Predicting Software Reliability using Artificial Neural Networks: A Review

Authors

  • Jasira Ali
  • Sheikh Riyaz-ul-Haq

DOI:

https://doi.org/10.37591/josettt.v6i2.2115

Abstract

Abstract

Software reliability has become a major concern for all the software systems. Predicting software reliability has become a major challenge for both the software developers and the engineers. Before the software is dispensed to the market/customers, it is thoroughly checked for any errors and if errors are there, they are thereby removed. For the purpose of reliability estimation certain mathematical software reliability models have been proposed for estimating the reliability of the software during the development process of the software. Over recent years, many of the software reliability models have been proposed and utilized for the purpose of reliability prediction and estimation; however, no single model provided the accurate results for all the cases. In this paper, the use of artificial neural network model for reliability estimation is explored.

 

Keywords: Software Reliability, Software Reliability Growth models, Artificial Neural Networks, Back-Propagation algorithm

 

Cite this Article

Jasira Ali, Sheikh Riyaz-ul-Haq. Predicting Software Reliability using Artificial Neural Networks: A Review. Journal of Software Engineering Tools & Technology Trends. 2019; 6(2): 14–19p.

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Published

2019-09-07

Issue

Vol. 6 No. 2 (2019)

Section

Research Articles

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