DocumentCode :
2663688
Title :
Exploratory failure analysis of open source software
Author :
Rahmani, Cobra ; Srinivasan, Satish M. ; Azadmanesh, Azad
Author_Institution :
Coll. of Inf. Sci. & Technol., Univ. of Nebraska-Omaha, Omaha, NE, USA
Volume :
1
fYear :
2010
fDate :
3-5 Oct. 2010
Abstract :
Reliability growth modeling in software system plays an important role in measuring and controlling software quality during software development. One main approach to reliability growth modeling is based on the statistical correlation of observed failure intensities versus estimated ones by the use of statistical models. Although there are a number of statistical models in the literature, this research concentrates on the following seven models: Weibull, Gamma, S-curve, Exponential, Lognormal, Cubic, and Schneidewind. The failure data collected are from five popular open source software (OSS) products. The objective is to determine which of the seven models best fits the failure data of the selected OSS products as well as predicting the future failure pattern based on partial failure history. The outcome reveals that the best model fitting the failure data is not necessarily the best predictor model.
Keywords :
Weibull distribution; exponential distribution; gamma distribution; program diagnostics; public domain software; quality control; software metrics; software quality; software reliability; S-curve model; Schneidewind model; Weibull model; cubic model; exploratory failure analysis; exponential model; gamma model; lognormal model; open source software; partial failure history; reliability growth modeling; software development; software quality control; software quality measurement; statistical correlation; Fires; Software; Software reliability; empirical software engineering; goodness-of-fit; open source software; software reliability growth modeling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Technology and Engineering (ICSTE), 2010 2nd International Conference on
Conference_Location :
San Juan, PR
Print_ISBN :
978-1-4244-8667-0
Electronic_ISBN :
978-1-4244-8666-3
Type :
conf
DOI :
10.1109/ICSTE.2010.5608887
Filename :
5608887
Link To Document :
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