Software reliability prediction and optimization using machine learning algorithms: A review

Authors

  • Neha Yadav KIET Group of Institutions, Ghaziabad
  • Vibhash Yadav Rajkiya Engineering College, Banda

Keywords:

Software Reliability, Quality, Intelligent Prediction, Machine Learning

Abstract

Software reliability is an important part while evaluating software quality. Many challenges are faced while developing highly reliable software such as its usability, performance, service, and maintenance, etc. Prediction and optimization of reliability estimation procedure is performed by optimizing parameters of the model. Several traditional models are existing to evaluate the reliability of the model, but it is quite difficult to directly estimate optimal parameters. Therefore, researchers adopted intelligent prediction and optimization algorithms for software reliability check. But still there a lot of limitations that needed to be focused and solved. In this paper, a detailed study is presented for software reliability prediction using machine learning. The paper also presents an analytical analysis for software reliability prediction.

URN:NBN:sciencein.jist.2023.v11.457

Downloads

Download data is not yet available.
 Software Reliability Prediction

Downloads

Published

2022-12-01

Issue

Section

Computer Sciences and Mathematics

URN

How to Cite

Software reliability prediction and optimization using machine learning algorithms: A review. (2022). Journal of Integrated Science and Technology, 11(1), 457. https://pubs.thesciencein.org/journal/index.php/jist/article/view/457

Similar Articles

1-10 of 86

You may also start an advanced similarity search for this article.