Towards Recovering Architectural Concepts Using Latent Semantic Indexing

In order to address the problem of locating high-level concepts in source code we propose to use an advanced information retrieval method to exploit linguistic information found in source code, such as variable names and comments. Our technique is based on latent semantic indexing (LSI) which is als...

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Bibliographic Details
Published in2008 12th European Conference on Software Maintenance and Reengineering pp. 253 - 257
Main Authors van der Spek, P., Klusener, S., van de Laar, P.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2008
Subjects
Clustering
Clustering algorithms
Embedded system
Feature Extraction
Indexing
Information retrieval
Large scale integration
Latent Semantic Indexing
Medical services
Natural language processing
Reverse Engineering
Search engines
Software Architecture
Software maintenance
Software systems
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Summary:In order to address the problem of locating high-level concepts in source code we propose to use an advanced information retrieval method to exploit linguistic information found in source code, such as variable names and comments. Our technique is based on latent semantic indexing (LSI) which is also used in today's search engines. Applying LSI to source code, however, is not straightforward. Our approach therefore not only includes LSI, but also several other algorithms and methods. We discuss the algorithms and methods that turned out to be useful and provide an overview of their effects using the results obtained from a case study at Philips Healthcare.
ISBN:9781424421572
1424421578
ISSN:1534-5351
2640-7574
DOI:10.1109/CSMR.2008.4493321