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Titlebook: Computer Aided Verification; 28th International C Swarat Chaudhuri,Azadeh Farzan Conference proceedings 2016 Springer International Publish

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樓主: 弄碎
51#
發(fā)表于 2025-3-30 09:19:59 | 只看該作者
52#
發(fā)表于 2025-3-30 12:54:29 | 只看該作者
0302-9743 cation, CAV 2016, held in Toronto, ON, USA, in July 2016..Thetotal of 46 full and 12 short papers presented in the proceedings wascarefully reviewed and selected from 195 submissions. The papers wereorganized in topical sections named: probabilistic systems; synthesis; constraint solving; model chec
53#
發(fā)表于 2025-3-30 17:36:20 | 只看該作者
54#
發(fā)表于 2025-3-31 00:06:41 | 只看該作者
Termination Analysis of Probabilistic Programs Through Positivstellensatz’s analysis of nondeterministic probabilistic programs with polynomial guards and assignments. Our approach is through synthesis of polynomial ranking supermartingales, that on one hand significantly generalizes linear ranking supermartingales and on the other hand is a counterpart of polynomial ranki
55#
發(fā)表于 2025-3-31 04:53:26 | 只看該作者
Markov Chains and Unambiguous Büchi Automatased instead of deterministic automata in settings where nondeterministic automata can not be applied in general. In this paper, we provide a polynomially time-bounded algorithm for probabilistic model checking of discrete-time Markov chains against unambiguous Büchi automata specifications and repor
56#
發(fā)表于 2025-3-31 06:28:26 | 只看該作者
Synthesizing Probabilistic Invariants via Doob’s Decompositionnvariant—and then apply the optional stopping theorem in order to infer properties at termination time. One of the main challenges, then, is to systematically find martingales..We propose a novel procedure to synthesize martingale expressions from an arbitrary initial expression. Contrary to state-o
57#
發(fā)表于 2025-3-31 10:27:48 | 只看該作者
,: Exact Symbolic Inference for Probabilistic Programsistic inference systems today have adopted approximate inference techniques, which trade precision for better performance (but often without guarantees). As a result, while desirable for its ultimate precision, the practical effectiveness of exact inference for probabilistic programs is mostly unkno
58#
發(fā)表于 2025-3-31 15:05:42 | 只看該作者
PSCV: A Runtime Verification Tool for Probabilistic SystemC Models of interest are expressed using bounded linear temporal logic. The various features of the tool including automatic monitor generation for producing execution traces of the model-under-verification, mechanism for automatically instrumenting the model, and the interaction with statistical model chec
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