Thesaurus-based automatic query expansion for interface-driven code search.

Software engineers often resort to code search practices to support software maintenance and evolution tasks, in particular code reuse. An issue that affects code search is the vocabulary mismatch problem: while searching for a particular function, users have to guess the exact words that were chosen by original developers to name code entities. In this paper we present an automatic query expansion (AQE) approach that uses word relations to increase the chances of finding relevant code. The approach is applied on top of Test-Driven Code Search (TDCS), a promising code retrieval technique that uses test cases as inputs to formulate the search query, but can also be used with other techniques that handle interface definitions to produce queries (interface-driven code search). Since these techniques rely on keywords and types, the vocabulary mismatch problem is also relevant. AQE is carried out by leveraging WordNet, a type thesaurus for expanding types, and another thesaurus containing only software-related word relations. Our approach is general but was specifically designed for non-native English speakers, who are frequently unaware of the most common terms used to name functions in software. Our evaluation with 36 non-native subjects - including developers and senior Computer Science students - provides evidence that our approach can improve the chances of finding relevant functions by 41% (recall improvement of 30%, on average), without hurting precision.