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oaioai:digitalcommons.tamusa.edu:computer_faculty-1021

Test Cases Selection Based on Source Code Features Extraction

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Publication date
1 January 2014
Publisher
'Science and Engineering Research Support Society'
Doi

    Abstract

    Extracting valuable information from source code automatically was the subject of many research papers. Such information can be used for document traceability, concept or feature extraction, etc. In this paper, we used an Information Retrieval (IR) technique: Latent Semantic Indexing (LSI) for the automatic extraction of source code concepts for the purpose of test cases\u27 reduction. We used and updated the open source FLAT Eclipse add on to try several code stemming approaches. The goal is to check the best approach to extract code concepts that can improve the process of test cases\u27 selection or reduction

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    Last time updated on 17/10/2019

    This paper was published in Digital Commons @ Texas A&M University-San Antonio.

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