Code Search via Topic-Enriched Dependence Graph Matching

Abstract

Source code contains textual, structural, and semantic information, which can all be leveraged for effective search. Some studies have proposed semantic code search where users can specify query topics in a natural language. Other studies can search through system dependence graphs. In this paper, we propose a semantic dependence search engine that integrates both kinds of techniques and can retrieve code snippets based on expressive user queries describing both topics and dependencies. Users can specify their search targets in a free form format describing desired topics (i.e., high-level semantic or functionality of the target code); a specialized graph query language allows users to describe low-level data and control dependencies in code and thus helps to refine the queries described in the free format. Our empirical evaluation on a number of software maintenance tasks shows that our search engine can efficiently locate desired code fragments accurately.