This paper studies the analysis and parameter synthesis problems for Parametric Timed Automata (PTA) with properties in Linear-time Temporal Logic (LTL). It introduces a series of variations of Nested Depth-First Search (NDFS). We first study the LTL model checking problem for PTA. Based on a careful analysis of parametric zones, we introduce a new layered NDFS approach to LTL model checking. We integrate this with several techniques to prune the search space. In particular, we apply subsumption abstraction to PTA for the first time. We also propose heuristics on the search order to improve the performance. Next, we study parameter synthesis. To this end, this new layered approach and subsumption are added to a Collecting NDFS scheme. We implemented all algorithms in the IMITATOR tool and analyse their efficiency in a number of experiments.

The synthesis of timing parameters consists in deriving conditions on the timing constants of a concurrent system such that it meets its specification. Parametric timed automata are a powerful formalism for parameter synthesis, although most problems are undecidable. We first address here the following reachability preservation problem: given a reference parameter valuation and a (bad) control state, do there exist other parameter valuations that reach this control state iff the reference parameter valuation does? We show that this problem is undecidable, and introduce a procedure that outputs a possibly underapproximated answer. We then show that our procedure can efficiently replace the behavioral cartography to partition a bounded parameter subspace into good and bad subparts; furthermore, our procedure can even outperform the classical bad-state driven parameter synthesis semi-algorithm, especially when distributed on a cluster.

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