1. Predicting software reliability and quality using ant colony optimization technique with travelling salesman problem for software process
Authors : D. Hema Latha, Prof. P. Premchand
Pages : 174-178
DOI : http://dx.doi.org/10.21172/1.103.30
Keywords : : Software Reliability, Software Quality, Bio-inspired Computing, Ant Colony Optimization technique (ACO), Travelling Salesman Problem (TSP). Abstract :In the context of software engineering, software quality measures how good software is designed (quality of design), and how good the software conforms to that design (quality of conformance). Software quality is described as the ‘fitness for purpose’ of a piece of software. Software reliability is a failure free operation of software for a specific period of time under specified environment. Software reliability is defined as the probability with which the software will operate without any failure for a specific period of time in a specified environment. Software reliability and quality Software reliability and quality prediction is very challenging in starting phases of life cycle model. , Software reliability and quality, when estimated in early phases of software development life cycle, saves lot of money and time as it prevents spending huge amount of money on fixing of defects in the software after it has been deployed to the client. Prediction of Software reliability and quality has thus become an important research area as every organization works towards to produce reliable and good quality software and error or defect free software. There are many software quality and reliability growth models that are used to estimate or predict the reliability and quality of the software. These models help in developing robust and fault tolerant systems.In the past few years many software reliability models and quality models have been proposed for assessing reliability and quality for software, but developing accurate reliability and quality prediction models is difficult due to the recurrent or frequent changes in data in the domain of software engineering. As a result, the software reliability prediction models built on one dataset show a significant decrease in their accuracy when they are used with new data. The main objective of this paper is to introduce a model for predicting software reliability and quality with a new approach that optimizes the accuracy of software reliability and quality predictive models when used with real data. In this research paper, Ant Colony Optimization Technique (ACOT) with Travelling Salesman Problem (TSP) is proposed to predict software reliability and quality based on the data collected from literature. An ant colony system by combining with Travelling Sales Problem (TSP) algorithm has been used, which has been changed by implementing different algorithms and extra functionality, in an attempt to achieve better software reliability and quality results with new data for software process.
Citing this Journal Article :D. Hema Latha, Prof. P. Premchand, "Predicting software reliability and quality using ant colony optimization technique with travelling salesman problem for software process", Volume 10 Issue 3 - May 2018, 174-178
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