determine whether the targeted bug has been triggered, (3) configure reproducing environment. In this project, techniques and tools based on a combination of techniques include static/dynamic program analyses, deep learning, natural language processing, and web crawling. The approach will be embedded in a user interface and evaluated extensively on public bug reports and through industrial collaborations.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.