文章基本信息

标题：Software Reliability Estimation using Artificial Neural Networks
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作者：Parveen Sehgal ; Meenal
期刊名称：International Journal of Research in Management, Science & Technology
印刷版ISSN：2321-3264
出版年度：2016
卷号：4
期号：2
出版社：Prannath Parnami Institute of Management & Technology, Hisar
摘要：In today’s world need for reliability estimation of software is increasing and hence leading to the development of new sophisticated techniques, which in turn can be used for construction of new models for predicting reliability attributes based on some predictor inputs. Our objective in this communication is to provide a framework, which is expected to be more effective and acceptable for predicting the reliability in multiple phases across software development lifecycle and the proposed framework is based on the use of artificial neural networks for predicting software reliability based upon historical datasets. Several software estimation models have already been developed over the past few years, but providing accurate estimates of the software projects is still a challenging job and therefore many researchers have been working on the development of new models and improvement of the existing ones including artificial intelligence based techniques. In this paper, we present a study of techniques based on ANNs and comparing the results and performance analysis of different ANNs methods in reliability estimation.
关键词：Artificial neural networks; error back propagation; gradient based algorithms; reliability estimation; software matrices; supervised learning