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tutorial/00_metamodeling.py

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+# Before we can create a model in muMLE, we have to create a meta-model.
+
+# Here's an example of a (silly) meta-model.
+# We use a textual concrete syntax:
+
+mm_cs = """
+    # A class named 'A':
+    A:Class
+
+    # A class named 'B':
+    B:Class
+
+    # An association from 'A' to 'B':
+    a2b:Association (A -> B) {
+        # Every 'A' must be associated with at least one 'B'
+        target_lower_cardinality = 1;
+    }
+"""
+
+# Now, we create a model that is an instance of our meta-model:
+
+m_cs = """
+    myA:A
+
+    myB:B
+
+    myLnk:a2b (myA -> myB)
+"""
+
+# So far we've only created text strings. To parse the models, we first create our 'state', which is a mutable graph that will contain our models and meta-models:
+
+
+from state.devstate import DevState
+
+state = DevState()
+
+
+# Next, we must load the Simple Class Diagrams (SCD) meta-meta-model into our 'state'. The SCD meta-meta-model is a meta-model for our meta-model, and it is also a meta-model for itself.
+
+# The meta-meta-model is not specified in textual syntax because it is typed by itself, and the parser cannot resolve circular dependencies. Therefore, we load the meta-meta-model by mutating the 'state' directly at a very low level:
+
+from bootstrap.scd import bootstrap_scd
+
+print("Loading meta-meta-model...")
+mmm = bootstrap_scd(state)
+print("OK")
+
+# Now that the meta-meta-model has been loaded, we can parse our meta-model:
+
+from concrete_syntax.textual_od import parser
+
+print()
+print("Parsing 'woods' meta-model...")
+mm = parser.parse_od(
+    state,
+    m_text=mm_cs, # the string of text to parse
+    mm=mmm, # the meta-model of class diagrams (= our meta-meta-model)
+)
+print("OK")
+
+
+# And we can parse our model, the same way:
+
+print()
+print("Parsing 'woods' model...")
+m = parser.parse_od(
+    state,
+    m_text=m_cs,
+    mm=mm, # this time, the meta-model is the previous model we parsed
+)
+print("OK")
+
+
+# Now we can do a conformance check:
+
+from framework.conformance import Conformance, render_conformance_check_result
+
+print()
+print("Is our model a valid instance of our meta model?")
+conf = Conformance(state, m, mm)
+print(render_conformance_check_result(conf.check_nominal()))
+
+# Looks like it is OK!
+
+
+# We can also check if our meta-model is a valid class diagram:
+
+print()
+print("Is our meta-model a valid class diagram?")
+conf = Conformance(state, mm, mmm)
+print(render_conformance_check_result(conf.check_nominal()))
+
+# Also good.
+
+
+# Finally, we can even check if the meta-meta-model is a valid instance of itself (it should be):
+
+print()
+print("Is our meta-model a valid class diagram?")
+conf = Conformance(state, mmm, mmm)
+print(render_conformance_check_result(conf.check_nominal()))
+
+# All good!
+
+
+# Now let's make things a bit more interesting and introduce non-conformance:
+
+m2_cs = """
+    myA:A
+    myA2:A
+
+    myB:B
+
+    myLnk:a2b (myA -> myB)
+"""
+
+# Parse it:
+
+m2 = parser.parse_od(
+    state,
+    m_text=m2_cs,
+    mm=mm,
+)
+
+# The above model is non-conformant because 'myA2' should have at least one outgoing link of type 'a2b', but it doesn't.
+
+print()
+print("Is model 'm2' a valid instance of our meta-model? (it should not be)")
+conf = Conformance(state, m2, mm)
+print(render_conformance_check_result(conf.check_nominal()))
+
+# It should be non-conformant.
+
+
+# Finally, let's render everything as PlantUML:
+
+from concrete_syntax.plantuml import renderer as plantuml
+from concrete_syntax.plantuml.make_url import make_url
+
+uml = (""
+ + plantuml.render_package("Meta-model", plantuml.render_class_diagram(state, mm))
+ + plantuml.render_package("Model", plantuml.render_object_diagram(state, m, mm))
+ + plantuml.render_trace_conformance(state, m, mm)
+ # + plantuml.render_package("Meta-meta-model", plantuml.render_class_diagram(state, mmm))
+ # + plantuml.render_trace_conformance(state, mm, mmm)
+)
+
+print()
+print("PlantUML output:", make_url(uml))
+
+
+# On to the next tutorial...