Clustering Support for Static Concept Location in Source Code

One of the most common comprehension activities undertaken by developers is concept location in source code. In the context of software change, concept location means finding locations in source code where changes are to be made in response to a modification request. Static techniques for concept location usually rely on searching the source code using textual information or on navigating the dependencies among software elements. In this paper we propose a novel static concept location technique, which leverages both the textual information present in the code and the structural dependencies between source code elements. The technique employs a textual search in that source code, which is clustered using the Border Flow algorithm, based on combining both structural and textual data. We evaluated the technique against a text search based baseline approach using data on almost 200 changes from five software systems. The results indicate that the new approach outperforms the baseline and that improvements are still possible.

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