Collaborative Research: SHF: Medium: Bug Report Management 2.0

协作研究:SHF:中:错误报告管理 2.0

基本信息

  • 批准号:
    1955853
  • 负责人:
  • 金额:
    $ 79.13万
  • 依托单位:
  • 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 2024-09-30
  • 项目状态:
    已结题

项目摘要

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结果,以便软件工程师可以识别和修复相关缺陷,以提高系统质量。 在报告时,用户可以使用自然语言或图形信息(如屏幕截图和视频)描述软件问题。不幸的是,日常终端用户很少(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解决问题,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,在报告者提交不合标准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,该系统将允许用户通过与自动化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,并将其传输给软件工程师。拟议中的系统将允许软件工程师更快地管理和修复缺陷,从而提高软件系统的质量。该项目还将制作和分发关于报告软件问题的最佳做法的教育材料。打算将这些材料纳入各级教育的现有计算机扫盲课程。 此外,该项目将侧重于从传统上代表性不足的类别中招聘和留住计算机科学学生。该项目围绕三个具体目标。 首先,它将为缺陷报告的自动分析和质量评估开发新技术。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议题报道质量。 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。这种新的基于对话框的报告有望成为报告多种软件问题的标准方法。最后,该项目将开发更高效和有效的自动缺陷复制和重复检测技术,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NSF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

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Denys Poshyvanyk其他文献

MASC: A Tool for Mutation-Based Evaluation of Static Crypto-API Misuse Detectors
MASC:基于突变的静态加密 API 滥用检测器评估工具

Denys Poshyvanyk的其他文献

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{{ truncateString('Denys Poshyvanyk', 18)}}的其他基金

Collaborative Research: SHF: Medium: Toward Understandability and Interpretability for Neural Language Models of Source Code
合作研究:SHF:媒介:实现源代码神经语言模型的可理解性和可解释性
  • 批准号:
    2311469
  • 财政年份:
    2023
  • 资助金额:
    $ 79.13万
  • 项目类别:
    Standard Grant
DASS: Enabling Comprehensive and Interactive Open Source Software License Compliance
DASS:实现全面、交互式的开源软件许可证合规性
  • 批准号:
    2217733
  • 财政年份:
    2022
  • 资助金额:
    $ 79.13万
  • 项目类别:
    Standard Grant
SHF: Small: Towards a Holistic Causal Model for Continuous Software Traceability
SHF:小型:迈向连续软件可追溯性的整体因果模型
  • 批准号:
    2007246
  • 财政年份:
    2020
  • 资助金额:
    $ 79.13万
  • 项目类别:
    Standard Grant
EAGER: Mapping Future Synergies between Deep Learning and Software Engineering
EAGER:绘制深度学习与软件工程之间的未来协同效应
  • 批准号:
    1927679
  • 财政年份:
    2019
  • 资助金额:
    $ 79.13万
  • 项目类别:
    Standard Grant
SHF: Small: Natural GUI-Based Testing of Mobile Apps via Mining Software Repositories
SHF:小型:通过挖掘软件存储库对移动应用程序进行基于 GUI 的自然测试
  • 批准号:
    1815186
  • 财政年份:
    2018
  • 资助金额:
    $ 79.13万
  • 项目类别:
    Standard Grant
CI-EN: Collaborative Research: TraceLab Community Infrastructure for Replication, Collaboration, and Innovation
CI-EN:协作研究:用于复制、协作和创新的 TraceLab 社区基础设施
  • 批准号:
    1510239
  • 财政年份:
    2015
  • 资助金额:
    $ 79.13万
  • 项目类别:
    Standard Grant
SHF: Small: Deep Learning Software Repositories
SHF:小型:深度学习软件存储库
  • 批准号:
    1525902
  • 财政年份:
    2015
  • 资助金额:
    $ 79.13万
  • 项目类别:
    Standard Grant
CAREER: Enabling License Compliance Analysis and Verification for Evolving Software
职业:为不断发展的软件提供许可证合规性分析和验证
  • 批准号:
    1253837
  • 财政年份:
    2013
  • 资助金额:
    $ 79.13万
  • 项目类别:
    Continuing Grant
Supporting student travel from underrepresented groups to the 28th IEEE International Conference on Software Maintenance (ICSM 2012)
支持代表性不足群体的学生参加第 28 届 IEEE 软件维护国际会议 (ICSM 2012)
  • 批准号:
    1240505
  • 财政年份:
    2012
  • 资助金额:
    $ 79.13万
  • 项目类别:
    Standard Grant
III: Small: Collaborative Research: Linking Evolving Software Requirements and Acceptance Tests
III:小:协作研究:将不断发展的软件需求和验收测试联系起来
  • 批准号:
    1218129
  • 财政年份:
    2012
  • 资助金额:
    $ 79.13万
  • 项目类别:
    Standard Grant

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