| L. de Alfaro. Formal Veri cation of Probabilistic Systems. PhD thesis, Stanford University, 1997. |
....know nondeterminism versus unconditional, conditional don t care and conditional don t know probability. Di erent combinations of these induced nine di erent semantic models. Di erent approaches, in the eld of probabilistic automaton and Markov decision processes, are considered in [26, 25, 29, 8] where the separation between nondeterministic and probabilistic behaviour is achieved by means of adversaries, schedulers or policies, which resolve the nondeterminism. The speci c aim of this paper is to add probabilistic choice to Hennessy s EPL [14] to show how the semantics of that can be ....
L. de Alfaro. Formal Veri cation of Probabilistic Systems. PhD thesis, Stanford University, 1998.
....such as RCP. Moreover, most performance measures are no longer expressible as a single number, but, depending on how the nondeterminism is resolved, yield a number within an interval. Several performance analysis methods have been extended for systems with nondeterminism in [LSS94, BdA95, dA97, McI99, KNSS01] Since the timing delays of RCP lie in intervals, rather than having xed values, only [LSS94, KNSS01] are directly applicable here. Thus, the approach taken by [D A99] and [FS01] is to remove the nondeterminism and replace it respectively by a probabilistic and a deterministic ....
....by traces) In other words, if A v B that A does not perform worse than B for those measures; if also B v A, then A and B satisfy exactly the same performance measures. Moreover, remark that the minimal and maximal average number of rounds can be computed easily with the methods by [BdA95, dA97] on the automaton I 3 , because we can abstract from the exact timing delays. However, as far as the author knows, no techniques exist yet for calculation of the average time before a leader is elected; an extension of the results by [BdA95, dA97] to probabilistic timed automata would be useful ....
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L. de Alfaro. Formal Verication of Probabilistic Systems. PhD thesis, Stanford University, 1997.
....to formal methods for probabilistic systems, grafted upon the vast amount of work achieved in the area of performance modeling, start from a mathematical reconstruction of the system under consideration. Models that are often used are Markov chains and Markov decision processes (see, e.g. [16, 1 6]) and probabilistic input output automata (cf. 28, 29] for example) sometimes augmented with notions of probabilistic bisimulation [22, 12] In the probabilistic analyses of the model, results from probability theory are used to obtain, e.g. average performance or bounds on error probabilities. ....
....the model, results from probability theory are used to obtain, e.g. average performance or bounds on error probabilities. Model checking based techniques provide a logical language to characterize program properties and exploit automated tools to exhaustively search the state space (consult, e.g. [27, 19, 1, 15]) For a wide range of programs the construction of the mathematical model can already be problematic. A systematic approach to simplify the program, or obtain properties without having to actually calculate the semantics are useful. Approaches in this area are probabilistic process algebra and ....
L. de Alfaro. Formal Verication of Probabilistic Systems. PhD thesis, Stanford University, 1997.
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L. de Alfaro. Formal Veri cation of Probabilistic Systems. PhD thesis, Stanford University, 1997. Technical Report STAN-CS-TR-98-1601.
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L. de Alfaro. Formal Veri cation of Probabilistic Systems. PhD thesis, Stanford University, 1997.
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L. de Alfaro. Formal Veri cation of Probabilistic Systems. PhD thesis. Technical Report STAN-CS-TR-98-1601, Stanford University, 1997.
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L. de Alfaro. Formal Veri cation of Probabilistic Systems. PhD thesis. Technical Report STAN-CS-TR-98-1601, Stanford University, 1997.
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L. de Alfaro. Formal Veri cation of Probabilistic Systems. PhD thesis, Stanford University, 1997.
No context found.
L. de Alfaro. Formal Veri cation of Probabilistic Systems. PhD thesis, Stanford University, 1997.
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L. de Alfaro. Formal Veri cation of Probabilistic Systems. PhD thesis, Stanford University, Department of Computer Science, 1998.
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L. de Alfaro. Formal Veri cation of Probabilistic Systems. PhD thesis, Stanford University, 1997.
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L. de Alfaro. Formal veri cation of probabilistic systems. PhD thesis, Stanford University, Department of Computer Science, 1997.
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L. de Alfaro. Formal Veri cation of Probabilistic Systems. PhD thesis, Stanford University, 1997.
No context found.
L. de Alfaro. Formal Veri cation of Probabilistic Systems. PhD thesis, Stanford University, 1997.
No context found.
de Alfaro, L. Formal Veri cation of Probabilistic Systems. PhD thesis, Stanford
No context found.
L. de Alfaro. Formal Veri cation of Probabilistic Systems. PhD thesis, Stanford University, 1997.
No context found.
de Alfaro, L.: Formal Verication of Probabilistic Systems. PhD thesis, Stanford University (1997) Technical Report STAN-CS-TR-98-1601.
No context found.
L. de Alfaro. Formal Veri cation of Probabilistic Systems. PhD thesis, Stanford University, 1997.
No context found.
L. de Alfaro. Formal veri cation of probabilistic systems. PhD thesis, Stanford University, Department of Computer Science, 1997.
No context found.
L. de Alfaro. Formal Veri cation of Probabilistic Systems. PhD thesis, Stanford University, 1997.
No context found.
de Alfaro, L.: Formal Veri cation of Probabilistic Systems. PhD thesis, Stanford University (1997) Technical Report STAN-CS-TR-98-1601.
No context found.
L. de Alfaro. Formal Veri cation of Probabilistic Systems. PhD thesis, Stanford University, 1997. Technical Report STAN-CSTR -98-1601.
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