Paper Info
Title
Software Belief Reliability Growth Model Based on Uncertain Differential Equation
Abstract
Software reliability plays an important role in modern society. To evaluate software reliability, software reliability growth models (SRGMs) investigate the number of software faults in the testing phase. Obviously, testing progresses are inevitably influenced by dynamic indeterministic fluctuations such as the testing effort expenditure, testing efficiency and skill, testing method, and strategy. To model these dynamic fluctuations, several probability theory-based SRGMs are proposed. However, probability theory is suitable for dealing with aleatory uncertainty, but fails to deal with epistemic uncertainty widely existing in software faults. Therefore, this article considers software reliability from a new perspective under the framework of uncertainty theory, which is a new mathematical system different from probability theory, and proposes a software belief reliability growth model (SBRGM) based on uncertain differential equations for the first time. Based on this SBRGM, properties of essential software reliability metrics are investigated under belief reliability theory, which is a brand-new reliability theory. Parameter estimations for unknown parameters in SBRGM are presented. Furthermore, some numerical examples and real data analyses illustrate our methodology in detail, and show that it performs better than several famous probability-based SRGMs in terms of fitting ability and prediction ability. Finally, an optimal software release policy is discussed.
Year
DOI
Venue
2022
10.1109/TR.2022.3154770
IEEE Transactions on Reliability
Keywords
DocType
Volume
Belief reliability,software belief reliability growth model,software reliability,uncertain differential equation,uncertainty theory
Journal
71
Issue
ISSN
Citations 
2
0018-9529
1
PageRank 
References 
Authors
0.35
21
4
Name
Order
Citations
PageRank
Zhe Liu112.72
Shunkun Yang23112.25
Minghao Yang311.37
Rui Kang416528.97