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Generalized Renewal Process (Grp) For The Analysis Of Software Reliability Growth Model

Author

Listed:
  • MADHU JAIN

    (Department of Mathematics, Institute of Basic Science, Khandari, Agra — 282002, India)

  • SANDHYA MAHESHWARI

    (Department of Mathematics, Institute of Basic Science, Khandari, Agra — 282002, India)

Abstract

With the rapid advancement in computer technology, the software reliability plays a very significant role in predicting the performance and assuring the quality of the software. A compromise testing effort is necessary to affirm the pre-defined quality of the software at optimum cost by detecting and eliminating errors in the software. In this investigation, a robust solution for software reliability growth model (SRGM) which is applicable to non-perfect repair condition called generalized renewal process (GRP) is proposed. The GRP includes the renewal process (RP) and non-homogeneous Poisson process (NHPP) as special cases by suitable choice of index parameters. The optimal testing time of the software is determined for a large and complex modular software system wherein each module having a different failure rate and other characteristics. Maximum likelihood approach is used to estimate the GRP parameters. Numerical illustrations are provided to explore the effect of various parameters on maintenance cost.

Suggested Citation

  • Madhu Jain & Sandhya Maheshwari, 2006. "Generalized Renewal Process (Grp) For The Analysis Of Software Reliability Growth Model," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 23(02), pages 215-227.
    • Handle: RePEc:wsi:apjorx:v:23:y:2006:i:02:n:s0217595906000917
    DOI: 10.1142/S0217595906000917
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    Cited by:

    1. de Oliveira, Cícero Carlos Felix & Firmino, Paulo Renato Alves & Cristino, Cláudio Tadeu, 2019. "A tool for evaluating repairable systems based on Generalized Renewal Processes," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 281-297.
    2. Ricardo José Ferreira & Paulo Renato Alves Firmino & Cláudio Tadeu Cristino, 2015. "A Mixed Kijima Model Using the Weibull-Based Generalized Renewal Processes," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-17, July.

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