Skip to main content



Master Thesis Defense: Jyotsana Gupta

July 3, 2019

Speaker: Jyotsana Gupta

Supervisor: Dr. J. Paquet

Examining Committee: Drs. Y.-G. Gueheneuc, N. Tsantalis, D. Pankratov (Chair)

Title: Execution/Simulation of Context/Constraint-aware Composite Services using GIPSY

Date: Wednesday, July 3, 2019

Time: 10:30am

Place: EV 2.260


For fulfilling a complex requirement comprising of several sub-tasks, a composition of simple web services, each of which is dedicated to performing a specific sub-task involved, proves to be a more competent solution in comparison to an equivalent atomic web service. Owing to advantages such as re-usability of components, broader options for composition requesters and liberty to specialize for component providers, for over two decades now, composite services have been extensively researched to the point of being perfected in many aspects. Yet, most of the studies undertaken in this field fail to acknowledge that every web service has a limited context in which it can successfully perform its tasks, the boundaries of which are defined by the internal constraints placed on the service by its providers. When used as part of a composition, the restricted context-spaces of all such component services together define the contextual boundaries of the composite service as a unit, which makes internal constraints an influential factor for composite service functionality. However, due to the limited exposure received by them, no systems have yet been proposed to cater to the specific verification of internal constraints imposed on components of a composite service. In an attempt to address this gap in service composition research, in this thesis, we propose a multi-faceted solution capable of not only automatically constructing context-aware composite web services with their internal constraints positioned for optimum resource-utilization but also of validating the generated compositions using the General Intensional Programming SYstem (GIPSY) as a time- and cost-efficient simulation/execution environment.

Back to top Back to top

© Concordia University