一个在提交时进行软件缺陷预防的项目:一个大学-工业研究合作的成功案例

A. Hamou-Lhadj, Mathieu Nayrolles
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引用次数: 1

摘要

在这次演讲中,我们将介绍康考迪亚大学和育碧之间的一个研究合作项目。该项目包括在提交时调查用于缺陷预防的技术,以提高软件质量。这个项目的成果是一个名为CLEVER(结合Bug预防和解决技术的层次)的工具,它使用机器学习在程序员编写代码时自动检测编码缺陷。CLEVER的主要新颖之处在于,它依靠代码匹配技术来检测基于多个相关项目中发现的历史代码缺陷数据库的编码错误。该工具还根据已知模式提出修复建议。
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A Project on Software Defect Prevention at Commit-Time: A Success Story of University-Industry Research Collaboration
In this talk, we describe a research collaboration project between Concordia University and Ubisoft. The project consists of investigating techniques for defect prevention at commit-time for increased software quality. The outcome of this project is a tool called CLEVER (Combining Levels of Bug Prevention and Resolution techniques) that uses machine learning to automatically detect coding defects as programmers write code. The main novelty of CLEVER is that it relies on code matching techniques to detect coding mistakes based on a database of historical code defects found in multiple related projects. The tool also proposes fixes based on known patterns.
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