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Application of fuzzy time series in prediction of time between failures & faults in software reliability assessment

Author

Listed:
  • S. Chatterjee

    (Indian School of Mines)

  • S. Nigam

    (Indian School of Mines)

  • J. B. Singh

    (Indian School of Mines)

  • L. N. Upadhyaya

    (Indian School of Mines)

Abstract

Since last seventies, various software reliability growth models (SRGMs) have been developed to estimate different measures related to quality of software like: number of remaining faults, software failure rate, reliability, cost, release time, etc. Most of the exiting SRGMs are probabilistic. These models have been developed based on various assumptions. The entire software development process is performed by human being. Also, a software can be executed in different environments. As human behavior is fuzzy and the environment is changing, the concept of fuzzy set theory is applicable in developing software reliability models. In this paper, two fuzzy time series based software reliability models have been proposed. The first one predicts the time between failures (TBFs) of software and the second one predicts the number of errors present in software. Both the models have been developed considering the software failure data as linguistic variable. Usefulness of the models has been demonstrated using real failure data.

Suggested Citation

  • S. Chatterjee & S. Nigam & J. B. Singh & L. N. Upadhyaya, 2011. "Application of fuzzy time series in prediction of time between failures & faults in software reliability assessment," Fuzzy Information and Engineering, Springer, vol. 3(3), pages 293-309, September.
    • Handle: RePEc:spr:fuzinf:v:3:y:2011:i:3:d:10.1007_s12543-011-0084-7
    DOI: 10.1007/s12543-011-0084-7
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    References listed on IDEAS

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    1. Hoang Pham, 2006. "System Software Reliability," Springer Series in Reliability Engineering, Springer, number 978-1-84628-295-9, December.
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    Cited by:

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