Application of EM Algorithm to NHPP-Based Software Reliability Assessment with Generalized Failure Count Data

• Main Authors: Hiroyuki Okamura, Tadashi Dohi
• Format: Article
• Language: English
• Published: MDPI AG 2021-04-01
• Series: Mathematics
• Subjects: software reliability model; maximum likelihood estimation; EM algorithm; non- homogeneous Poisson process; generalized failure count data
• Online Access: https://www.mdpi.com/2227-7390/9/9/985
• ISSN: 2227-7390

Software reliability models (SRMs) are widely used for quantitative evaluation of software reliability by estimating model parameters from failure data observed in the testing phase. In particular, non-homogeneous Poisson process (NHPP)-based SRMs are the most popular because of their mathematical tractability. In this paper, we focus on the parameter estimation algorithm for NHPP-based SRMs and discuss the EM algorithm for generalized fault count data. The presented algorithm can be applied for failure time data, failure count data, and their mixture. The paper derives the EM-step formulas for basic 12 NHPP-based SRMs and demonstrate a numerical experiment to present the convergence property of our algorithms. The developed algorithms are suitable for an automatic tool for software reliability evaluation.