Publication Type

Journal Article

Version

acceptedVersion

Publication Date

12-2022

Abstract

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.

Keywords

Code search, modeling, code retrieval

Discipline

Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

ACM Computing Surveys

Volume

54

Issue

9

First Page

1

Last Page

35

ISSN

0360-0300

Identifier

10.1145/3480027

Publisher

Association for Computing Machinery (ACM)

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1145/3480027

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