DocumentCode
2905824
Title
Estimating Markov Modulated Software Reliability Models via EM Algorithm
Author
Ando, Takao ; Okamura, Hiroyuki ; Dohi, Tadashi
Author_Institution
Dept. of Inf. Eng., Hiroshima Univ.
fYear
2006
fDate
Sept. 29 2006-Oct. 1 2006
Firstpage
111
Lastpage
118
Abstract
In this paper, we develop a parameter estimation method to Markovian software reliability models. When software fault-detection rates change in the software testing phase, fault-detection processes can be generally modeled by Markov modulated processes. This paper deals with a unified parameter estimation method for Markov modulated software reliability models as well as the typical pure birth process models. In numerical examples, we evaluate a goodness-of-fit for the Markov modulated software reliability models with real fault data, and show numerically that the Markov modulated software reliability models are superior to the existing pure birth process models in the viewpoint of information criterion
Keywords
Markov processes; expectation-maximisation algorithm; parameter estimation; program testing; software reliability; EM algorithm; Markov modulated software reliability; parameter estimation; software fault detection; software testing; Bayesian methods; Fault detection; Parameter estimation; Phase modulation; Reliability engineering; Software algorithms; Software debugging; Software reliability; Software testing; Stochastic processes; EM algorithm; Information criterion; Markov modulated; Software reliability models; processes;
fLanguage
English
Publisher
ieee
Conference_Titel
Dependable, Autonomic and Secure Computing, 2nd IEEE International Symposium on
Conference_Location
Indianapolis, IN
Print_ISBN
0-7695-2539-3
Type
conf
DOI
10.1109/DASC.2006.29
Filename
4030873
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