Abstract away Object Diagram pattern matching in a function that does all the magic
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3 changed files with 89 additions and 101 deletions
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@ -137,18 +137,6 @@ def main():
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conf4 = Conformance(state, rhs_id, ramified_mm_id)
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print("RHS conforms?", conf4.check_nominal(log=True))
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# Convert to format understood by matching algorithm
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host = mvs_adapter.model_to_graph(state, dsl_m_id, dsl_mm_id)
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guest = mvs_adapter.model_to_graph(state, lhs_id, ramified_mm_id)
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print("HOST:")
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print(host.vtxs)
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print(host.edges)
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print("GUEST:")
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print(guest.vtxs)
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print(guest.edges)
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def render_ramification():
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uml = (""
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# Render original and RAMified meta-models
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@ -177,16 +165,9 @@ def main():
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uml += plantuml.render_trace_conformance(state, dsl_m_id, dsl_mm_id)
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print("matching...")
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matcher = MatcherVF2(host, guest, mvs_adapter.RAMCompare(Bottom(state), dsl_m_od))
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for m, color in zip(matcher.match(), ["red", "orange"]):
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print("\nMATCH:\n", m)
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name_mapping = {}
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# id_mapping = {}
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for guest_vtx, host_vtx in m.mapping_vtxs.items():
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if isinstance(guest_vtx, mvs_adapter.NamedNode) and isinstance(host_vtx, mvs_adapter.NamedNode):
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# id_mapping[guest_vtx.node_id] = host_vtx.node_id
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name_mapping[guest_vtx.name] = host_vtx.name
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print(name_mapping)
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generator = mvs_adapter.match_od(state, dsl_m_id, dsl_mm_id, lhs_id, ramified_mm_id)
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for name_mapping, color in zip(generator, ["red", "orange"]):
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print("\nMATCH:\n", name_mapping)
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# Render every match
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uml += plantuml.render_trace_match(state, name_mapping, lhs_id, dsl_m_id, color)
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@ -197,17 +178,8 @@ def main():
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def render_rewrite():
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uml = render_ramification()
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matcher = MatcherVF2(host, guest, mvs_adapter.RAMCompare(Bottom(state), dsl_m_od))
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for m in matcher.match():
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name_mapping = {}
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# id_mapping = {}
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for guest_vtx, host_vtx in m.mapping_vtxs.items():
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if isinstance(guest_vtx, mvs_adapter.NamedNode) and isinstance(host_vtx, mvs_adapter.NamedNode):
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# id_mapping[guest_vtx.node_id] = host_vtx.node_id
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name_mapping[guest_vtx.name] = host_vtx.name
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print(name_mapping)
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generator = mvs_adapter.match_od(state, dsl_m_id, dsl_mm_id, lhs_id, ramified_mm_id)
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for name_mapping in generator:
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rewriter.rewrite(state, lhs_id, rhs_id, ramified_mm_id, name_mapping, dsl_m_id, dsl_mm_id)
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# Render match
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@ -3,7 +3,7 @@ from uuid import UUID
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from services.bottom.V0 import Bottom
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from services.scd import SCD
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from services.od import OD
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from pattern_matching.matcher import Graph, Edge, Vertex
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from pattern_matching.matcher import Graph, Edge, Vertex, MatcherVF2
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from transformation import ramify
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import itertools
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import re
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@ -188,87 +188,103 @@ def model_to_graph(state: State, model: UUID, metamodel: UUID, prefix=""):
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return graph
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# Function object for pattern matching. Decides whether to match host and guest vertices, where guest is a RAMified instance (e.g., the attributes are all strings with Python expressions), and the host is an instance (=object diagram) of the original model (=class diagram)
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class RAMCompare:
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def __init__(self, bottom, host_od):
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self.bottom = bottom
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self.host_od = host_od
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type_model_id = bottom.state.read_dict(bottom.state.read_root(), "SCD")
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self.scd_model = UUID(bottom.state.read_value(type_model_id))
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def match_od(state, host_m, host_mm, pattern_m, pattern_mm):
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# Function object for pattern matching. Decides whether to match host and guest vertices, where guest is a RAMified instance (e.g., the attributes are all strings with Python expressions), and the host is an instance (=object diagram) of the original model (=class diagram)
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class RAMCompare:
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def __init__(self, bottom, host_od):
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self.bottom = bottom
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self.host_od = host_od
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def is_subtype_of(self, supposed_subtype: UUID, supposed_supertype: UUID):
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if supposed_subtype == supposed_supertype:
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# reflexive:
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return True
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type_model_id = bottom.state.read_dict(bottom.state.read_root(), "SCD")
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self.scd_model = UUID(bottom.state.read_value(type_model_id))
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inheritance_node, = self.bottom.read_outgoing_elements(self.scd_model, "Inheritance")
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def is_subtype_of(self, supposed_subtype: UUID, supposed_supertype: UUID):
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if supposed_subtype == supposed_supertype:
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# reflexive:
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return True
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for outgoing in self.bottom.read_outgoing_edges(supposed_subtype):
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if inheritance_node in self.bottom.read_outgoing_elements(outgoing, "Morphism"):
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# 'outgoing' is an inheritance link
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supertype = self.bottom.read_edge_target(outgoing)
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if supertype != supposed_subtype:
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if self.is_subtype_of(supertype, supposed_supertype):
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return True
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inheritance_node, = self.bottom.read_outgoing_elements(self.scd_model, "Inheritance")
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return False
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for outgoing in self.bottom.read_outgoing_edges(supposed_subtype):
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if inheritance_node in self.bottom.read_outgoing_elements(outgoing, "Morphism"):
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# 'outgoing' is an inheritance link
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supertype = self.bottom.read_edge_target(outgoing)
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if supertype != supposed_subtype:
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if self.is_subtype_of(supertype, supposed_supertype):
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return True
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def match_types(self, g_vtx_type, h_vtx_type):
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# types only match with their supertypes
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# we assume that 'RAMifies'-traceability links have been created between guest and host types
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try:
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g_vtx_original_type = ramify.get_original_type(self.bottom, g_vtx_type)
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except:
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return False
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return self.is_subtype_of(h_vtx_type, g_vtx_original_type)
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# Memoizing the result of comparison gives a huge performance boost!
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# Especially `is_subtype_of` is very slow, and will be performed many times over on the same pair of nodes during the matching process.
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# Assuming the model is not altered *during* matching, this is safe.
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@functools.cache
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def __call__(self, g_vtx, h_vtx):
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# First check if the types match (if we have type-information)
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if hasattr(g_vtx, 'typ'):
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if not hasattr(h_vtx, 'typ'):
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# if guest has a type, host must have a type
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def match_types(self, g_vtx_type, h_vtx_type):
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# types only match with their supertypes
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# we assume that 'RAMifies'-traceability links have been created between guest and host types
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try:
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g_vtx_original_type = ramify.get_original_type(self.bottom, g_vtx_type)
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except:
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return False
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return self.match_types(g_vtx.typ, h_vtx.typ)
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# Then, match by value
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return self.is_subtype_of(h_vtx_type, g_vtx_original_type)
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if g_vtx.value == None:
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return h_vtx.value == None
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# mvs-edges (which are converted to vertices) only match with mvs-edges
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if g_vtx.value == IS_EDGE:
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return h_vtx.value == IS_EDGE
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# Memoizing the result of comparison gives a huge performance boost!
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# Especially `is_subtype_of` is very slow, and will be performed many times over on the same pair of nodes during the matching process.
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# Assuming the model is not altered *during* matching, this is safe.
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@functools.cache
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def __call__(self, g_vtx, h_vtx):
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# First check if the types match (if we have type-information)
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if hasattr(g_vtx, 'typ'):
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if not hasattr(h_vtx, 'typ'):
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# if guest has a type, host must have a type
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return False
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return self.match_types(g_vtx.typ, h_vtx.typ)
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if h_vtx.value == IS_EDGE:
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return False
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# Then, match by value
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if g_vtx.value == IS_MODELREF:
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return h_vtx.value == IS_MODELREF
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if g_vtx.value == None:
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return h_vtx.value == None
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if h_vtx.value == IS_MODELREF:
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return False
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# mvs-edges (which are converted to vertices) only match with mvs-edges
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if g_vtx.value == IS_EDGE:
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return h_vtx.value == IS_EDGE
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# print(g_vtx.value, h_vtx.value)
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def get_slot(h_vtx, slot_name: str):
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slot_node = self.host_od.get_slot(h_vtx.node_id, slot_name)
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return slot_node
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if h_vtx.value == IS_EDGE:
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return False
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def read_int(slot: UUID):
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i = Integer(slot, self.bottom.state)
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return i.read()
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if g_vtx.value == IS_MODELREF:
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return h_vtx.value == IS_MODELREF
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try:
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return eval(g_vtx.value, {}, {
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'v': h_vtx.value,
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'get_slot': functools.partial(get_slot, h_vtx),
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'read_int': read_int,
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})
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except Exception as e:
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return False
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if h_vtx.value == IS_MODELREF:
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return False
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# print(g_vtx.value, h_vtx.value)
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def get_slot(h_vtx, slot_name: str):
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slot_node = self.host_od.get_slot(h_vtx.node_id, slot_name)
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return slot_node
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def read_int(slot: UUID):
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i = Integer(slot, self.bottom.state)
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return i.read()
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try:
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return eval(g_vtx.value, {}, {
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'v': h_vtx.value,
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'get_slot': functools.partial(get_slot, h_vtx),
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'read_int': read_int,
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})
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except Exception as e:
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return False
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# Convert to format understood by matching algorithm
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host = model_to_graph(state, host_m, host_mm)
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guest = model_to_graph(state, pattern_m, pattern_mm)
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matcher = MatcherVF2(host, guest, RAMCompare(Bottom(state), OD(host_mm, host_m, state)))
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for m in matcher.match():
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# print("\nMATCH:\n", m)
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# Convert mapping
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name_mapping = {}
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for guest_vtx, host_vtx in m.mapping_vtxs.items():
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if isinstance(guest_vtx, NamedNode) and isinstance(host_vtx, NamedNode):
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name_mapping[guest_vtx.name] = host_vtx.name
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yield name_mapping
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@ -25,7 +25,7 @@ def process_rule(state, lhs: UUID, rhs: UUID):
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# Rewrite is performed in-place
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# Also updates the mapping in-place, to become RHS -> host
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def rewrite(state, lhs: UUID, rhs: UUID, rhs_mm: UUID, match_mapping: dict, m_to_transform: UUID, mm: UUID) -> dict:
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def rewrite(state, lhs: UUID, rhs: UUID, rhs_mm: UUID, match_mapping: dict, m_to_transform: UUID, mm: UUID):
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bottom = Bottom(state)
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scd_metamodel_id = state.read_dict(state.read_root(), "SCD")
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