Resumen de A Bayesian Analysis of Beta Testing
Simon P. Wilson, Michael Peter Wiper
In this article, we define a model for fault detection during the beta testing phase of a software design project. Given sampled data, we illustrate how to estimate the failure rate and the number of faults in the software using Bayesian statistical methods with various different prior distributions. Secondly, given a suitable cost function, we also show how to optimize the duration of a further test period for each one of the prior distribution structures considered.
