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An efficient parameter estimation of software reliability growth models using gravitational search algorithm

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Abstract

This paper presents an effective parameter estimation approach for software reliability growth models using gravitational search algorithm. A software reliability growth model is imperfect, if model parameters are unknown and are not validated on real-time software datasets. There exist several efficient numerical estimation techniques for parameter estimation of software reliability growth models. But they are not panacea. Sample size, biasing and initialization etc. always remain a constraint for best parameter estimation. Results indicate that gravitational search algorithm based technique for parameter estimation overcomes these problems and does superior quality parameter estimation. In this paper, extensive experiments on nine real-time datasets were conducted and results were analyzed to compare the proposed approach. The analysis results point towards the superiority of proposed approach over existing numerical estimation, genetic algorithm and cuckoo search methods.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Amity University Uttar Pradesh, Noida, India

    Ankur Choudhary

  2. Department of Computer Science and Engineering, School of ICT, Gautam Buddha University, Greater Noida, India

    Anurag Singh Baghel

  3. Department of Computer Science and Engineering, Guru Jambheshwar University, Hisar, India

    Om Prakash Sangwan

Authors
  1. Ankur Choudhary
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  2. Anurag Singh Baghel
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  3. Om Prakash Sangwan
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Correspondence to Ankur Choudhary.

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Choudhary, A., Baghel, A.S. & Sangwan, O.P. An efficient parameter estimation of software reliability growth models using gravitational search algorithm. Int J Syst Assur Eng Manag 8, 79–88 (2017). https://doi.org/10.1007/s13198-016-0541-0

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  • DOI: https://doi.org/10.1007/s13198-016-0541-0

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