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Canfora Gerardo and Penta Massimiliano Di.

Testing and verification in service-oriented architecture: A survey.

Bozkurt Mustafa, Harman Mark, and Hassoun Youssef.In Proceedings of the 41st International Conference on Software Engineering (ICSE’19). Atlidakis Vaggelis, Godefroid Patrice, and Polishchuk Marina.EvoMaster: A search-based system test generation tool. Arcuri Andrea, Galeotti Juan Pablo, Marculescu Bogdan, and Zhang Man.Handling SQL databases in automated system test generation. Arcuri Andrea and Galeotti Juan Pablo.Adaptive random testing: An illusion of effectiveness? In ACM International Symposium on Software Testing and Analysis (ISSTA). Automated blackbox and whitebox testing of RESTful APIs with EvoMaster. RESTful API automated test case generation with EvoMaster. Test suite generation with the Many Independent Objective (MIO) algorithm.

In IEEE International Conference on Software Testing, Verification and Validation (ICST). EvoMaster: Evolutionary multi-context automated system test generation. Search-based software test data generation for string data using program-specific search operators.

Alshraideh Mohammad and Bottaci Leonardo.

A systematic review of the application and empirical investigation of search-based test-case generation. The article presents a taxonomy of the faults found based on the manual analysis of 415 faults in the eight case studies and proposes a method to support the classification using clustering of the resulting test cases. The tests were manually evaluated to determine their root causes and to obtain additional information. The test cases generated during the search are clustered based on the reported last executed line and based on the error messages returned, when such error messages were available.

Tests were automatically generated for a set of eight case studies, seven open-source and one industrial. This is needed to enable engineers to highlight and focus on the most serious faults. We propose to apply a density-based clustering algorithm to the test cases evolved during the search to allow a better separation between different groups of faults. The taxonomy is a first step in understanding, analyzing, and ultimately fixing software faults in web services and enterprise applications. This article proposes a taxonomy of the faults we have found using search-based software testing techniques applied on RESTful APIs. However, automated test generation often results in large test suites that are hard to evaluate and investigate manually. Automation in test data generation provides a useful way of generating test data in a fast and efficient manner. The diversity and increased number of applications using RESTful APIs means that increasing amounts of resources are spent developing and testing these systems. RESTful web services are often used for building a wide variety of enterprise applications.