Title: Improvement of component selection process using Genetic Algorithm for Component-Based Software Development

Authors: K. Vijayalakshmi, N. Ramaraj, R. Amuthakkannan

Addresses: Department of Computer Science and Engineering, Dr Mahalingam College of Engineering and Technology, Pollachi 642 003, Tamil Nadu, India. ' GKM College of Engineering and Technology, Chennai 600 063, Tamil Nadu, India. ' Mechatronics and Virtual Instrumentation Research Cell, Department of Mechanical Engineering, Coimbatore Institute of Technology, Coimbatore 641 014, Tamil Nadu, India

Abstract: Modern information systems are becoming more expensive to build and maintain. Software development management and software quality goals are necessary, but not sufficient for the needs of today|s marketplace. Shorter cycle time, completed with fewer resources is also in demand. Therefore, organisations are turning to Component-Based Software Development (CBSD). Potentially, CBSD can be used to reduce software development time by bringing the system to markets as early as possible. CBSD process consists of four major processes: component qualification, component adaptation, component composition and component update. To realise the benefits which CBS brings it is imperative that the right software component is selected for a project, because selecting inappropriate component may results in increased time and cost of software development which CBSD aims at reducing. Component selection is a major challenge to CBS developers, due to the multiplicity of similar components on the market with varying capabilities. Although several approaches and criteria have been proposed for component selection, there is no well-defined procedure to select optimised components. In this article, an automated approach is proposed based on Genetic Algorithm that enables the selection of software components both considering functional and non-functional requirements to find the best combination of components.

Keywords: component-based software development; CBSD; component selection; genetic algorithms; GAs; software quality; information systems.

DOI: 10.1504/IJISCM.2008.019289

International Journal of Information Systems and Change Management, 2008 Vol.3 No.1, pp.63 - 80

Published online: 06 Jul 2008 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article