STM Journals Peer-reviewed research from Consortium e-Learning Network

Journal of Advances in Shell Programming

Design and Evaluation of Dynamic Testing in Object Oriented Programming Through Computational Techniques

  1. Sonam Singh Bhati
  2. Pradeep Tomar
  3. Parul Chaudhary

Abstract

Software testing is one of the most labour-intensive and expensive phase of the software development life cycle. It is an important and valuable part of it. Software testing successfulness is always determined on the basis of generated test cases and their prioritization. So, it consumes more effort, time and cost. Today, a numerous search-based optimization techniques are available for better accuracy in testing. The aim of this paper is to evaluate soft computing approaches for software testing. This paper aims at employing PSO algorithm in the issue of data flow testing. It proposed a simple approach based on PSO (Particle Swarm Optimization) which is inspired by social metaphors of behaviour and uses the concepts for optimizing the non linear function of particle swarm theory for data flow testing which guarantees full path coverage. In this process, first control flow graph is constructed then based on that dominance tree is generated. Test cases are generated by applying particle swarm optimization on dominance. Hence, this approach is based on generating set of optimal paths to cover all definition-use associations (du-pairs) in the program under test. Then this paper also discusses the comparison between two meta-heuristic techniques (Particle swarm optimization and Ant Colony optimization) for data flow testing. Cite this Article:Sonam Singh Bhati, Pradeep Tomar. Parul Chaudhary. Design and Evaluation of Dynamic Testing in Object Oriented Programming through Computational Techniques. Journal of Advances in Shell Programming. 2015; 2(1): 1–6p.

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