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@@ -0,0 +1,93 @@
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+include "primitives.alh"
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+include "modelling.alh"
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+include "object_operations.alh"
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+
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+Element function coverability_graph(params : Element, output : Element):
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+ Element result
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+ Element model
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+ Element workset
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+ String state
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+
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+ result = create_node()
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+ out_model = instantiate_node(output["CoverabilityGraph"])
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+ in_model = params["PetriNets"]
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+
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+ // Create a dictionary representation for each transition
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+ transition_vectors_produce = create_node()
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+ transition_vectors_consume = create_node()
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+ all_transitions = allInstances(in_model, "Transition")
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+ while (read_nr_out(all_transitions) > 0):
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+ transition = set_pop(all_transitions)
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+ name = read_attribute(in_model, transition, "name")
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+ vector = create_node()
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+
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+ tv = create_node()
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+ dict_add(transition_vectors_consume, name, tv)
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+ links = allIncomingAssociationInstances(in_model, transition, "P2T")
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+ while (read_nr_out(links) > 0):
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+ link = set_pop(links)
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+ name = reverseKeyLookup(in_model["model"], read_edge_src(in_model["model"][link]))
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+ link_weight = read_attribute(in_model, link, "weight")
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+ dict_add(tv, name, link_weight)
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+
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+ tv = create_node()
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+ dict_add(transition_vectors_produce, name, tv)
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+ links = allOutgoingAssociationInstances(in_model, transition, "T2P")
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+ while (read_nr_out(links) > 0):
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+ link = set_pop(links)
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+ name = reverseKeyLookup(in_model["model"], read_edge_dst(in_model["model"][link]))
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+ link_weight = read_attribute(in_model, link, "weight")
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+ dict_add(tv, name, link_weight)
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+
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+ workset = create_node()
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+ initial = instantiate_node(out_model, "InitialState", "")
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+
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+ all_places = allInstances(in_model, "Place")
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+ dict_repr = create_node()
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+ while (read_nr_out(all_places) > 0):
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+ place = set_pop(all_places)
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+ state_config = instantiate_node(out_model, "Place", "")
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+ instantiate_attribute(out_model, state_config, "name", read_attribute(in_model, place, "name"))
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+ instantiate_attribute(out_model, state_config, "tokens", read_attribute(in_model, place, "tokens"))
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+ instantiate_link(out_model, "", "", initial, state_config)
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+ dict_add(dict_repr, read_attribute(in_model, place, "name"), read_attribute(in_model, place, "tokens"))
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+
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+ set_add(workset, create_tuple(initial, dict_repr))
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+
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+ while (read_nr_out(workset) > 0):
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+ work_unit = set_pop(workset)
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+ state = work_unit[0]
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+ dict_repr = dict_copy(work_unit[1])
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+
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+ // Compute how the PN behaves with this specific state
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+ // For this, we fetch all transitions and check if they are enabled
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+ all_transitions = allInstances(in_model, "Transition")
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+ while (read_nr_out(all_transitions) > 0):
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+ name = set_pop(all_transitions)
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+ keys = dict_keys(transition_vectors_consume[name])
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+ possible = True
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+ while (read_nr_out(keys) > 0):
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+ key = set_pop(keys)
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+
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+ // Compare the values in the state with those consumed by the transition
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+ if (dict_repr[key] < transition_vectors_consume[name][key]):
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+ // Impossible transition, so discard this one
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+ possible = False
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+ continue!
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+
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+ if (possible):
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+ // Transition can execute, so compute and add the new state based on the consume/produce vectors
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+ keys = dict_keys(transition_vectors_consume[name])
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+ while (read_nr_out(keys) > 0):
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+ key = set_pop(keys)
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+ dict_overwrite(dict_repr, key, dict_repr[key] - transition_vectors_consume[name][key])
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+ keys = dict_keys(transition_vectors_produce[name])
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+ while (read_nr_out(keys) > 0):
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+ key = set_pop(keys)
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+ dict_overwrite(dict_repr, key, dict_repr[key] + transition_vectors_produce[name][key])
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+
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+ // Now write out the dictionary representation to a model!
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+ // TODO
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+
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+ dict_add(result, "CoverabilityGraph", out_model)
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+ return result!
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