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Software Reliability Modeled on Contagion

Authors: Néstor Ruben Barraza;

Software Reliability Modeled on Contagion

Abstract

A new software reliability model based on the Polya contagion stochastic process is proposed. We model the failure detection process as a pure birth process with a failure rate that depends not just on time but on the number of failures previously detected, as it happens in the Polya process obtained as the asymptotic limit of the Polya urn model for contagion. Since the contagion proposes an increasing failure (birth) rate, this model is suitable to be applied at the beginning of the testing process or when some code has been added to the project, situations where the S-shaped model is usually used. The result of applying our model to real data is also shown.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Average
Top 10%
Top 10%
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