Role of Swarm Intelligence based Algorithms and their Applications for optimization in Software Reliability
Narender1, Sona Malhotra2 

1Narender, Ph. D Scholar, Department of Computer Engineering, Kurukshetra University/ UIET, Kurukshetra, Haryana, India.
2Sona Malhotra, Assistant Professor, Department of Computer Engineering, Kurukshetra University/ UIET, Kurukshetra, Haryana, India.

Manuscript received on 03 March 2019 | Revised Manuscript received on 09 March 2019 | Manuscript published on 30 July 2019 | PP: 3323-3327 | Volume-8 Issue-2, July 2019 | Retrieval Number: B2953078219/19©BEIESP | DOI: 10.35940/ijrte.B2953.078219
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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.
Index Terms: ABC, ACO, Bat, Fish, PSO, Software Reliability Optimization, Swarm Intelligence.

Scope of the Article: Discrete Optimization