Andy Jinqing Yu

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We propose a new saturation-based symbolic state-space generation algorithm for finite discrete-state systems. Based on the structure of the high-level model specification, we first disjunctively partition the transition relation of the system, then conjunctively partition each disjunct. Our new encoding recognizes identity transformations of state(More)
Chaining can reduce the number of iterations required for symbolic state-space generation and model-checking, especially in Petri nets and similar asynchronous systems, but requires considerable insight and is limited to a static ordering of the events in the high-level model. We introduce a two-step approach that is instead fine-grained and dynamically(More)
Choosing a good variable order is crucial for making symbolic state-space generation algorithms truly efficient. One such algorithm is the MDD-based Saturation algorithm for Petri nets implemented in S m A r T, whose efficiency relies on exploiting event locality. This paper presents a novel, static ordering heuristic that considers place invariants of(More)
We consider the stationary solution of large ergodic continuous-time Markov chains (CTMCs) with a finite state space <i>S</i>, i.e., the computation of &pi; as solution of &pi; &#183; <b>Q</b> = 0 subject to &sum;<sub><b>i</b>&#949;<i>s</i></sub>&pi;[<b>i</b>] = 1, where <b>Q</b> coincides with transition rate matrix <b>R</b> except in its diagonal(More)
The S m A r T (Stochastic Model checking Analyzer for Reliability and Timing) tool is a software package to study complex discrete-state systems. With S m A r T, it is possible to study the logical behavior of the system, by generating the state space underlying a complex model and asking temporal logic queries about its dynamic behavior, as done in(More)
Bounded reachability or model checking is widely believed to work poorly when using decision diagrams instead of SAT procedures. Recent research suggests this to be untrue with regards to synchronous systems, particularly digital circuits. This paper shows that the belief is also a myth for asynchronous systems, such as models specified by Petri nets. We(More)
The S m A r T (Symbolic Model-checking Analyzer for Reliability and Timing) tool is a software package to study complex discrete-state systems. With S m A r T, it is possible to study the logical behavior of the system, by generating the state space underlying a complex model and asking temporal logic queries about its dynamic behavior, as done in(More)
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