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Optimized test suites for automated testing using different optimization techniques

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Abstract

Automated testing mitigates the risk of test maintenance failure, selects the optimized test suite, improves efficiency and hence reduces cost and time consumption. This paper is based on the development of an automated testing tool which includes two major automated components of software testing, test suite generation and test suite optimization. The control flow of the software under test has been represented by a flow graph. There are five test suite generation methods which are made available in the tool, namely boundary value testing, robustness testing, worst-case testing, robust worst-case testing and random testing. The generated test suite is further optimized to a desired fitness level using the artificial bee colony algorithm or the cuckoo search algorithm. The proposed method is able to provide a set of minimal test cases with maximum path coverage as compared to other algorithms. Finally, the generated optimal test suite is used for automated fault detection.

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Abbreviations

TSG:

Test suite generation

TSO:

Test suite optimization

ABC:

Artificial bee colony

CSA:

Cuckoo search algorithm

SUT:

Software under test

N:

Nodes

E:

Edge

PSO:

Particle swarm optimization

GA:

Genetic algorithm

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Authors and Affiliations

  1. Ambedkar institute of Advanced Communication Technologies, Delhi, India

    Manju Khari & Prabhat Kumar

  2. Universidad Internacional de La Rioja, Logroño, Spain

    Daniel Burgos & Rubén González Crespo

Authors
  1. Manju Khari
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  2. Prabhat Kumar
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  3. Daniel Burgos
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  4. Rubén González Crespo
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Corresponding author

Correspondence to Rubén González Crespo.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Communicated by V. Loia.

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Khari, M., Kumar, P., Burgos, D. et al. Optimized test suites for automated testing using different optimization techniques. Soft Comput 22, 8341–8352 (2018). https://doi.org/10.1007/s00500-017-2780-7

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  • DOI: https://doi.org/10.1007/s00500-017-2780-7

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