An Improved Genetic Algorithm-Based Test Coverage Analysis for Graphical User Interface Software
Asade Mojeed Adeniyi,
Akinola Solomon Olalekan
Issue:
Volume 5, Issue 2, April 2016
Pages:
7-14
Received:
22 January 2016
Accepted:
3 February 2016
Published:
6 April 2016
Abstract: Quality and reliability of software products can be determined through the amount of testing that is carried out on them. One of the metrics that are often employed in measuring the amount of testing is the coverage analysis or adequacy ratio. In the proposed optimized basic Genetic Algorithm (GA) approach, a concept of adaptive mutation was introduced into the basic GA in order for low-fitness chromosomes to have an increased probability of mutation, thereby enhancing their role in the search to produce more efficient search. The main purpose of this concept is to decrease the chance of disrupting a high-fitness chromosome and to have the best exploitation of the exploratory role of low-fitness chromosome. The study reveals that the optimized basic GA improves significantly the adequacy ratio or coverage analysis value for Graphical User Interface (GUI) software test over the existing non-adaptive mutation basic GA.
Abstract: Quality and reliability of software products can be determined through the amount of testing that is carried out on them. One of the metrics that are often employed in measuring the amount of testing is the coverage analysis or adequacy ratio. In the proposed optimized basic Genetic Algorithm (GA) approach, a concept of adaptive mutation was introd...
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