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Improving Source Code Search with Natural Language Phrasal Representations of Method Signatures

Emily Hill, Lori Pollock, and K. Vijay-Shanker
(Montclair State University, USA; University of Delaware, USA)

As software continues to grow, locating code for maintenance tasks becomes increasingly difficult. Software search tools help developers find source code relevant to their maintenance tasks. One major challenge to successful search tools is locating relevant code when the user’s query contains words with multiple meanings or words that occur frequently throughout the program. Traditional search techniques, which treat each word individually, are unable to distinguish relevant and irrelevant methods under these conditions. In this paper, we present a novel search technique that uses information such as the position of the query word and its semantic role to calculate relevance. Our evaluation shows that this approach is more consistently effective than three other state of the art search techniques.

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