A Survey of Source Code Search: A 3-Dimensional Perspective

IF 6.6 2区 计算机科学 Q1 COMPUTER SCIENCE, SOFTWARE ENGINEERING ACM Transactions on Software Engineering and Methodology Pub Date : 2024-04-06 DOI:10.1145/3656341
Weisong Sun, Chunrong Fang, Yifei Ge, Yuling Hu, Yuchen Chen, Quanjun Zhang, Xiuting Ge, Yang Liu, Zhenyu Chen
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Abstract

(Source) code search is widely concerned by software engineering researchers because it can improve the productivity and quality of software development. Given a functionality requirement usually described in a natural language sentence, a code search system can retrieve code snippets that satisfy the requirement from a large-scale code corpus, e.g., GitHub. To realize effective and efficient code search, many techniques have been proposed successively. These techniques improve code search performance mainly by optimizing three core components, including query understanding component, code understanding component, and query-code matching component. In this paper, we provide a 3-dimensional perspective survey for code search. Specifically, we categorize existing code search studies into query-end optimization techniques, code-end optimization techniques, and match-end optimization techniques according to the specific components they optimize. These optimization techniques are proposed to enhance the performance of specific components, and thus the overall performance of code search. Considering that each end can be optimized independently and contributes to the code search performance, we treat each end as a dimension. Therefore, this survey is 3-dimensional in nature, and it provides a comprehensive summary of each dimension in detail. To understand the research trends of the three dimensions in existing code search studies, we systematically review 68 relevant literatures. Different from existing code search surveys that only focus on the query end or code end or introduce various aspects shallowly (including codebase, evaluation metrics, modeling technique, etc.), our survey provides a more nuanced analysis and review of the evolution and development of the underlying techniques used in the three ends. Based on a systematic review and summary of existing work, we outline several open challenges and opportunities at the three ends that remain to be addressed in future work.

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源代码搜索调查:三维视角
(源代码搜索可以提高软件开发的效率和质量,因此受到软件工程研究人员的广泛关注。给定一个通常用自然语言句子描述的功能需求,代码搜索系统可以从大规模代码语料库(如 GitHub)中检索出满足该需求的代码片段。为了实现高效的代码搜索,人们相继提出了许多技术。这些技术主要通过优化三个核心组件来提高代码搜索性能,包括查询理解组件、代码理解组件和查询-代码匹配组件。本文从三维角度对代码搜索进行了研究。具体来说,我们将现有的代码搜索研究按照其优化的具体组件分为查询端优化技术、代码端优化技术和匹配端优化技术。这些优化技术的提出是为了提高特定组件的性能,从而提高代码搜索的整体性能。考虑到每个末端都可以独立优化并对代码搜索性能做出贡献,我们将每个末端视为一个维度。因此,本调查报告具有三维性质,对每个维度的细节进行了全面总结。为了了解现有代码搜索研究中三个维度的研究趋势,我们系统地回顾了 68 篇相关文献。与现有的代码搜索研究只关注查询端或代码端或浅层次介绍各方面(包括代码库、评估指标、建模技术等)不同,我们的调查对三端所使用的底层技术的演变和发展进行了更细致的分析和回顾。在对现有工作进行系统回顾和总结的基础上,我们概述了三端中有待在未来工作中解决的若干挑战和机遇。
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来源期刊
ACM Transactions on Software Engineering and Methodology
ACM Transactions on Software Engineering and Methodology 工程技术-计算机:软件工程
CiteScore
6.30
自引率
4.50%
发文量
164
审稿时长
>12 weeks
期刊介绍: Designing and building a large, complex software system is a tremendous challenge. ACM Transactions on Software Engineering and Methodology (TOSEM) publishes papers on all aspects of that challenge: specification, design, development and maintenance. It covers tools and methodologies, languages, data structures, and algorithms. TOSEM also reports on successful efforts, noting practical lessons that can be scaled and transferred to other projects, and often looks at applications of innovative technologies. The tone is scholarly but readable; the content is worthy of study; the presentation is effective.
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