A survey of computational intelligence approaches for software reliability prediction

Abstract

Computational Intelligence has been known to be very useful in predicting software reliability. In this paper, two kinds of investigations are performed. First, we provide a systematic review of Software Reliability Prediction studies with consideration of various metrics, methods and CI techniques (including fuzzy logic, neural networks, genetic algorithms). Second, reliability prediction and data collection with the help of various available tools are discussed. 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.

Efficient effort estimation of web based projects using neuro-web

“…medicine, geology, engineering, image processing, physics, classification and control problems), It grabs the attention of more researchers to use this for software effort estimation and many researchers used this in different areas of software project management. Tronto et al (2008) and Bhuyan et al (2014) evaluated the use of artificial neural networks as prediction of cost and effort in software project management. Furthermore, Finnie et al (1997) reported that back propagation learning algorithm on multilayer perceptron for software effort prediction.…”

Software Reliability Assesment using Neural Networks of Computational Intelligence Based on Software Failure Data

“…The learning rule applied in this model is parameter learning (Lin and Lee, 1996). The layer that receives input is called the input layer and typically performs no function other than buffering the input signal (Bhuyan et al, 2014). The input layer is not used for computation, so each node of input layer transmits input values to the hidden layer directly.…”

“…Also it is a difficult task for software companies to deliver good quality software in appropriate time (Bhuyan et al, 2014). The last two decades have witnessed a paradigm shift in the field of software engineering (Benala, 2012).…”

Software Reliability Prediction using Fuzzy Min-Max Algorithm and Recurrent Neural Network Approach

“…As per IEEE Standard Glossary of Software Engineering, a definition of software reliability is the probability of the failure free operation of a computer program for a specified period of time in a specified environment [1,2,3,4]. Computational Intelligence (CI) can offer promising approaches to software reliability prediction and modeling, because they require only failure history as input without any assumption [5].…”