Timed analysis of real-time systems can be performed using continuous (symbolic) or discrete (explicit) techniques. The explicit state-space exploration can be considerably faster for models with moderately small constants, however, at the expense of high memory consumption. In the setting of timed-arc Petri nets, we explore new data structures for lowering the used memory: PTries for efficient storing of configurations and time darts for semi-symbolic description of the state-space. Both methods are implemented as a part of the tool TAPAAL and the experiments document at least one order of magnitude of memory savings while preserving comparable verification times.
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