Journal Article10.4172/2165-7866.1000144
Software Reliability Modeling using Soft Computing Techniques: Critical Review
TL;DR: This paper has provided an overview of existing soft computing techniques, and then critically analyzed the work done by the various researchers in the field of software reliability.
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Abstract: To obtained solutions to problems quickly, accurately and acceptably, a large number of soft computing techniques have been developed, but it is very difficult to find out which one is the most suitable and can be used globally. In this paper, we have provided an overview of existing soft computing techniques, and then critically analyzed the work done by the various researchers in the field of software reliability. The probability of failure-free operation of a software system for a specified time in a specifies environment. Further to this, we have also compared soft computing techniques in terms of software reliability modeling capabilities.
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Citations
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Soft Computing Techniques for Dependable Cyber-Physical Systems
Muhammad Atif,Siddique Latif,Rizwan Ahmad,Adnan K. Kiani,Junaid Qadir,Adeel Baig,Hisao Ishibuchi,Waseem Abbas +7 more
TL;DR: This paper provides an overview of CPS applications, explores the foundations of dependability engineering, and highlights the potential role of soft computing techniques for CPS dependability with various case studies while also identifying common pitfalls and future directions.
11
The Use of Original and Hybrid Grey Wolf Optimizer in Estimating the Parameters of Software Reliability Growth Models
TL;DR: The hybrid GWO was hybrid with Real Coded Genetic Algorithm (RGA) to obtain Hybrid GWO (HGWO) and the results showed that the hybrid algorithm outperformed the original one.
Software Reliability Assesment using Neural Networks of Computational Intelligence Based on Software Failure Data
Manmath Kumar Bhuyan,Durga Prasad Mohapatra,Srinivas Sethi +2 more
- 19 Dec 2016
TL;DR: Feed Forward Back-Propagation Network (FFBPN) model is proposed as a model to predict software reliability and is applied on data sets collected across several standard software projects during system testing phase with fault removal.
Software reliability modeling using increased failure interval with ANN
K. Kumaresan,P. Ganeshkumar +1 more
TL;DR: The proposed software reliability model with the increased number of training data set and neural networks increases the accuracy of the software reliability prediction.
10
Fault-Tolerant Multiprocessor Systems Reliability Estimation Using Statistical Experiments with GL-Models
Alexei Romankevich,Andrii Feseniuk,Ivan Maidaniuk,Vitaliy Romankevich +3 more
- 18 Jan 2018
TL;DR: The article addresses the statistical estimation error (Monte-Carlo Error) and it is shown that the error could be estimated more precisely using the results of conducted statistical experiments and the upper bound for calculating the error before conducting statistical experiments is suggested.
9
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