research-article

Measuring software reliability: a fuzzy model

Authors:

Ravinder Kumar,

Arvind KaliaAuthors Info & Claims

ACM SIGSOFT Software Engineering Notes, Volume 36, Issue 6

Pages 1 - 6

https://doi.org/10.1145/2047414.2047425

Published: 14 November 2011 Publication History

Abstract

Software reliability is an essential part of software engineering to ensure the quality of a system. There are various techniques, which can be used in building models for predicting quality attributes. This paper presents a Fuzzy model for software reliability prediction. We have proposed three parameters Availability, Failure Probability and Recoverability as an integrated measure of software reliability. Fuzzy Model provides a way to arrive at a discrete Reliability Non-functional requirement (NFR) in contrast to imprecise, vague and ambiguous. This model will help us to evolve intermediate stages between reliable state and unreliable state of a system. Results obtained by proposed model show that this is suitable for predicting software reliability of the software.

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Cited By

Samal UKushwaha SNain GSingh SUsmani SKumar A(2025)Necessity of fuzzy logic: Trends in software reliability assessmentReliability Assessment and Optimization of Complex Systems10.1016/B978-0-443-29112-8.00009-8(275-285)Online publication date: 2025
https://doi.org/10.1016/B978-0-443-29112-8.00009-8
Mishra ANagpal RSeth KSehgal R(2022)Analyzability of SOA using Soft Computing Technique2022 10th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)10.1109/ICRITO56286.2022.9964602(1-5)Online publication date: 13-Oct-2022
https://doi.org/10.1109/ICRITO56286.2022.9964602
Markov ABarabanov ATsirlov V(2018)Models for Testing Modifiable SystemsProbabilistic Modeling in System Engineering10.5772/intechopen.75126Online publication date: 26-Sep-2018
https://doi.org/10.5772/intechopen.75126
Show More Cited By

Index Terms

Measuring software reliability: a fuzzy model
1. General and reference
  1. Cross-computing tools and techniques
    1. Metrics

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Published In

cover image ACM SIGSOFT Software Engineering Notes

ACM SIGSOFT Software Engineering Notes Volume 36, Issue 6

November 2011

117 pages

ISSN:0163-5948

DOI:10.1145/2047414

Issue’s Table of Contents

Copyright © 2011 Authors.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 14 November 2011

Published in SIGSOFT Volume 36, Issue 6

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Cited By

Samal UKushwaha SNain GSingh SUsmani SKumar A(2025)Necessity of fuzzy logic: Trends in software reliability assessmentReliability Assessment and Optimization of Complex Systems10.1016/B978-0-443-29112-8.00009-8(275-285)Online publication date: 2025
https://doi.org/10.1016/B978-0-443-29112-8.00009-8
Mishra ANagpal RSeth KSehgal R(2022)Analyzability of SOA using Soft Computing Technique2022 10th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)10.1109/ICRITO56286.2022.9964602(1-5)Online publication date: 13-Oct-2022
https://doi.org/10.1109/ICRITO56286.2022.9964602
Markov ABarabanov ATsirlov V(2018)Models for Testing Modifiable SystemsProbabilistic Modeling in System Engineering10.5772/intechopen.75126Online publication date: 26-Sep-2018
https://doi.org/10.5772/intechopen.75126
Kumar ATadayoni RSorensen L(2015)Metric based efficiency analysis of educational ERP system usability-using fuzzy modelProceedings of the 2015 Third International Conference on Image Information Processing (ICIIP)10.1109/ICIIP.2015.7414801(382-386)Online publication date: 21-Dec-2015
https://dl.acm.org/doi/10.1109/ICIIP.2015.7414801
Georgieva O(2013)Dynamic Data-Driven Fuzzy Modeling of Software Reliability GrowthTowards Advanced Data Analysis by Combining Soft Computing and Statistics10.1007/978-3-642-30278-7_19(241-252)Online publication date: 2013
https://doi.org/10.1007/978-3-642-30278-7_19

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