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Testing effort dependent software reliability model for imperfect debugging process considering both detection and correction

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  • Peng, R.
  • Li, Y.F.
  • Zhang, W.J.
  • Hu, Q.P.

Abstract

This paper studies the fault detection process (FDP) and fault correction process (FCP) with the incorporation of testing effort function and imperfect debugging. In order to ensure high reliability, it is essential for software to undergo a testing phase, during which faults can be detected and corrected by debuggers. The testing resource allocation during this phase, which is usually depicted by the testing effort function, considerably influences not only the fault detection rate but also the time to correct a detected fault. In addition, testing is usually far from perfect such that new faults may be introduced. In this paper, we first show how to incorporate testing effort function and fault introduction into FDP and then develop FCP as delayed FDP with a correction effort. Various specific paired FDP and FCP models are obtained based on different assumptions of fault introduction and correction effort. An illustrative example is presented. The optimal release policy under different criteria is also discussed.

Suggested Citation

  • Peng, R. & Li, Y.F. & Zhang, W.J. & Hu, Q.P., 2014. "Testing effort dependent software reliability model for imperfect debugging process considering both detection and correction," Reliability Engineering and System Safety, Elsevier, vol. 126(C), pages 37-43.
    • Handle: RePEc:eee:reensy:v:126:y:2014:i:c:p:37-43
    DOI: 10.1016/j.ress.2014.01.004
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    References listed on IDEAS

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    Cited by:

    1. Byun, Ji-Eun & Noh, Hee-Min & Song, Junho, 2017. "Reliability growth analysis of k-out-of-N systems using matrix-based system reliability method," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 410-421.
    2. Qing Tian & Chun-Wu Yeh & Chih-Chiang Fang, 2022. "Bayesian Decision Making of an Imperfect Debugging Software Reliability Growth Model with Consideration of Debuggers’ Learning and Negligence Factors," Mathematics, MDPI, vol. 10(10), pages 1-21, May.
    3. Nguyen, Khanh T.P. & Fouladirad, Mitra & Grall, Antoine, 2018. "Model selection for degradation modeling and prognosis with health monitoring data," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 105-116.
    4. Anshul Tickoo & P. K. Kapur & A. K. Shrivastava & Sunil K. Khatri, 2016. "Testing effort based modeling to determine optimal release and patching time of software," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 7(4), pages 427-434, December.
    5. Qing Tian & Chih-Chiang Fang & Chun-Wu Yeh, 2022. "Software Release Assessment under Multiple Alternatives with Consideration of Debuggers’ Learning Rate and Imperfect Debugging Environment," Mathematics, MDPI, vol. 10(10), pages 1-24, May.
    6. Vishal Pradhan & Ajay Kumar & Joydip Dhar, 2022. "Modelling software reliability growth through generalized inflection S-shaped fault reduction factor and optimal release time," Journal of Risk and Reliability, , vol. 236(1), pages 18-36, February.
    7. Chetna Choudhary & P. K. Kapur & Sunil K. Khatri & R. Muthukumar & Avinash K. Shrivastava, 2020. "Effort based release time of software for detection and correction processes using MAUT," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(2), pages 367-378, July.
    8. Mohammad Ubaidullah Bokhari & Md. Ashraf Siddiqui & Afaq Ahmad, 2021. "Integration of Testing Effort Function into Delayed S-Shaped Software Reliability Growth Model with Imperfect Debugging — a Proposed Bokhari Model," SN Operations Research Forum, Springer, vol. 2(4), pages 1-23, December.
    9. Hiroyuki Okamura & Tadashi Dohi, 2016. "Phase-type software reliability model: parameter estimation algorithms with grouped data," Annals of Operations Research, Springer, vol. 244(1), pages 177-208, September.
    10. Wang, Jinyong & Wu, Zhibo, 2016. "Study of the nonlinear imperfect software debugging model," Reliability Engineering and System Safety, Elsevier, vol. 153(C), pages 180-192.

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