H
Hongyang Qu
Researcher at University of Sheffield
Publications - 77
Citations - 1909
Hongyang Qu is an academic researcher from University of Sheffield. The author has contributed to research in topics: Model checking & Probabilistic logic. The author has an hindex of 21, co-authored 74 publications receiving 1711 citations. Previous affiliations of Hongyang Qu include Concordia University & Coventry Health Care.
Papers
More filters
Book ChapterDOI
MCMAS: A Model Checker for the Verification of Multi-Agent Systems
TL;DR: In this article, a specification language based on epistemic logic for knowledge has been proposed to express security specifications involving anonymity in epistemic formalisms as they explicitly state the lack of different kinds of knowledge of the principals.
Journal ArticleDOI
MCMAS: an open-source model checker for the verification of multi-agent systems
TL;DR: The underlying semantics of the specification language supported and the algorithms implemented in MCMAS, including its fairness and counterexample generation features, are presented and a detailed description of the implementation is provided.
Book ChapterDOI
Assume-Guarantee verification for probabilistic systems
TL;DR: This work adopts an assume-guarantee approach to verification, where both the assumptions made about system components and the guarantees that they provide are regular safety properties, represented by finite automata.
Book ChapterDOI
Quantitative multi-objective verification for probabilistic systems
TL;DR: This work proposes and implements an efficient verification framework for analysing multiple quantitative objectives of systems that exhibit both nondeterministic and stochastic behaviour, and presents two distinct applications of it: firstly, controller synthesis subject to multiple quantitative objective verification; and, secondly, quantitative compositional verification.
Proceedings ArticleDOI
Model Repair for Markov Decision Processes
TL;DR: This paper first formulate a region-based approach, which yields an interval in which the minimal repair cost is contained, and also considers sampling based approaches, which are faster but unable to provide lower bounds on the repair cost.