Critical fault-detecting time evaluation in software with discrete compound Poisson models

Min Hsiung Hsieh, Shuen Lin Jeng, Paul Kvam

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Software developers predict their product’s failure rate using reliability growth models that are typically based on nonhomogeneous Poisson (NHP) processes. In this article, we extend that practice to a nonhomogeneous discrete-compound Poisson process that allows for multiple faults of a system at the same time point. Along with traditional reliability metrics such as average number of failures in a time interval, we propose an alternative reliability index called critical fault-detecting time in order to provide more information for software managers making software quality evaluation and critical market policy decisions. We illustrate the significant potential for improved analysis using wireless failure data as well as simulated data.

Original languageEnglish
Pages (from-to)94-108
Number of pages15
JournalJournal of Quality Technology
Issue number1
Publication statusPublished - 2019 Jan 1

All Science Journal Classification (ASJC) codes

  • Safety, Risk, Reliability and Quality
  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering


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