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Bayesian optimum stopping rule for software release

Author

Listed:
  • Ashis Kumar Chakraborty

    (Indian Statistical Institute, Kolkata)

  • Gopal Krishna Basak

    (Indian Statistical Institute, Kolkata)

  • Suchismita Das

    (S P Jain School of Global Management)

Abstract

This Paper proposes a Bayesian approach to find out the optimum stopping rule of software testing. We consider a discrete periodic debugging framework so that software can be released for market once the criteria are fulfilled. Simplification of stopping rules were obtained by using some specific prior distributions of the number of remaining bugs. We also develop necessary and sufficient conditions for stopping the software testing. Some illustrative examples are presented.

Suggested Citation

  • Ashis Kumar Chakraborty & Gopal Krishna Basak & Suchismita Das, 2019. "Bayesian optimum stopping rule for software release," OPSEARCH, Springer;Operational Research Society of India, vol. 56(1), pages 242-260, March.
    • Handle: RePEc:spr:opsear:v:56:y:2019:i:1:d:10.1007_s12597-018-00353-0
    DOI: 10.1007/s12597-018-00353-0
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    References listed on IDEAS

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    1. Anup Dewanji & Debasis Sengupta & Ashis Kumar Chakraborty, 2011. "A discrete time model for software reliability with application to a flight control software," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 27(6), pages 723-731, November.
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