Applying Semantic Analysis to Feature Execution Traces

Kuhn, Adrian; Greevy, Orla; Gîrba, Tudor (November 2005). Applying Semantic Analysis to Feature Execution Traces. Working Conference on Reverse Engineering. Proceedings, pp. 48-53. Los Alamitos CA: IEEE

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Recently there has been a revival of interest in feature analysis of software systems. Approaches to feature location have used a wide range of techniques such as dynamic analysis, static analysis, information retrieval and formal concept analysis. In this paper we introduce a novel approach to analyze the execution traces of features using Latent Semantic Indexing (LSI). Our goal is twofold. On the one hand we detect similarities between features based on the content of their traces, and on the other hand we categorize classes based on the frequency of the outgoing invocations involved in the traces. We apply our approach on two case studies and we discuss its benefits and drawbacks.

Item Type:

Conference or Workshop Item (Paper)

Division/Institute:

08 Faculty of Science > Institute of Computer Science (INF)
08 Faculty of Science > Institute of Computer Science (INF) > Software Composition Group (SCG)

UniBE Contributor:

Kuhn, Adrian; Greevy, Orla and Girba, Tudor Adrian

Subjects:

000 Computer science, knowledge & systems
500 Science > 510 Mathematics

ISSN:

1095-1350

Publisher:

IEEE

Language:

English

Submitter:

Manuela Bamert

Date Deposited:

18 Oct 2017 15:18

Last Modified:

23 Oct 2017 16:49

BORIS DOI:

10.7892/boris.104565

URI:

https://boris.unibe.ch/id/eprint/104565

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