Collaborative Research: SHF: Medium: Bug Report Management 2.0

协作研究：SHF：中：错误报告管理 2.0

• 批准号: 1955837
• 负责人: Andrian Marcus
• 金额: $ 40.87万
• 依托单位: University of Texas at Dallas
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1955837&HistoricalAwards=false
• 关键词: Collaborative; Research; SHF; Medium; Bug

Software systems often suffer from defects that lead to unexpected results. End users report these unexpected results via issue-reporting systems so that software engineers can identify and fix the related defects to improve the quality of the system. When reporting, users can describe the software problems using natural language or graphical information such as screenshots and videos. Unfortunately, everyday end users are rarely, if ever, trained in reporting software issues. In consequence, they often submit reports that are incomplete or hard to understand, resulting in excessive effort spent addressing the problems, or even the inability for the underlying defects to be identified and fixed. In addition, existing issue-reporting systems are unable to enforce quality standards for reports and fail to provide feedback to the reporters when they submit substandard information. This project will develop a novel-issue reporting system that will allow users to describe software problems interactively, through a dialogue with an automated software agent, rather than writing reports passively, with no feedback and quality assessment. The software agent will automatically convert the conversations into high-quality issue reports, which will be transmitted to the software engineers. The proposed system will allow software engineers to manage and fix defects faster, leading to higher-quality software systems. The project will also produce and disseminate educational material on best practices in reporting software problems. These materials are intended to be integrated into existing computer-literacy courses at all levels of education. In addition, the project will focus on recruiting and retaining computer science students from traditionally underrepresented categories. The project is centered on three specific goals. First, it will develop novel techniques for the automated analysis and quality assessment of defect reports. This component will adapt and build upon techniques for automated discourse analysis, dynamic program analysis, and computer vision. Second, it will improve the quality of issue reports through interactive mechanisms. This proactive reporting solution will be developed through cross-cutting research on empirical software engineering, human-computer interaction, automated text analysis, and advanced machine learning. This new dialogue-based reporting is expected to become the standard method by which many kinds of software issues will be reported. Finally, the project will develop more efficient and effective techniques for automated defect reproduction and duplicate detection, leveraging the high-quality reports created via the interactive reporting system.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.

软件系统经常遭受导致意外结果的缺陷。最终用户通过问题报告系统报告这些意外的结果，这样软件工程师就可以识别并修复相关的缺陷，从而提高系统的质量。在报告时，用户可以使用自然语言或图形信息（如截图和视频）描述软件问题。不幸的是，每天的终端用户很少（如果有的话）接受报告软件问题的培训。因此，他们经常提交不完整或难以理解的报告，导致花费过多的精力来处理问题，甚至无法识别和修复潜在的缺陷。此外，现有的问题报告制度无法执行报告的质量标准，当记者提交不合格的信息时，也无法向他们提供反馈。该项目将开发一个新问题报告系统，允许用户通过与自动软件代理的对话交互式地描述软件问题，而不是被动地编写报告，没有反馈和质量评估。软件代理将自动将对话转换为高质量的问题报告，并将其传送给软件工程师。所建议的系统将允许软件工程师更快地管理和修复缺陷，从而导致更高质量的软件系统。该项目还将制作和传播关于报告软件问题的最佳实践的教育材料。这些材料的目的是将其纳入各级教育现有的计算机知识课程。此外，该项目将侧重于从传统上代表性不足的类别中招募和留住计算机科学专业的学生。该项目以三个具体目标为中心。首先，它将为缺陷报告的自动分析和质量评估开发新的技术。该组件将适应并建立在自动话语分析、动态程序分析和计算机视觉技术的基础上。二是通过互动机制提高问题报告质量。这种主动报告解决方案将通过对经验软件工程、人机交互、自动文本分析和高级机器学习的交叉研究来开发。这种新的基于对话的报告有望成为报告多种软件问题的标准方法。最后，项目将为自动缺陷再现和重复检测开发更有效的技术，利用通过交互式报告系统创建的高质量报告。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识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

An empirical study of data constraint implementations in Java

• DOI: 10.1007/s10664-022-10175-w
• 发表时间: 2021-07
• 期刊: Empirical Software Engineering
• 影响因子: 4.1
• 作者: Juan Manuel Florez;Laura Moreno;Zenong Zhang;Shiyi Wei;Andrian Marcus

BURT: A Chatbot for Interactive Bug Reporting

BURT：用于交互式错误报告的聊天机器人

• 发表时间: 2023
• 期刊: 45th IEEE/ACM International Conference on Software Engineering
• 作者: Song, Y.;Mahmud, J.;De Silva, N.;Zhou, Y.;Chaparro, O.;Moran, K.;Marcus, A.;Poshyvanyk, D.
• 通讯作者: Poshyvanyk, D.

Retrieving data constraint implementations using fine-grained code patterns

使用细粒度代码模式检索数据约束实现

• DOI: 10.1145/3510003.3510167
• 发表时间: 2022
• 期刊: International Conference on Software Engineering
• 作者: Florez, Juan Manuel;Perry, Jonathan;Wei, Shiyi;Marcus, Andrian
• 通讯作者: Marcus, Andrian

Translating Video Recordings of Complex Mobile App UI Gestures into Replayable Scenarios

• DOI: 10.1109/tse.2022.3192279
• 发表时间: 2023-01
• 期刊: IEEE Transactions on Software Engineering
• 影响因子: 7.4
• 作者: Carlos Bernal-Cárdenas;Nathan Cooper;Madeleine Havranek;Kevin Moran;Oscar Chaparro;D. Poshyvanyk;Andrian Marcus

Toward interactive bug reporting for (android app) end-users

为（android 应用程序）最终用户提供交互式错误报告

• DOI: 10.1145/3540250.3549131
• 发表时间: 2022
• 期刊: 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering
• 作者: Song, Yang;Mahmud, Junayed;Zhou, Ying;Chaparro, Oscar;Moran, Kevin;Marcus, Andrian;Poshyvanyk, Denys
• 通讯作者: Poshyvanyk, Denys