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@@ -567,7 +567,6 @@ Void function user_function_skip_init(user_id : String):
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schedule_model = get_full_model(transformation_id)
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- // Need to fall back to the default approach, which is way slower
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// 1) Create empty instance of merged metamodel
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ramified_metamodel_id = set_pop(followAssociation(core, transformation_id, "instanceOf"))
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@@ -619,7 +618,22 @@ Void function user_function_skip_init(user_id : String):
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else:
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output("Could not resolve intermediate merged metamodel")
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elif (exact_type == "ActionLanguage"):
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- output("Not Implemented yet!")
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+ output("Action Language execution starts!")
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+ action_model = get_full_model(transformation_id)
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+
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+ // 1) Group source models in dictionary
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+ input_keys = dict_keys(inputs)
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+ while (read_nr_out(input_keys) > 0):
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+ key = set_pop(input_keys)
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+
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+ // 2) Execute action language model
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+ func = get_func_AL_model(action_model)
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+
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+ // 3) Split output dictionary back to seperate models
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+ output_keys = dict_keys(outputs)
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+ while (read_nr_out(output_keys) > 0):
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+ key = set_pop(output_keys)
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+
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else:
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output("Did not know how to interpret model of type " + exact_type)
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else:
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@@ -828,6 +842,71 @@ Void function user_function_skip_init(user_id : String):
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else:
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output("No such model")
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+ elif (cmd == "transformation_add_AL"):
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+ // Add an action language transformation model
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+ output("Which metamodels do you want to use as source for the action code (empty string to finish)?")
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+ name = input()
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+ while (name != ""):
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+ model_id = get_model_id(name)
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+ if (model_id != ""):
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+ if (set_in(supported, model_id)):
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+ if (bool_not(set_in(source, model_id))):
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+ set_add(source, model_id)
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+ output("Model added as source")
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+ else:
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+ output("Model already selected as source")
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+ else:
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+ output("Model is not supported by RAMified metamodel!")
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+ else:
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+ output("No such model; try again")
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+
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+ name = input()
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+
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+ output("Which metamodels do you want to use as target for the action code (empty string to finish)?")
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+ name = input()
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+ while (name != ""):
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+ model_id = get_model_id(name)
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+ if (model_id != ""):
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+ if (set_in(supported, model_id)):
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+ if (bool_not(set_in(target, model_id))):
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+ set_add(target, model_id)
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+ output("Model added as target")
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+ else:
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+ output("Model already selected as target")
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+ else:
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+ output("Model is not supported by RAMified metamodel!")
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+ else:
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+ output("No such model; try again")
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+
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+ name = input()
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+
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+ output("Name of Action Language model?")
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+ name = input()
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+
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+ if (get_model_id(name) == ""):
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+ String new_model
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+ // Finished with all information, now create the model itself!
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+ output("Waiting for model constructors...")
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+ new_model = construct_model_raw(import_node("models/ActionLanguage"))
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+ model_create(new_model, name, user_id, ramified_metamodel_id, "ActionLanguage")
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+ model_id = get_model_id(name)
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+
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+ // Extend metadata with info on source and target
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+ String link
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+ String dst
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+
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+ while (read_nr_out(source) > 0):
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+ dst = set_pop(source)
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+ link = instantiate_link(core, "transformInput", "", model_id, dst)
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+ instantiate_attribute(core, link, "name", read_attribute(core, dst, "name"))
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+
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+ while (read_nr_out(target) > 0):
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+ dst = set_pop(target)
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+ link = instantiate_link(core, "transformOutput", "", model_id, dst)
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+ instantiate_attribute(core, link, "name", read_attribute(core, dst, "name"))
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+ else:
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+ output("Model already exists")
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+
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elif (cmd == "transformation_add_MT"):
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// Add a model transformation model
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// Just a usual model instantiation, but need to add the source and target links based on user info
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