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Joint optimization of software time-to-market and testing duration using multi-attribute utility theory

Author

Listed:
  • P. K. Kapur

    (Amity University)

  • Saurabh Panwar

    (University of Delhi)

  • Ompal Singh

    (University of Delhi)

  • Vivek Kumar

    (University of Delhi)

Abstract

An optimal software release strategy is a well-investigated issue in software reliability literature. Comprehensive testing is expected before releasing the software into the market to enhance the reliability and security of the software device. In recent years, few analysts have recommended the scheme for software projects that support releasing the software early in the market and continue the testing process for an added period in the field environment even after the software is distributed. These studies are based on one common assumption that the efficiency of the software engineers in detecting the faults occurs at a consistent rate throughout the testing phase. However, bug-identification rate may experience discontinuity at the software release time. In software engineering, the time-point at which fault detection rate changes is termed as change-point. Consequently, an alternative software release policy is proposed in the present paper, which offers a generalized framework for fault detection phenomenon using the unified approach. An extensive analysis of software time-to-market and testing duration based on cost-efficiency and reliability measures is discussed by considering the change in tester’s fault detection rate. A multi-criteria decision making technique known as multi-attribute utility theory is applied to optimize the software release policy under field-testing (FT) and no field-testing (NFT) frameworks. The relevance of the optimization problem is illustrated using a numerical example, comprising both the exponential and S-shaped bug-detection process.

Suggested Citation

  • P. K. Kapur & Saurabh Panwar & Ompal Singh & Vivek Kumar, 2022. "Joint optimization of software time-to-market and testing duration using multi-attribute utility theory," Annals of Operations Research, Springer, vol. 312(1), pages 305-332, May.
    • Handle: RePEc:spr:annopr:v:312:y:2022:i:1:d:10.1007_s10479-019-03483-w
    DOI: 10.1007/s10479-019-03483-w
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    References listed on IDEAS

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