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On optimality of one‐bug‐look‐ahead policies for a software testing model

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  • Xiaoyue Jiang
  • Donglei Du
  • Thomas G. Ray

Abstract

The optimality of the One‐Bug‐Look‐Ahead (OLA) software release policy proposed by Morali and Soyer (Nav Res Logist 50 (2003), 88–104) is re‐examined in this paper. A counterexample is constructed to show that OLA is not optimal in general. The optimal stopping approach is then called upon to prove that OLA possesses weaker sense of optimality under conditional monotonicity and the strong sense of optimality holds under a more restrictive sample‐wise monotonicity condition. The NTDS data are analyzed for illustration, and OLA is shown to be robust with respect to model parameters. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007.

Suggested Citation

  • Xiaoyue Jiang & Donglei Du & Thomas G. Ray, 2007. "On optimality of one‐bug‐look‐ahead policies for a software testing model," Naval Research Logistics (NRL), John Wiley & Sons, vol. 54(3), pages 346-355, April.
  • Handle: RePEc:wly:navres:v:54:y:2007:i:3:p:346-355
    DOI: 10.1002/nav.20194
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    References listed on IDEAS

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    1. Nilgun Morali & Refik Soyer, 2003. "Optimal stopping in software testing," Naval Research Logistics (NRL), John Wiley & Sons, vol. 50(1), pages 88-104, February.
    2. Pham, Hoang & Zhang, Xuemei, 2003. "NHPP software reliability and cost models with testing coverage," European Journal of Operational Research, Elsevier, vol. 145(2), pages 443-454, March.
    3. Uwe Jensen & Guang-Hui Hsu, 1993. "Optimal Stopping by Means of Point Process Observations with Applications in Reliability," Mathematics of Operations Research, INFORMS, vol. 18(3), pages 645-657, August.
    4. Pham, Hoang, 2003. "Software reliability and cost models: Perspectives, comparison, and practice," European Journal of Operational Research, Elsevier, vol. 149(3), pages 475-489, September.
    5. V. Makis & X. Jiang & K. Cheng, 2000. "Optimal Preventive Replacement Under Minimal Repair and Random Repair Cost," Mathematics of Operations Research, INFORMS, vol. 25(1), pages 141-156, February.
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