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

Min Hsiung Hsieh, Shuen-Lin Jeng, Paul Kvam

Research output: Contribution to journalArticle

Abstract

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
Volume51
Issue number1
DOIs
Publication statusPublished - 2019 Jan 1

Fingerprint

Managers
Software
Evaluation
Compound Poisson model
Fault
Poisson process
Quality evaluation
Failure rate
Compound Poisson process
Software quality
Developer
Growth model

All Science Journal Classification (ASJC) codes

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

Cite this

@article{541bdc4de7924e7fb3f5be1d1e2f6857,
title = "Critical fault-detecting time evaluation in software with discrete compound Poisson models",
abstract = "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.",
author = "Hsieh, {Min Hsiung} and Shuen-Lin Jeng and Paul Kvam",
year = "2019",
month = "1",
day = "1",
doi = "10.1080/00224065.2018.1545494",
language = "English",
volume = "51",
pages = "94--108",
journal = "Journal of Quality Technology",
issn = "0022-4065",
publisher = "American Society for Quality",
number = "1",

}

Critical fault-detecting time evaluation in software with discrete compound Poisson models. / Hsieh, Min Hsiung; Jeng, Shuen-Lin; Kvam, Paul.

In: Journal of Quality Technology, Vol. 51, No. 1, 01.01.2019, p. 94-108.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Critical fault-detecting time evaluation in software with discrete compound Poisson models

AU - Hsieh, Min Hsiung

AU - Jeng, Shuen-Lin

AU - Kvam, Paul

PY - 2019/1/1

Y1 - 2019/1/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85061209423&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85061209423&partnerID=8YFLogxK

U2 - 10.1080/00224065.2018.1545494

DO - 10.1080/00224065.2018.1545494

M3 - Article

AN - SCOPUS:85061209423

VL - 51

SP - 94

EP - 108

JO - Journal of Quality Technology

JF - Journal of Quality Technology

SN - 0022-4065

IS - 1

ER -