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Ant Colony Optimization (ACO-Min) Algorithm for Test Suite Minimization

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Progress in Computing, Analytics and Networking

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1119))

Abstract

This paper presents a test suite (TS) minimization algorithm based on ant colony optimization. The algorithm represents all the test cases in the test suite as nodes of a complete graph. Each test case execution time and corresponding test requirement are stored in the form of a matrix. Ants start from the nodes of the complete graph. The selection of neighbor nodes depends on maximizing requirements and minimizing execution time, for which the ant takes the help of the matrix. The algorithm finds a representative set (RS) of test case which satisfies all the requirements and takes least execution time. The derived representative set satisfies (i) |RS| ⊑ |TS| (ii) τRS ≤ τTS. The representative set also preserves the same fault detection capability, like that of the original test suite, which ensures zero compromise on the overall effectiveness of the program.

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Notes

  1. 1.

    SIR repository: website, http://sir.unl.edu/portal/index.php/ (Accessed September 15, 2018).

  2. 2.

    The Eclipse Foundation website, http://www.eclipse.org/ (Accessed September 15, 2018).

  3. 3.

    JUnit’s official website, http://www.junit.org/ (Accessed September 15, 2018).

  4. 4.

    http://www.eclipse.org/eclipse/ant/ (Accessed September 15, 2018).

  5. 5.

    EclEmma’s official website, http://www.eclemma.org/ (Accessed September 15, 2018).

  6. 6.

    Jumble home page, http://jumble.sourceforge.net (Accessed September 15, 2018).

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Author information

Authors and Affiliations

  1. G.I.E.T University, Gunupur, Odisha, 765022, India

    Subhasish Mohanty

  2. Addis Ababa Science & Technology University, 16417, Addis Ababa, Ethiopia

    Sudhir Kumar Mohapatra & Sultan Feisso Meko

Authors
  1. Subhasish Mohanty
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  2. Sudhir Kumar Mohapatra
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  3. Sultan Feisso Meko
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Corresponding author

Correspondence to Sudhir Kumar Mohapatra .

Editor information

Editors and Affiliations

  1. School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, Odisha, India

    Himansu Das

  2. School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, Odisha, India

    Prasant Kumar Pattnaik

  3. School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, Odisha, India

    Siddharth Swarup Rautaray

  4. Department of Computer Science and Information Engineering (CSIE), Providence University, Taichung, Taiwan

    Kuan-Ching Li

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Mohanty, S., Mohapatra, S.K., Meko, S.F. (2020). Ant Colony Optimization (ACO-Min) Algorithm for Test Suite Minimization. In: Das, H., Pattnaik, P., Rautaray, S., Li, KC. (eds) Progress in Computing, Analytics and Networking. Advances in Intelligent Systems and Computing, vol 1119. Springer, Singapore. https://doi.org/10.1007/978-981-15-2414-1_6

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