Abstract
Software testing is a vital part of the software development life cycle. In many cases, the system under test has more than one input making the testing efforts for every exhaustive combination impossible (i.e. the time of execution of the test case can be outrageously long). Combinatorial testing offers an alternative to exhaustive testing via considering the interaction of input values for every t-way combination between parameters. Combinatorial testing can be divided into three types which are uniform strength interaction, variable strength interaction and input-output based relation (IOR). IOR combinatorial testing only tests for the important combinations selected by the tester. Most of the researches in combinatorial testing applied the uniform and the variable interaction strength, however, there is still a lack of work addressing IOR. In this paper, a Jaya algorithm is proposed as an optimization algorithm engine to construct a test list based on IOR in the proposed combinatorial test list generator strategy into a tool called CTJ. The result of applying the Jaya algorithm in input-output based combinatorial testing is acceptable since it produces a nearly optimum number of test cases in a satisfactory time range.
Highlights
Combinatorial testing is a black-box testing technique that generates test cases by combining the values of different input parameters using combinatorial optimization strategies to reduce the interfaces fail and increase the reliability of the system [1]
Experimental Results and Discussion: This section is divided into three parts which are parameter tuning of CTJ, two experiments for input-output based relation (IOR) and one experiment for uniform strength interaction strength to evaluate the difference between CTJ with another existing strategy in handling combinatorial optimization
CTJ which stands for the combinatorial testing strategy that featured inputoutput based relation using Jaya algorithm is proposed and introduced
Summary
Combinatorial testing is a black-box testing technique that generates test cases by combining the values of different input parameters using combinatorial optimization strategies to reduce the interfaces fail and increase the reliability of the system [1]. All input values of the test objects and interactions between each parameter are tested. This testing causes a higher detection of interaction failures compared to single parameter testing. Combinatorial test generation relates to the process of searching the optimum number of test cases for test consideration based on the interaction of t-way parameters (where t indicates the interaction strength). Many different optimization strategies are used to generate the test cases for combinatorial testing such as Harmony Search [3], Genetic Algorithm [4], Ant Colony Algorithm [4], Simplified Swarm Optimization [5], Differential Evolution Algorithm [6] and so on
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