Paper Info
Title
Resource-based test case generation for RESTful web services
Abstract
ABSTRACTNowadays, RESTful web services are widely used for building enterprise applications. In this paper, we propose an enhanced search-based method for automated system test generation for RESTful web services. This method exploits domain knowledge on the handling of HTTP resources, and it is integrated in the Many Independent Objectives (MIO) search algorithm. MIO is an evolutionary algorithm specialized for system test case generation with the aim of maximizing code coverage and fault finding. Our approach builds on top of the MIO by implementing a set of effective templates to structure test actions, based on the semantics of HTTP methods, used to manipulate the web services' resources. We propose four novel sampling strategies for the test cases that can use one or more of these test actions. The strategies are further supported with a set of new, specialized mutation operators that take into account the use of these resources in the generated test cases. We implemented our approach as an extension to the EvoMaster tool, and evaluated it on seven open-source RESTful web services. The results of our empirical study show that our novel, resource-based sampling strategies obtain a significant improvement in performance over the baseline MIO (up to +42% coverage).
Year
DOI
Venue
2019
10.1145/3321707.3321815
GECCO
Keywords
Field
DocType
Search-based Test Case Generation, RESTful Web Service Testing
World Wide Web,Computer science,Artificial intelligence,Web service,Machine learning
Conference
Citations 
PageRank 
References 
4
0.46
0
Authors
3
Name
Order
Citations
PageRank
Man Zhang111315.27
Bogdan Marculescu2404.43
Andrea Arcuri3263092.48