Role of swarm intelligence based algorithms and their applications for optimization in software reliability

0Citations
Citations of this article
8Readers
Mendeley users who have this article in their library.
Get full text

Abstract

The software has many features like functionality, maintainability, serviceability, usability, quality, performance. The reliability of the software is an imperative characteristic of software that leads to the eminence of the software. Software reliability is a great concern for software producers as well as users of the software. Keeping this concern in mind, there are already hundreds of software reliability models developed in the last four decades. This paper evaluates different algorithms based on Swarm intelligence in the way of optimization in software reliability. There are a number of swarm intelligence based algorithms that already have been used to improve the efficiency of the reliability of the software. Some of them are ant colony optimizer method (ACO), particle swarm optimizer method (PSO), artificial bee colony optimizer (ABC), bat algorithm, fish swarm algorithm, cuckoo search, bird flock algorithm. Still, there are so many algorithms based on Swarm intelligence that has not been used in this area. This paper investigates some known swarm intelligence based algorithms and their applications for optimizing software reliability.

Cite

CITATION STYLE

APA

Narender, & Malhotra, S. (2019). Role of swarm intelligence based algorithms and their applications for optimization in software reliability. International Journal of Recent Technology and Engineering, 8(2), 3323–3327. https://doi.org/10.35940/ijrte.B2953.078219

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free