Title: Optimal test sequence generation: an approach using ant colony optimisation

Authors: Praveen Ranjan Srivastava

Addresses: Department of Computer Science and Information System, Birla Institute of Technology and Science (BITS), Pilani Campus 333031, Pilani, Rajasthan, India

Abstract: As the demand for highly sophisticated software increase, the role of software testing becomes indispensible in the software development life cycle. Software testing is one of the most important factors for assessing the global competitive position of any software organisation. Thus, the automation of software testing is very essential. Software testing coverage criteria (i.e., generation of complete test sequences) are not very easily measured and quantified. Many attempts have been made to quantify the software testing coverage using various meta-heuristic models. The present work describes a method for increasing software testing efficiency by identifying the optimal test sequences for behaviour model. The aim of this paper is to present an algorithm, using ant colony optimisation (ACO), a swarm-based optimisation approach, to automate the process of optimised test sequence generation of software under test (SUT). A real-life example of verifying a proposed approach using ACO is given in this paper.

Keywords: ant colony optimisation; ACO; software testing; test data; test sequence generation; behavioural testing.

DOI: 10.1504/IJCSYSE.2012.050232

International Journal of Computational Systems Engineering, 2012 Vol.1 No.2, pp.91 - 99

Published online: 28 Aug 2014 *

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