Software Reliability Modeling using Soft Computing Techniques: Critical Review
TL;DR: An overview of existing soft computing techniques, and critically analyzed the work done by the various researchers in the field of software reliability modeling capabilities is provided.
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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
Predicting software bugs of newly and large datasets through a unified neuro-fuzzy approach: reliability perspective
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- 22 Jan 2021
TL;DR: The proposed methods of prediction would be useful for practitioners to simplify the procedures during software development in large datasets for reducing failures of software.
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Ranking of software engineering metrics by fuzzy‐based matrix methodology
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A comparative study of statistical and soft computing techniques for reliability prediction of automotive manufacturing
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TL;DR: The analysis of the study shows that artificial neural network provides better results compared to Fuzzy Inference System; but applicability of best approach depends on the data availability and the quantum of data.
A survey of computational intelligence approaches for software reliability prediction
TL;DR: The overall idea of this paper is to present, analyze, investigate, compare and discuss software reliability prediction with various CI techniques and tools and their advantages and disadvantages.
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