Learning-Based Testing of Microservices : An Exploratory Case Study Using LBTest
Peter Nycander · KTH Publication Database DiVA (KTH Royal Institute of Technology) · 2015
Learning-based testing (LBT) is a relatively new testing paradigm which automatically generates test cases for black-box testing of a system under test (SUT). LBT uses machine learning to model a SUT, and combines this with model-based testing. This thesis uses LBTest, a research tool created at CSC, in order to apply LBT on a new architectural style of distributed systems called microservices. Two new approaches to using LBT have been implemented to test a commercial product for counter-party credit risk. One approach is to monitor the internal processes to extract the states of the software. The second is based on fault injection on the software level. Errors have been found during the fault injection approach. Lastly, some general recommendations are given on how to implement LBT.