Thilini Bhagya Randunu Pathirannehelage

Doctor of Philosophy, (Computer Science)
Study Completed: 2021
College of Sciences


Thesis Title
Generating Mock Skeletons for Lightweight Web Service Testing

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As Service-Oriented Computing opens up the possibility for service reuse in new contexts, most applications today are not developed from the ground up. Rather, developers make extensive use of RESTful HTTP-based services to realise certain functional behaviours that an application requires. This has, however, introduced new challenges for application testing as dependent services are not necessarily available for testing purposes. Simulating the behaviour of such services is, therefore, useful in addressing their absence and progressing through testing. Mrs Thilini examined the appropriateness of Symbolic Machine Learning algorithms to automatically synthesise HTTP services' mock skeletons from network traffic recordings. These skeletons could then be customised to create mocks that generate service responses suitable for testing. The experimental results demonstrated that symbolic learning techniques were capable of making highly accurate and human-readable predictions for key aspects of HTTP service responses, such as headers and status codes.

Professor Hans Guesgen
Associate Professor Jens Dietrich