The Transactions of the Korea Information Processing Society (한국정보처리학회논문지)

Korea Information Processing Society (한국정보처리학회)
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Bayesian Analysis of Software Reliability Growth Model with Negative Binomial Information

음이항분포 정보를 가진 베이지안 소프트웨어 신뢰도 성장모형에 관한 연구

  • 김희철 (송호대학 정보산업계열) ;
  • 박종구 (원광대학교 컴퓨터공학과) ;
  • 이병수 (시립인천대학교 컴퓨터정보통신학부)
  • Published : 2000.03.01
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Abstract

Software reliability growth models are used in testing stages of software development to model the error content and time intervals betwewn software failures. In this paper, using priors for the number of fault with the negative binomial distribution nd the error rate with gamma distribution, Bayesian inference and model selection method for Jelinski-Moranda and Goel-Okumoto and Schick-Wolverton models in software reliability. For model selection, we explored the sum of the relative error, Braun statistic and median variation. In Bayesian computation process, we could avoid the multiple integration by the use of Gibbs sampling, which is a kind of Markov Chain Monte Carolo method to compute the posterior distribution. Using simulated data, Bayesian inference and model selection is studied.

Keywords

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