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Soft Computing Applications pp 149–164Cite as

Estimating Software Reliability Growth Model Parameters Using Opposition-Based Shuffled Frog-Leaping Algorithm

Part of the Studies in Computational Intelligence book series (SCI,volume 761)

Abstract

Software engineering (SE) is concerned with designing, developing and maintaining programs that behave reliably and efficiently. SE is composed of various phases which software goes through during and after its development. In today’s prospects, predicting quality of software is a quite challenging task. This study focuses on a recent bio-inspired algorithm named shuffled frog-leaping algorithm (SFLA) for estimating parameters of software reliability growth models (SRGM). Most of the bio-inspired algorithms are inspired by some real-world phenomenon, generally a natural method of optimization. Over the last few decades, a number of bio-inspired algorithms have been introduced and applied on various problems of different domains. SFLA embeds features of particle swarm optimization (PSO) and shuffled complex evolution (SCE) algorithms. It is evident from the literature that SFLA can be efficiently applied to solve various engineering design problems. A variant of SFLA named O-SFLA that embeds opposition-based learning is also introduced in this study. This variant has been evaluated on a set of benchmark problems, which have been verified by performing nonparametric analysis. Later the application of O-SFLA has been carried out on estimating parameters of software reliability growth models (SRGM).

Keywords

  • Shuffled frog-leaping algorithm
  • SFLA
  • Opposition-based learning
  • OBL
  • Software reliability growth models
  • Global optimization

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Author information

Authors and Affiliations

  1. Amity University Rajasthan, Jaipur, India

    Tarun Kumar Sharma

Authors
  1. Tarun Kumar Sharma
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Corresponding author

Correspondence to Tarun Kumar Sharma .

Editor information

Editors and Affiliations

  1. Amity School of Applied Sciences, Amity University Rajasthan, Jaipur, Rajasthan, India

    Prof. Dr. Kanad Ray

  2. Department of Applied Science and Engineering, IIT Roorkee, Saharanpur, Uttar Pradesh, India

    Prof. Millie Pant

  3. Surface Characterization Group, National Institute for Materials Science, Tsukuba, Ibaraki, Japan

    Dr. Anirban Bandyopadhyay

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Sharma, T.K. (2018). Estimating Software Reliability Growth Model Parameters Using Opposition-Based Shuffled Frog-Leaping Algorithm. In: Ray, K., Pant, M., Bandyopadhyay, A. (eds) Soft Computing Applications. Studies in Computational Intelligence, vol 761. Springer, Singapore. https://doi.org/10.1007/978-981-10-8049-4_8

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  • DOI: https://doi.org/10.1007/978-981-10-8049-4_8

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-8048-7

  • Online ISBN: 978-981-10-8049-4

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