论文标题
代码搜索工具中的机会和挑战
Opportunities and Challenges in Code Search Tools
论文作者
论文摘要
代码搜索是一项核心软件工程任务。有效的代码搜索工具可以帮助开发人员实质上提高其软件开发效率和效率。近年来，许多代码搜索研究利用了不同的技术，例如深度学习和信息检索方法，以从大规模代码库中检索预期的代码。但是，缺乏现有代码搜索方法的全面比较摘要。为了了解现有代码搜索研究的研究趋势，我们系统地审查了81项相关研究。我们研究了代码搜索研究的出版趋势，分析了用于构建代码搜索工具的密码库，查询和建模技术等关键组件，并将现有工具分类为专注于支持七个不同的搜索任务。根据我们的发现，我们确定了现有研究中的一系列杰出挑战，以及用于未来代码搜索研究的研究路线图。
Code search is a core software engineering task. Effective code search tools can help developers substantially improve their software development efficiency and effectiveness. In recent years, many code search studies have leveraged different techniques, such as deep learning and information retrieval approaches, to retrieve expected code from a large-scale codebase. However, there is a lack of a comprehensive comparative summary of existing code search approaches. To understand the research trends in existing code search studies, we systematically reviewed 81 relevant studies. We investigated the publication trends of code search studies, analyzed key components, such as codebase, query, and modeling technique used to build code search tools, and classified existing tools into focusing on supporting seven different search tasks. Based on our findings, we identified a set of outstanding challenges in existing studies and a research roadmap for future code search research.
