@inproceedings{d112efd2225845f6b2e7154bc0b773ed,
title = "Evolutionary-based automated testing for GraphQL APIs",
abstract = "The Graph Query Language (GraphQL) is a powerful language for APIs manipulation in web services. It has been recently introduced as an alternative solution for addressing the limitations of RESTful APIs. This paper introduces an automated solution for GraphQL APIs testing. We present a full framework for automated APIs testing, from the schema extraction to test case generation. Our approach is based on evolutionary search. Test cases are evolved to intelligently explore the solution space while maximizing code coverage criteria. The proposed framework is implemented and integrated in the open-source EVOMASTER tool. Experiments on two open-source GraphQL APIs show statistically significant improvement of the evolutionary approach compared to the baseline random search.",
keywords = "GraphQL, automated testing, evolutionary algorithms, evomaster, fuzzing, search-based software testing",
author = "Asma Belhadi and Man Zhang and Andrea Arcuri",
note = "Publisher Copyright: {\textcopyright} 2022 Owner/Author.; 2022 Genetic and Evolutionary Computation Conference, GECCO 2022 ; Conference date: 09-07-2022 Through 13-07-2022",
year = "2022",
month = jul,
day = "9",
doi = "10.1145/3520304.3528952",
language = "英语",
series = "GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference",
publisher = "Association for Computing Machinery, Inc",
pages = "778--781",
booktitle = "GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference",
}