Reference : RESTful API Automated Test Case Generation
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/31273
RESTful API Automated Test Case Generation
English
Arcuri, Andrea mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
2017
IEEE International Conference on Software Quality, Reliability & Security (QRS)
Yes
IEEE International Conference on Software Quality, Reliability & Security (QRS)
2017
[en] Nowadays, web services play a major role in the
development of enterprise applications. Many such applications
are now developed using a service-oriented architecture (SOA),
where microservices is one of its most popular kind. A RESTful
web service will provide data via an API over the network using
HTTP, possibly interacting with databases and other web services.
Testing a RESTful API poses challenges, as inputs/outputs
are sequences of HTTP requests/responses to a remote server.
Many approaches in the literature do black-box testing, as the
tested API is a remote service whose code is not available. In
this paper, we consider testing from the point of view of the
developers, which do have full access to the code that they
are writing. Therefore, we propose a fully automated white-box
testing approach, where test cases are automatically generated
using an evolutionary algorithm. Tests are rewarded based on
code coverage and fault finding metrics. We implemented our
technique in a tool called EVOMASTER, which is open-source.
Experiments on two open-source, yet non-trivial RESTful services
and an industrial one, do show that our novel technique did
automatically find 38 real bugs in those applications. However,
obtained code coverage is lower than the one achieved by the
manually written test suites already existing in those services.
Research directions on how to further improve such approach
are therefore discussed.
http://hdl.handle.net/10993/31273
FnR ; FNR3949772 > Lionel Briand > VVLAB > Validation and Verification Laboratory > 01/01/2012 > 31/07/2018 > 2010

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