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A Path-Oriented Test Data Generation Approach Hybridizing Genetic Algorithm and Artificial Immune System

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Computational Intelligence in Data Mining

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 711))

Abstract

Validating the correctness of software through a tool has started gaining a wide foothold in the business. A test data generator is one such tool which automatically generates the test data for software so as to attain maximum coverage. Researchers in the past have adopted different evolutionary algorithms to automatically generate a data set. One such often used procedure is Genetic Algorithm (GA). Due to certain flaws present in this approach, we have redefined the cause of concern for coverage in structural testing. In this paper, we have explored the properties of immune system along with GA. We have proposed a new hybrid algorithm—GeMune algorithm—inspired from these biological backdrops. Experimental results certify that the new algorithm has a better coverage compared to the use of only Genetic Algorithm for structural testing.

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Author information

Authors and Affiliations

  1. Department of IT, Veer Surendra Sai University of Technology, Burla, 768018, Odisha, India

    Gargi Bhattacharjee & Ashish Singh Saluja

Authors
  1. Gargi Bhattacharjee
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  2. Ashish Singh Saluja
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Corresponding author

Correspondence to Gargi Bhattacharjee .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering & Information Technology, Veer Surendra Sai University of Technology, Sambalpur, Odisha, India

    Himansu Sekhar Behera

  2. Department of Computer Science and Engineering, Sri Sivani College of Engineering (SSCE), Srikakulam, Andhra Pradesh, India

    Janmenjoy Nayak

  3. Department of Computer Application, Veer Surendra Sai University of Technology, Sambalpur, Odisha, India

    Bighnaraj Naik

  4. Machine Intelligence Research (MIR) Lab, Auburn, WA, USA

    Ajith Abraham

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Bhattacharjee, G., Saluja, A.S. (2019). A Path-Oriented Test Data Generation Approach Hybridizing Genetic Algorithm and Artificial Immune System. In: Behera, H., Nayak, J., Naik, B., Abraham, A. (eds) Computational Intelligence in Data Mining. Advances in Intelligent Systems and Computing, vol 711. Springer, Singapore. https://doi.org/10.1007/978-981-10-8055-5_58

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