We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
A software reliability model with time-dependent fault detection and fault removal.
- Authors
Zhu, Mengmeng; Pham, Hoang
- Abstract
The common assumption for most existingsoftware reliability growth models is that fault is independent and can be removed perfectly upon detection. However, it is often not true due to various factors including software complexity, programmer proficiency, organization hierarchy, etc. In this paper, we develop a software reliability model with considerations of fault-dependent detection, imperfect fault removal and the maximum number of faults software. The genetic algorithm (GA) method is applied to estimate the model parameters. Four goodness-of-fit criteria, such as mean-squared error, predictive-ratio risk, predictive power, and Akaike information criterion, are used to compare the proposed model and several existing software reliability models. Three datasets collected in industries are used to demonstrate the better fit of the proposed model than other existing software reliability models based on the studied criteria.
- Subjects
SOFTWARE reliability; RELIABILITY in engineering; COMPUTER reliability; COMPUTER performance; TIME series analysis; FAULT-tolerant computing
- Publication
Vietnam Journal of Computer Science (Springer Nature), 2016, Vol 3, Issue 2, p71
- ISSN
2196-8888
- Publication type
Article
- DOI
10.1007/s40595-016-0058-0