Article

Using latent semantic analysis to identify similarities in source code to support program understanding

ICTAI '00: Proceedings of the 12th IEEE International Conference on Tools with Artificial Intelligence

Page 46

Published: 13 November 2000 Publication History

Abstract

Abstract: The paper describes the results of applying Latent Semantic Analysis (LSA), an advanced information retrieval method, to program source code and associated documentation. Latent semantic analysis is a corpus based statistical method for inducing and representing aspects of the meanings of words and passages (of natural language) reflective in their usage. This methodology is assessed for application to the domain of software components (i.e., source code and its accompanying documentation). Here LSA is used as the basis to cluster software components. This clustering is used to assist in the understanding of a nontrivial software system, namely a version of Mosaic. Applying latent semantic analysis to the domain of source code and internal documentation for the support of program understanding is a new application of this method and a departure from the normal application domain of natural language.

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DeLozier GDecker MNewman CMaletic JKhomh FRoy CSiegmund J(2018)Leveraging the agile development process for selecting invoking/excluding tests to support feature locationProceedings of the 26th Conference on Program Comprehension10.1145/3196321.3196354(370-379)Online publication date: 28-May-2018
https://dl.acm.org/doi/10.1145/3196321.3196354
Shahriar HHaddad HOssowski S(2016)Object injection vulnerability discovery based on latent semantic indexingProceedings of the 31st Annual ACM Symposium on Applied Computing10.1145/2851613.2851865(801-807)Online publication date: 4-Apr-2016
https://dl.acm.org/doi/10.1145/2851613.2851865
Schindler MFox ORausch AHarrison RBener ATurhan B(2015)Clustering source code elements by semantic similarity using WikipediaProceedings of the Fourth International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering10.5555/2820668.2820672(13-18)Online publication date: 16-May-2015
https://dl.acm.org/doi/10.5555/2820668.2820672
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ICTAI '00: Proceedings of the 12th IEEE International Conference on Tools with Artificial Intelligence

November 2000

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IEEE Computer Society

United States

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Published: 13 November 2000

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DeLozier GDecker MNewman CMaletic JKhomh FRoy CSiegmund J(2018)Leveraging the agile development process for selecting invoking/excluding tests to support feature locationProceedings of the 26th Conference on Program Comprehension10.1145/3196321.3196354(370-379)Online publication date: 28-May-2018
https://dl.acm.org/doi/10.1145/3196321.3196354
Shahriar HHaddad HOssowski S(2016)Object injection vulnerability discovery based on latent semantic indexingProceedings of the 31st Annual ACM Symposium on Applied Computing10.1145/2851613.2851865(801-807)Online publication date: 4-Apr-2016
https://dl.acm.org/doi/10.1145/2851613.2851865
Schindler MFox ORausch AHarrison RBener ATurhan B(2015)Clustering source code elements by semantic similarity using WikipediaProceedings of the Fourth International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering10.5555/2820668.2820672(13-18)Online publication date: 16-May-2015
https://dl.acm.org/doi/10.5555/2820668.2820672
Port DNikora AHihn JHuang LTaylor RGall HMedvidović N(2011)Experiences with text mining large collections of unstructured systems development artifacts at jplProceedings of the 33rd International Conference on Software Engineering10.1145/1985793.1985891(701-710)Online publication date: 21-May-2011
https://dl.acm.org/doi/10.1145/1985793.1985891
Gibiec MCzauderna ACleland-Huang JPecheur CAndrews JDi Nitto E(2010)Towards mining replacement queries for hard-to-retrieve tracesProceedings of the 25th IEEE/ACM International Conference on Automated Software Engineering10.1145/1858996.1859046(245-254)Online publication date: 20-Sep-2010
https://dl.acm.org/doi/10.1145/1858996.1859046
Cleland-Huang JCzauderna AGibiec MEmenecker JKramer JBishop JDevanbu PUchitel S(2010)A machine learning approach for tracing regulatory codes to product specific requirementsProceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 110.1145/1806799.1806825(155-164)Online publication date: 1-May-2010
https://dl.acm.org/doi/10.1145/1806799.1806825
Sindhgatta RLi YLiu BSarawagi S(2008)Identifying domain expertise of developers from source codeProceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining10.1145/1401890.1402007(981-989)Online publication date: 24-Aug-2008
https://dl.acm.org/doi/10.1145/1401890.1402007
Kuhn ADucasse SGírba T(2007)Semantic clusteringInformation and Software Technology10.1016/j.infsof.2006.10.01749:3(230-243)Online publication date: 1-Mar-2007
https://dl.acm.org/doi/10.1016/j.infsof.2006.10.017
Kawaguchi SGarg PMatsushita MInoue K(2006)MUDABlueJournal of Systems and Software10.1016/j.jss.2005.06.04479:7(939-953)Online publication date: 1-Jul-2006
https://dl.acm.org/doi/10.1016/j.jss.2005.06.044
Lu WKan M(2005)Supervised categorization of JavaScript™ using program analysis featuresProceedings of the Second Asia conference on Asia Information Retrieval Technology10.1007/11562382_13(160-173)Online publication date: 13-Oct-2005
https://dl.acm.org/doi/10.1007/11562382_13
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