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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.