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A Survey and Taxonomy of Intent-Based Code Search

A Survey and Taxonomy of Intent-Based Code Search
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Author(s): Shailesh Kumar Shivakumar (IGNOU, India)
Copyright: 2021
Volume: 9
Issue: 1
Pages: 42
Source title: International Journal of Software Innovation (IJSI)
Editor(s)-in-Chief: Roger Y. Lee (Central Michigan University, USA)and Lawrence Chung (The University of Texas at Dallas, USA)
DOI: 10.4018/IJSI.2021010106

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Abstract

In this paper, the authors introduce the novel concept of intent-based code search that categorizes code search goals into a hierarchy. They will explore state-of-the-art techniques in source code search covering various tools, techniques, and algorithms related to source code search. They will survey the code search field through the core use cases of code search such as code reusability, code understanding, and code repair. They propose a user intent-based taxonomy based on the code search goals. The code search goal taxonomy is derived based on deep analysis of literature survey of code search, and the taxonomy is validated based on their exclusive developer survey conducted as part of this paper. The code search goal taxonomy is based on logical categorization of code search goals and shared characteristics (query type, expected response, and such) for each of the categories in the taxonomy. The paper also details the latest trends and surveys the code search tools and the implications on tool design.

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