Fibonacci driven novel test generation strategy for constrained testing

Abstract

The complex software systems consist of a number of input parameters that interact with each other. As the number of input parameters in the system increases, the trade off that the system tester faces is the thoroughness of test cases coverage, versus limited resources of time and expense that are available. An approach to resolving this trade off is to constrain the set of available test cases such that each pair-wise combination of input parameters is covered. This goal gives a well-defined level of test coverage, with a reduced number of test cases. But the problem becomes severe if the domains of input parameters are large and therefore the number of generated test cases is huge. To deal with the problem a novel constrain strategy has been introduced based on the Pairwise testing for selecting a set of test cases in the software systems having the input parameters with large domains. The strategy uses the Fibonacci series driven testcase generation approach to generate the set of intelligent testcases which are as effective as conventional testcases but in total are less in number. In the end paper also presents the experimental results which prove the effectiveness of proposed strategy in terms of number of testcases generated and issues uncovered by these testcases.