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International Conference on Future Data and Security Engineering

FDSE 2019: Future Data and Security Engineering pp 15–30Cite as

A New Test Suite Reduction Approach Based on Hypergraph Minimal Transversal Mining

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11814))

Abstract

Test Suite Reduction (TSR) approaches aim at selecting only those test cases of a test suite to reduce the execution time or decrease the cost of regression testing. They extract the tests that cover test requirements without redundancy, or exercise changed parts of the System Under Test (SUT) or parts affected by changes, respectively. We introduce DTSR (Deterministic Test Suite Reduction), that relies on the hypergraph structural information to select the candidate test cases. Requirement data, which are associated with the test cases, optimize the selection by retaining a deterministic set. To do so, DTSR considers a test suite as a hypergraph, where its nodes are equivalent to tests, and its hyperedges are similar to requirements. The algorithm extracts a subset of the minimal transversals of a hypergraph by selecting the minimum number of test cases satisfying the requirements. We compare our new algorithm versus search based ones, and we show that we outperform the pioneering approaches of the literature. The reduction rate varies from \(50\%\) up to \(65\%\) of the initial set size.

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Notes

  1. 1.

    DTSR stands for deterministic TSR.

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Author information

Authors and Affiliations

  1. Faculty of Sciences of Tunis, University of Tunis El Manar, LIPAH-LR11ES14, 2092, Tunis, Tunisia

    Shaima Trabelsi, Mohamed Taha Bennani & Sadok Ben Yahia

  2. Tallinn University of Technology, Akadeemia tee 15a, 12618, Tallinn, Estonia

    Sadok Ben Yahia

Authors
  1. Shaima Trabelsi
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  2. Mohamed Taha Bennani
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  3. Sadok Ben Yahia
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Corresponding author

Correspondence to Sadok Ben Yahia .

Editor information

Editors and Affiliations

  1. Ho Chi Minh City University of Technology, Ho Chi Minh City, Vietnam

    Tran Khanh Dang

  2. Johannes Kepler Universität Linz, Linz, Austria

    Josef Küng

  3. Hosei University, Tokyo, Japan

    Makoto Takizawa

  4. Telecommunications University, Nha Trang City, Vietnam

    Son Ha Bui

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Trabelsi, S., Bennani, M.T., Yahia, S.B. (2019). A New Test Suite Reduction Approach Based on Hypergraph Minimal Transversal Mining. In: Dang, T., Küng, J., Takizawa, M., Bui, S. (eds) Future Data and Security Engineering. FDSE 2019. Lecture Notes in Computer Science(), vol 11814. Springer, Cham. https://doi.org/10.1007/978-3-030-35653-8_2

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  • DOI: https://doi.org/10.1007/978-3-030-35653-8_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-35652-1

  • Online ISBN: 978-3-030-35653-8

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