A Systematic Review of Automated Query Reformulations in Source Code Search

TL;DR

This paper systematically reviews 70 studies on automated query reformulation techniques in source code search, highlighting methodologies, limitations, and future research directions to improve bug fixing and feature addition tasks.

Contribution

It provides a comprehensive analysis of existing query reformulation methods, identifies key limitations, and suggests best practices and future opportunities for research advancement.

Findings

Eight major methodologies identified for query reformulation

Major limitations include lack of generalizability and vocabulary mismatch

Discussion of best practices and future research opportunities

Abstract

Fixing software bugs and adding new features are two of the major maintenance tasks. Software bugs and features are reported as change requests. Developers consult these requests and often choose a few keywords from them as an ad hoc query. Then they execute the query with a search engine to find the exact locations within software code that need to be changed. Unfortunately, even experienced developers often fail to choose appropriate queries, which leads to costly trials and errors during a code search. Over the years, many studies attempt to reformulate the ad hoc queries from developers to support them. In this systematic literature review, we carefully select 70 primary studies on query reformulations from 2,970 candidate studies, perform an in-depth qualitative analysis (e.g., Grounded Theory), and then answer seven research questions with major findings. First, to date, eight major methodologies (e.g., term weighting, term co-occurrence analysis, thesaurus lookup) have been adopted to reformulate queries. Second, the existing studies suffer from several major limitations (e.g., lack of generalizability, vocabulary mismatch problem, subjective bias) that might prevent their wide adoption. Finally, we discuss the best practices and future opportunities to advance the state of research in search query reformulations.