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Ferhat Khendek

Researcher at Concordia University

Publications -  192
Citations -  2920

Ferhat Khendek is an academic researcher from Concordia University. The author has contributed to research in topics: Middleware & High availability. The author has an hindex of 23, co-authored 186 publications receiving 2751 citations. Previous affiliations of Ferhat Khendek include Université de Montréal & Concordia University Wisconsin.

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Test selection based on finite state models

TL;DR: In this paper, a method for the selection of appropriate test case, an important issue for conformance testing of protocol implementations as well as software engineering, is presented, called the partial W-method, which is shown to have general applicability, full fault-detection power, and yields shorter test suites than the W-Method.
Journal ArticleDOI

Test selection based on finite state models

TL;DR: In this paper, a method for the selection of appropriate test case, an important issue for conformance testing of protocol implementations as well as software engineering, is presented, called the partial W-method, which is shown to have general applicability, full fault-detection power, and yields shorter test suites than the W-Method.
Journal ArticleDOI

Timed Wp-method: testing real-time systems

TL;DR: This paper addresses the issue of testing real-time software systems specified as a timed input output automaton (TIOA) and introduces the syntax and semantics of TIOA, a variant of timed automaton.
Proceedings ArticleDOI

Timed test cases generation based on state characterization technique

TL;DR: An existing test cases generation technique is adapted, based on state characterization set, to generate timed test cases from a timed system specification, which is a variant of the Alur and Dill model.
Proceedings ArticleDOI

Deploying Microservice Based Applications with Kubernetes: Experiments and Lessons Learned

TL;DR: This paper examines the availability achievable through Kubernetes under its default configuration and conducts a set of experiments which show that the service outage can be significantly higher than expected.