A Web Services Testing Approach based on Difference Measurement and Adaptive Random Testing

Abstract

Nowadays, people's demand for Web services is increasing, but in the process of obtaining these services, there are some problems in the service, which have not been detected, resulting in a poor experience. Therefore, this paper proposes a difference measurement method based on FSCS (Fixed Sized Candidate Set) algorithm, which improves the traditional ART (Adaptive Random Testing) algorithm. By comparing the differences of each method in Web Services, the farthest method is selected for testing, which improves the testing efficiency and improves the service experience. The method first selects one of the multiple services that may have a potential error service for testing, each time picks the farthest service in the combined service, and then selects the farthest method from the service as a test case, and then measures the differences between the methods in the service, compare the test results with the expected results, so that the problems in the service can be effectively detected. The experimental results show that the proposed method based on difference metric and adaptive random test can detect the existing methods in the service and improve the detection efficiency.