Print Email Facebook Twitter Guiding automated system test generation for RESTful APIs using log statements Title Guiding automated system test generation for RESTful APIs using log statements Author Kemna, Michael (TU Delft Electrical Engineering, Mathematics and Computer Science; Cardiology Informatics, Philips Healthcare) Contributor Panichella, A. (mentor) Olsthoorn, Mitchell (mentor) Pawełczak, Przemysław (graduation committee) Degree granting institution Delft University of Technology Programme Computer Science and Engineering Project CSE3000 Research Project Date 2020-06-22 Abstract Automated generation of system tests for RESTful APIs has been extensively investigated. Previous investigations use either a white box or a blackbox approach, wherein the quality of the test cases can be assessed on the HTTP response in the prior and also on the results of byte-code analysis in the latter. Both approaches are limited however, as the black box is often under performing, while the white box can only be applied to a limited set of RESTful APIs. In this paper, we introduce a novel approach where the system under test (SUT) is defined as a container. In this approach, the log output can be used to assess the quality of the test cases. We present a prototype that retrieves all semantically relevant in-formation from the logs using regex patterns, which was subsequently maximized by an evolutionary algorithm. The container, white box and black box mode were performed on three SUTs to evaluate the effectiveness and performance of these modes. An increase in code coverage was observed in the container versus black box mode in all SUTs (p <0.001,p <0.001 and p= 0.054). In all SUTs, significantly less actions could be evaluated by the container as compared to the black box and white box mode. Our results show promising results for the novel approach outlined in this paper. Importantly, this approach can be applied to any RESTful API Subject System testingRESTful APIEvolutionary Algorithmscontainerblack boxwhite box To reference this document use: http://resolver.tudelft.nl/uuid:5cee41ad-7dab-4aad-863b-f08226ab2597 Part of collection Student theses Document type bachelor thesis Rights © 2020 Michael Kemna Files PDF RP_MJK_EM_Blackbox_stripp ... nomail.pdf 224.27 KB Close viewer /islandora/object/uuid:5cee41ad-7dab-4aad-863b-f08226ab2597/datastream/OBJ/view