New interval Bayesian models for software reliability based on non-homogeneous Poisson processes

  • Authors:

  • L. V. Utkin;S. I. Zatenko;F. P. Coolen

  • Affiliations:

  • Saint-Petersburg State Forest-Technical Academy, St. Petersburg, Russia;Saint-Petersburg State Forest-Technical Academy, St. Petersburg, Russia;Durham University, Durham, UK

  • Venue:
  • Automation and Remote Control
  • Year:
  • 2010

Quantified Score

Hi-index 0.00

Visualization

Abstract

We propose a new class of models for software reliability based on known models employing non-homogeneous Poisson processes, e.g., Musa-Okomoto and Goel-Okomoto models. We show that the general idea of model design is in a combined application of imprecise Bayesian inference and the maximum likelihood approach. We show examples where proposed models show better reliability prediction quality compared to the known ones.