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NHPP models for categorized software defects

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  • Zhaohui Liu
  • Nalini Ravishanker
  • Bonnie K. Ray

Abstract

We develop NHPP models to characterize categorized event data, with application to modelling the discovery process for categorized software defects. Conditioning on the total number of defects, multivariate models are proposed for modelling the defects by type. A latent vector autoregressive structure is used to characterize dependencies among the different types. We show how Bayesian inference can be achieved via MCMC procedures, with a posterior prediction‐based L‐measure used for model selection. The results are illustrated for defects of different types found during the System Test phase of a large operating system software development project. Copyright © 2005 John Wiley & Sons, Ltd.

Suggested Citation

  • Zhaohui Liu & Nalini Ravishanker & Bonnie K. Ray, 2005. "NHPP models for categorized software defects," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 21(6), pages 509-524, November.
    • Handle: RePEc:wly:apsmbi:v:21:y:2005:i:6:p:509-524
    DOI: 10.1002/asmb.604
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    1. Ravishanker, Nalini & Liu, Zhaohui & Ray, Bonnie K., 2008. "NHPP models with Markov switching for software reliability," Computational Statistics & Data Analysis, Elsevier, vol. 52(8), pages 3988-3999, April.

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