Combining Formal Concept Analysis with Information Retrieval for Concept Location in Source Code 论文

2007引用 233
Web Data Mining and AnalysisSoftware Engineering ResearchRough Sets and Fuzzy Logic

摘要

The paper addresses the problem of concept location in source code by presenting an approach which combines formal concept analysis (FCA) and latent semantic indexing (LSI). In the proposed approach, LSI is used to map the concepts expressed in queries written by the programmer to relevant parts of the source code, presented as a ranked list of search results. Given the ranked list of source code elements, our approach selects most relevant attributes from these documents and organizes the results in a concept lattice, generated via FCA. The approach is evaluated in a case study on concept location in the source code of eclipse, an industrial size integrated development environment. The results of the case study show that the proposed approach is effective in organizing different concepts and their relationships present in the subset of the search results. The proposed concept location method outperforms the simple ranking of the search results, reducing the programmers' effort.

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