Software release optimization for a non-kalman filter SRGM

Author

Jiang, X. ; Du, D. ; Ray, T.G. ; Ghazavi, S.N.

Author_Institution

Louisiana State Univ., Baton Rouge

fYear

2007

fDate

2-4 Dec. 2007

Firstpage

1181

Lastpage

1185

Abstract

The optimality of the one-bug-look-ahead (OLA) software release policy proposed in Morali, N. and Soyer, R. (2003) for a non- Kalman filter type of software reliability growth model (SRGM) is disproved in Jiang, X., et al., (2007). The remaining question - what is the optimal policy - is answered in this paper. It turns out that the optimal policy has a control-limit structure similar to OLA, but is not as impatient. A key step in the research is the identification of a Markov structure implied in the Bayesian updating mechanism which in turn reduces the optimal stopping formulation to an easily solvable Markov decision problem. A numerical example based on the NTDS data is included for illustration.

Keywords

Bayes methods; Markov processes; program debugging; program testing; software reliability; Bayesian updating mechanism; Markov decision problem; Markov structure; NTDS data; control-limit structure; nonKalman filter SRGM; one-bug-look-ahead software release policy; optimal policy; software release optimization; software reliability growth model; Bayesian methods; Educational institutions; Exponential distribution; Filters; History; Optimal control; Random variables; Reliability engineering; Software reliability; Software testing; Bayesian inference; Markov decision process; optimal release; software reliability;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Engineering and Engineering Management, 2007 IEEE International Conference on

Conference_Location

Singapore

Print_ISBN

978-1-4244-1529-8

Electronic_ISBN

978-1-4244-1529-8

Type

conf

DOI

10.1109/IEEM.2007.4419378

Filename

4419378