Practical Automated Software Bug Fixing via Syntactic and Semantic Analyses

通过句法和语义分析进行实用的自动化软件错误修复

• 批准号: DE220101057
• 负责人: Dr Dinh Xuan Bach Le
• 金额: $ 30.44万
• 依托单位: The University of Melbourne
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Early Career Researcher Award
• 财政年份: 2022
• 资助国家: 澳大利亚
• 起止时间: 2022-01-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DE220101057
• 关键词: Practical; Automated; Software; Bug; Fixing

This proposal aims to advance the practical adoption of automated software bug repair, which has recently been adopted by industry, e.g., Facebook. It will produce novel methods that use mining software repositories, program analysis, and human-guided search to help automated repair to scale and be accurate. Expected outcomes include a publicly available automated bug repair framework. This project will help the software industry deliver to users high quality software with improved reliability and safety, and increase education quality for students learning to code via automated feedback generation.

该提案旨在促进自动软件错误修复的实际采用，该自动软件错误修复最近已被行业采用，例如，Facebook.它将产生新的方法，使用挖掘软件存储库，程序分析和人工引导的搜索来帮助自动修复扩展和准确。预期成果包括一个公开可用的自动错误修复框架。该项目将帮助软件行业向用户提供高质量的软件，提高可靠性和安全性，并通过自动反馈生成提高学生学习编码的教育质量。