Automated generator for complex and realistic test data—a case study
Richard Lipka, Tomáš Potužák · Annals of Computer Science and Information Systems · 2018
Some type of tests, especially stress tests and functional tests, require a large amount of realistic test data.In this paper, we propose a tool JOP (Java Object Populator) that uses a pseudorandom number generator in order to create test sets of complex Java objects, that can be automatically generated and directly used.Along with that, we also show usage of this tool in case study focused on performance evaluation of a real cashier system.The tool is designed to be able to set simple attributes of any Java object and in many cases also to create complex structures when objects are connected via references.Random values are created using the rules that are added to the class definition in form of annotation to each attribute.Using this tool simplifies creating of tests, as the tester does not need a detailed knowledge of data structures.The specification of expected values is delegated to the designer of the data model and becomes the part of the model.Furthermore, as the data objects are created at runtime, using reflection, the tests do not have to be changed when data carrying objects are modified.