Computer Science

Computer Science ›› 2025, Vol. 52 ›› Issue (9): 360-367.doi: 10.11896/jsjkx.240600086

• Computer Software • Previous Articles     Next Articles

Bayesian Verification Scheme for Software Reliability Based on Staged Growth Test Information

WANG Yuzhuo1,2, LIU Haitao1, YUAN Haojie1, ZHAI Yali1, ZHANG Zhihua3   

  1. 1 Department of Foundation,Naval University of Engineering,Wuhan 430033,China
    2 College of Weaponry Engineering,Naval University of Engineering,Wuhan 430033,China
    3 College of Naval Architecture and Ocean Engineering,Naval University of Engineering,Wuhan 430033,China
  • Received:2024-06-13 Revised:2024-10-16 Online:2025-09-15 Published:2025-09-11
  • About author:WANG Yuzhuo,born in 1984,Ph.D,associate professor.Her main research interest is software reliability evaluation.
    LIU Haitao,born in 1982,Ph.D,professor.His main research interest is reliability theory and application.

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Abstract: The prior distribution determination methods of existing Bayesian schemes are relatively conservative and ideal for processing software reliability phased growth testing information.In this article,an edge distribution model for the software success probability at the final stage of growth testing is constructed using the identity relationship between the regular incomplete beta function and the cumulative sum of binomial distributions.On this basis,a prior distribution determination method of software success probability under sequential constraints is proposed,and a Bayesian verification scheme based on average a posteriori risk is designed to protect the interests of users.The example and simulation show that the proposed prior distribution determination method is more reasonable for processing software reliability phased growth information,the designed Bayesian scheme can significantly reduce the number of reliability verification test cases and reduce testing burden while ensuring the reliability of the schemes and has certain economic value.

Key words: Software reliability verification, Reliability growth testing, Software success rate

CLC Number: 

  • E917
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