An information retrieval approach to concept location in source code

TLDR

Concept location identifies parts of a software system that implement a specific concept originating from the problem or solution domain and is a common activity supporting maintenance and evolution tasks such as incremental change and reverse engineering. This work addresses concept location using Latent Semantic Indexing (LSI). Latent Semantic Indexing maps programmer‑expressed natural‑language concepts to the relevant source‑code components. A case study on NCSA Mosaic presents results that are compared with previously published static methods for concept location.

Abstract

Concept location identifies parts of a software system that implement a specific concept that originates from the problem or the solution domain. Concept location is a very common software engineering activity that directly supports software maintenance and evolution tasks such as incremental change and reverse engineering. This work addresses the problem of concept location using an advanced information retrieval method, Latent Semantic Indexing (LSI). LSI is used to map concepts expressed in natural language by the programmer to the relevant parts of the source code. Results of a case study on NCSA Mosaic are presented and compared with previously published results of other static methods for concept location.