Using Coupling Measure Technique and Random Iterative Algorithm for Inter-Class Integration Test Order Problem
Inter-class integration test order (ICITO) problem is to determine the order in which classes are integrated and tested. It is very important in object-oriented software integration testing or regression testing, because different test orders need different test cost to construct corresponding test stubs. However, the current solutions to the ICITO problem lack an effective coupling measure technique to estimate test stub complexity, and lack an effective algorithm to break cycles. Thus, this paper uses an improved coupling measure technique to estimate test stub complexity, and designs a random iterative algorithm to break cycles. Simulation experimental results show that the overall test stub complexity can be reduced by 15.5\% and the speed can be increased by 5.8 times, using our improved coupling measure technique and random iterative algorithm.