Covering Array Constructors: An Experimental Analysis of Their Interaction Coverage and Fault Detection

Combinatorial interaction testing (CIT) aims at constructing a covering array (CA) of all value combinations at a specific interaction strength, to detect faults that are caused by the interaction of parameters. CIT has been widely used in different applications, with many algorithms and tools having been proposed to support CA construction. To date, however, there appears to have been no studies comparing different CA constructors when only some of the CA test cases are executed. In this paper, we present an investigation of five popular CA constructors: ACTS, Jenny, PICT, CASA and TCA. We conducted empirical studies examining the five programs, focusing on interaction coverage and fault detection. The experimental results show that when there is no preference or special justification for using other CA constructors, then Jenny is recommended—because it achieves better interaction coverage and fault detection than the other four constructors in many cases. Our results also show that when using ACTS or CASA, their CAs must be prioritized before testing. The main reason for this is that these CAs can result in considerable interaction coverage or fault detection capabilities when executing a large number of test cases; however, they may also produce the lowest rates of fault detection and interaction coverage.

Combinatorial Interaction Testing for Improving Conformance Faults

In this paper we are describing about how to develop an interface for compiling of any java program and will show how many errors in the program. We will also perform some metrics like number of lines time taken to write the program, operands used in the program. And also find volume effort required to implement or understand the program. For this we are using Combinatorial Interaction testing (CIT), is a productive and viable strategy for identifying disappointments that are brought about by the collaborations of different framework input parameters. In this paper, we talk about CIT, call attention to a portion of challenges for applying it practically, and feature some ongoing advances that have improved CIT's immaterialness to present day frameworks. We additionally give a guide to future research and bearings one that we expectation will prompt new CIT look into and to more excellent testing of mechanical frameworks.

Optimization Driven Constraints Handling in Combinatorial Interaction Testing

The combinatorial strategy is useful in the reduction of the number of input parameters into a compact set of a system based on the combinations of the parameters. This strategy can be used in testing the behaviour that takes place when the events are allowed to be executed in an appropriate order. Basically, in the software systems, for the highly configurable system, the input configurations are based on the constraints, and the construction of this idea undergoes various kinds of difficulties. The proposed Jaya-Bat optimization algorithm is developed with the combinatorial interaction test cases in an effective manner in the presence of the constraints. The proposed Jaya-Bat based optimization algorithm is the integration of the Jaya optimization algorithm (JOA) and the Bat optimization algorithm (BA). The experimentation is carried out in terms of average size and the average time to prove the effectiveness of the proposed algorithm. From the results, it is clear that the proposed algorithm is capable of selecting the test cases optimally with better performance.