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
- 来源:
- 关键词:
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.
软件系统通常会遭受导致意外结果的缺陷。 最终用户通过发出的报告系统报告了这些意外的结果,以便软件工程师可以识别并修复相关缺陷以提高系统质量。 报告时,用户可以使用自然语言或图形信息(例如屏幕截图和视频)来描述软件问题。不幸的是,每天的最终用户很少经过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,导致花费过多的努力解决问题,甚至无法确定和固定的基本缺陷。此外,现有的问题报告系统无法为报告执行质量标准,并且在记者提交不合格信息时未能向记者提供反馈。该项目将开发一个小说的报告系统,该系统将允许用户通过与自动软件代理的对话而不是被动地编写报告,而没有反馈和质量评估,可以通过与自动软件代理进行对话进行交互描述软件问题。 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。提出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。该项目还将生产并传播有关报告软件问题的最佳实践的教育材料。这些材料旨在在各个级别的教育中纳入现有的计算机列表课程中。 此外,该项目将着重于传统代表性不足类别的招募和保留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,它将开发出新的技术,用于对缺陷报告的自动分析和质量评估。该组件将适应自动话语分析,动态程序分析和计算机视觉的技术。 其次,它将通过互动机制提高问题报告的质量。 这种主动的报告解决方案将通过对经验软件工程,人类计算机相互作用,自动化文本分析和高级机器学习的跨剪切研究开发。这种新的基于对话的报告预计将成为标准方法,通过该方法将通过这些方法进行多种软件问题。最后,该项目将开发出更高和有效的技术,用于自动缺陷复制和重复检测,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审查审查标准来通过评估来通过评估来获得支持的。
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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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
- DOI:
10.1145/3611643.3613099 - 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Amit Seal Ami;Syed Yusuf Ahmed;Radowan Mahmud Redoy;Nathan Cooper;Kaushal Kafle;Kevin Moran;Denys Poshyvanyk;Adwait Nadkarni - 通讯作者:
Adwait Nadkarni
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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