2015
DOI: 10.1007/978-3-319-25423-4_21
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Enhanced Distributed Behavioral Cartography of Parametric Timed Automata

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Cited by 6 publications
(4 citation statements)
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“…This problem can therefore be connected to the MCS problem, in which the computation time to find a common subgraph and how the domain can be decomposed cannot be known before the common subgraph has been found. Heuristics and dynamic algorithms have been designed and evaluated in [1, 2]. Their conclusion is that for small parameter spaces, a random distribution of points works well, and for larger parameter spaces, a dynamic domain decomposition with work stealing works better.…”
Section: Related Workmentioning
confidence: 99%
“…This problem can therefore be connected to the MCS problem, in which the computation time to find a common subgraph and how the domain can be decomposed cannot be known before the common subgraph has been found. Heuristics and dynamic algorithms have been designed and evaluated in [1, 2]. Their conclusion is that for small parameter spaces, a random distribution of points works well, and for larger parameter spaces, a dynamic domain decomposition with work stealing works better.…”
Section: Related Workmentioning
confidence: 99%
“…IMITATOR features a number of additional algorithms, including i) non-Zeno infinite run synthesis [27], ii) behavioral cartography [16] that partitions the parameter space into tiles where the discrete behavior is uniform, or iii) parametric reachability preservation, that takes as input a discrete state and a reference valuation, and synthesizes valuations for which this discrete state is reachable iff it is reachable for the reference valuation [25]. The two latter algorithms can be distributed over a cluster, showing interesting results, and can be used to perform reachability synthesis while being faster than the normal reachability synthesis algorithm for some benchmarks [14,15]. Finally, compositional verification for a subclass of IPTAs (a parametric extension of event-recording automata [4]) was proposed in [24].…”
Section: # Synth Deadlockfreementioning
confidence: 99%
“…robustness: synthesize parameter valuations preserving the discrete behavior (untimed language) w.r.t. to a given valuation (see e. g., [ACEF09,San15]).…”
Section: Propertiesmentioning
confidence: 99%