finished petrinet simulation by introducing succes/failure of matches, and by finsihing the loop in the rule ordering

integration/code/pn_interface.alc

@@ -76,8 +76,9 @@ Element function printNode(tf_pn_model: Element, tf_pn_node: Element):
 			log(read_attribute(tf_pn_model, tf_pn_node_name, tf_pn_attributename))
 	return 0
 	
+Element pivots
 
-Boolean function node_match(transf_model : Element, transf_elem : Element, host_model : Element, host_elem : Element, pivots : Element):
+Boolean function node_match(transf_model : Element, transf_elem : Element, host_model : Element, host_elem : Element):
 
 	//type equality
 	String type1
@@ -252,9 +253,6 @@ Element function new_SearchState(OldSearchState : Element, TransfModel : Element
 	// copy pattern_size
 	dict_add(nss, "pattern_size", OldSearchState["pattern_size"])
 	
-	//copy pivots
-	dict_add(nss, "pivots",OldSearchState["pivots"])
-	
 	return nss
 
 Element function transf_vf2(SearchState: Element, transf_m : Element, host_m : Element):
@@ -298,7 +296,7 @@ Element function transf_vf2(SearchState: Element, transf_m : Element, host_m : E
 		while (index2 < list_len(host_list)):
 			host_node = list_read(host_list, index2)
 			index2= index2 + 1
-			if(node_match(transf_m, pattern_node, host_m, host_node, SearchState["pivots"])):
+			if(node_match(transf_m, pattern_node, host_m, host_node)):
 				nss = new_SearchState(SearchState, transf_m, pattern_node, host_m, host_node)
 				nss = transf_vf2(nss, transf_m, host_m)
 				dict_delete(SearchState, "matches")
@@ -311,7 +309,7 @@ Element function transf_vf2(SearchState: Element, transf_m : Element, host_m : E
 		while (index2 < list_len(host_list)):
 			host_node = list_read(host_list, index2)
 			index2= index2 + 1
-			if(node_match(transf_m, pattern_node, host_m, host_node, SearchState["pivots"])):
+			if(node_match(transf_m, pattern_node, host_m, host_node)):
 				nss = new_SearchState(SearchState, transf_m, pattern_node, host_m, host_node)
 				nss = transf_vf2(nss, transf_m, host_m)
 				dict_delete(SearchState, "matches")
@@ -324,7 +322,7 @@ Element function transf_vf2(SearchState: Element, transf_m : Element, host_m : E
 		while (index2 < list_len(host_list)):
 			host_node = list_read(host_list, index2)
 			index2= index2 + 1
-			if(node_match(transf_m, pattern_node, host_m, host_node, SearchState["pivots"])):
+			if(node_match(transf_m, pattern_node, host_m, host_node)):
 				nss = new_SearchState(SearchState, transf_m, pattern_node, host_m, host_node)
 				nss = transf_vf2(nss, transf_m, host_m)
 				dict_delete(SearchState, "matches")
@@ -335,7 +333,7 @@ Element function transf_vf2(SearchState: Element, transf_m : Element, host_m : E
 
 
 // given a pattern, this function will return all matches in a model
-Element function tf_matchAll(tf_ma_transformation: Element, tf_ma_pattern : Element, tf_ma_model: Element, pivots:Element ):
+Element function tf_matchAll(tf_ma_transformation: Element, tf_ma_pattern : Element, tf_ma_model: Element ):
 	
 	//find all nodes in the pattern
 	
@@ -380,7 +378,6 @@ Element function tf_matchAll(tf_ma_transformation: Element, tf_ma_pattern : Elem
 	dict_add(SearchState, "V_pattern", tf_ma_ramified_nodes)
 	dict_add(SearchState, "V_host", host_nodes)
 	dict_add(SearchState, "pattern_size", list_len(tf_ma_ramified_nodes))
-	dict_add(SearchState, "pivots", pivots)
 	
 	//call vf2 for the matching
 	
@@ -414,7 +411,7 @@ Element function mergeLHSNAC(tf_er_lhs : Element, tf_er_nac: Element):
 			list_append(final_matches, lhs_match)
 	return final_matches
 
-Element function extractPivots(final_matches : Element, pivots: Element, tf_er_transformation : Element, tf_er_model : Element):
+Element function extractPivots(final_matches : Element, tf_er_transformation : Element, tf_er_model : Element):
 	Integer match_index
 	match_index = 0
 	Element pattern_match_node
@@ -510,13 +507,15 @@ Element function rhs_rewrite(final_matches : Element,plabel_to_rhsnode:Element,
 				log("unsupported metatype in rhs")
 	return 0
 	
-Element function tf_executeFRule(tf_er_transformation: Element,tf_er_rule: Element, tf_er_model: Element, pivots : Element):
+Element function tf_executeFRule(tf_er_transformation: Element,tf_er_rule: Element, tf_er_model: Element):
 	
 	//find LHS
 	//TODO if no lhs (is this allowed to happen?) // or empty lhs
 	Element tf_er_lhs
 	tf_er_lhs = allOutgoingAssociationInstances(tf_er_transformation, tf_er_rule, dict_read(dict_read(dict_read(tf_er_transformation, "metamodel"), "model"), "lhs"))
-	tf_er_lhs = tf_matchAll(tf_er_transformation, read_edge_dst(set_pop(tf_er_lhs)), tf_er_model, pivots)
+	Integer nr_of_lhs_nodes
+	nr_of_lhs_nodes = read_nr_out(tf_er_lhs)
+	tf_er_lhs = tf_matchAll(tf_er_transformation, read_edge_dst(set_pop(tf_er_lhs)), tf_er_model)
 	Integer nr_of_lhs_matches
 	nr_of_lhs_matches = list_len(tf_er_lhs)
 	
@@ -530,18 +529,28 @@ Element function tf_executeFRule(tf_er_transformation: Element,tf_er_rule: Eleme
 		tf_er_nac_ = allOutgoingAssociationInstances(tf_er_transformation, tf_er_rule, dict_read(dict_read(dict_read(tf_er_transformation, "metamodel"), "model"), "nac"))
 		Element partial_nac_matches
 		while (read_nr_out(tf_er_nac_) > 0):
-			partial_nac_matches = tf_matchAll(tf_er_transformation, read_edge_dst(set_pop(tf_er_nac_)), tf_er_model, pivots)
+			partial_nac_matches = tf_matchAll(tf_er_transformation, read_edge_dst(set_pop(tf_er_nac_)), tf_er_model)
 			while (read_nr_out(partial_nac_matches)>0):
 				list_append(tf_er_nac, set_pop(partial_nac_matches))
 		nr_of_nac_matches = list_len(tf_er_nac)
-		
+	
+	if( nr_of_lhs_nodes == 0):
+		if (nr_of_nac_matches == 0):
+			return True
+		else:
+			return False
+	
 	//remove from lhs matches that share a node with a nac match
 	//TODO if nac is not related to match (no plabels match)
 	Element final_matches
 	final_matches = mergeLHSNAC(tf_er_lhs, tf_er_nac)
 	
+	if( read_nr_out(final_matches) == 0 ):
+		return False
+		
+	
 	//extract pivots from the matches
-	extractPivots(final_matches, pivots, tf_er_transformation, tf_er_model)
+	extractPivots(final_matches, tf_er_transformation, tf_er_model)
 
 	//rhs part
 	
@@ -566,7 +575,7 @@ Element function tf_executeFRule(tf_er_transformation: Element,tf_er_rule: Eleme
 		
 		rhs_rewrite(final_matches ,plabel_to_rhsnode, tf_er_transformation, tf_er_model )
 		
-	return pivots
+	return True
 
 Integer function modulo(a:Integer,b:Integer):
 	return a - integer_division(a,b)*b
@@ -585,13 +594,14 @@ Element function list_select_random(list:Element):
 	return list_read(list, getRandomNumber(0,read_nr_out(list)))
 
 
-Element function tf_executeARule(tf_er_transformation: Element,tf_er_rule: Element, tf_er_model: Element, pivots : Element):
+Element function tf_executeARule(tf_er_transformation: Element,tf_er_rule: Element, tf_er_model: Element):
 	
 	//find LHS
-	//TODO if no lhs (is this allowed to happen?) // or empty lhs
 	Element tf_er_lhs
 	tf_er_lhs = allOutgoingAssociationInstances(tf_er_transformation, tf_er_rule, dict_read(dict_read(dict_read(tf_er_transformation, "metamodel"), "model"), "lhs"))
-	tf_er_lhs = tf_matchAll(tf_er_transformation, read_edge_dst(set_pop(tf_er_lhs)), tf_er_model, pivots)
+	Integer nr_of_lhs_nodes
+	nr_of_lhs_nodes = read_nr_out(tf_er_lhs)
+	tf_er_lhs = tf_matchAll(tf_er_transformation, read_edge_dst(set_pop(tf_er_lhs)), tf_er_model)
 	Integer nr_of_lhs_matches
 	nr_of_lhs_matches = list_len(tf_er_lhs)
 	
@@ -605,16 +615,25 @@ Element function tf_executeARule(tf_er_transformation: Element,tf_er_rule: Eleme
 		tf_er_nac_ = allOutgoingAssociationInstances(tf_er_transformation, tf_er_rule, dict_read(dict_read(dict_read(tf_er_transformation, "metamodel"), "model"), "nac"))
 		Element partial_nac_matches
 		while (read_nr_out(tf_er_nac_) > 0):
-			partial_nac_matches = tf_matchAll(tf_er_transformation, read_edge_dst(set_pop(tf_er_nac_)), tf_er_model, pivots)
+			partial_nac_matches = tf_matchAll(tf_er_transformation, read_edge_dst(set_pop(tf_er_nac_)), tf_er_model)
 			while (read_nr_out(partial_nac_matches)>0):
 				list_append(tf_er_nac, set_pop(partial_nac_matches))
 		nr_of_nac_matches = list_len(tf_er_nac)
 		
+	if( nr_of_lhs_nodes == 0):
+		if (nr_of_nac_matches == 0):
+			return True
+		else:
+			return False
+	
 	//remove from lhs matches that share a node with a nac match
 	//TODO if nac is not related to match (no plabels match)
 	Element final_matches
 	final_matches = mergeLHSNAC(tf_er_lhs, tf_er_nac)
 	
+	if( read_nr_out(final_matches) == 0 ):
+		return False
+	
 	//select only one match
 	Element selected 
 	selected = list_select_random(final_matches)
@@ -623,7 +642,7 @@ Element function tf_executeARule(tf_er_transformation: Element,tf_er_rule: Eleme
 	
 	
 	//extract pivots from the matches
-	extractPivots(final_matches, pivots, tf_er_transformation, tf_er_model)
+	extractPivots(final_matches, tf_er_transformation, tf_er_model)
 
 	//rhs part
 	
@@ -648,9 +667,9 @@ Element function tf_executeARule(tf_er_transformation: Element,tf_er_rule: Eleme
 		
 		rhs_rewrite(final_matches ,plabel_to_rhsnode, tf_er_transformation, tf_er_model )
 		
-	return pivots
+	return True
 
-Element function executeRuleBlock(transformation_model : Element,hostmodel:Element, ruleblock : Element, pivots:Element):
+Element function executeRuleBlock(transformation_model : Element,hostmodel:Element, ruleblock : Element):
 	//execute the correct ruletype
 	//TODO define decent succes_value
 	String typename
@@ -660,22 +679,21 @@ Element function executeRuleBlock(transformation_model : Element,hostmodel:Eleme
 	Element Rule
 	if (typename == "RuleBlockRoot"):
 		// do nothing
-		log("start transformation")
+		log("= startinging transformation")
 		succes = True
 	elif (typename == "ARule"):
-		log("running arule")
+		log("= running ARule")
 		Rule = read_edge_dst(set_pop(allOutgoingAssociationInstances(transformation_model, ruleblock, transformation_model["metamodel"]["model"]["getrule"])))
 		log(getName(transformation_model, Rule))
-		pivots = tf_executeARule(transformation_model, Rule, hostmodel, pivots)
-		succes = True
+		succes = tf_executeARule(transformation_model, Rule, hostmodel)
 	elif (typename == "FRule"):
-		log("running frule")
+		log("= running FRule")
 		Rule = read_edge_dst(set_pop(allOutgoingAssociationInstances(transformation_model, ruleblock, transformation_model["metamodel"]["model"]["getrule"])))
 		log(getName(transformation_model, Rule))
-		pivots = tf_executeFRule(transformation_model, Rule, hostmodel, pivots)
-		succes = True
+		succes = tf_executeFRule(transformation_model, Rule, hostmodel)
 	else:
 		log("RuleType is not supported yet")
+	
 	//Return the next
 	Element next
 	if succes: 
@@ -683,7 +701,6 @@ Element function executeRuleBlock(transformation_model : Element,hostmodel:Eleme
 	else:
 		next = allOutgoingAssociationInstances(transformation_model, ruleblock, transformation_model["metamodel"]["model"]["next_onFailure"])
 	if (read_nr_out(next) == 0):
-		log("No next defined")
 		next = transformation_model
 	else:
 		next = read_edge_dst(set_pop(next))
@@ -696,12 +713,11 @@ Element function tf_transform(tf_tf_transformation: Element, tf_tf_model: Elemen
 	ruleblock = allInstances(tf_tf_transformation, tf_tf_transformation["metamodel"]["model"]["RuleBlockRoot"])
 	if(read_nr_out(ruleblock) > 0):
 		ruleblock = set_pop(ruleblock)
-		Element pivots
 		pivots = create_node()
 		Boolean continue
 		continue = True
 		while (continue):
-			ruleblock = executeRuleBlock(tf_tf_transformation,tf_tf_model, ruleblock, pivots)
+			ruleblock = executeRuleBlock(tf_tf_transformation,tf_tf_model, ruleblock)
 			if(element_eq(ruleblock,tf_tf_transformation)):
 				log("finished")
 				continue = False
@@ -993,6 +1009,14 @@ Element function petrinet_transformation(root: Element):
 	//connect to rule
 	instantiate_link(my_model, "getrule","", "frule3", "produce_tokens")
 	
+	//create circularity link
+	instantiate_link(my_model, "next_onSucces", "",  "frule3",  "arule1")
+	//if you cannot consume, still try to produce (for source transitions)
+	instantiate_link(my_model, "next_onFailure", "",  "frule2",  "frule3")
+	//if you cannot produce, still check for other transitions (it might have consumed already)
+	instantiate_link(my_model, "next_onFailure", "",  "frule3",  "arule1")
+	
+	
 	
 	////////////////////////////
 	// semantic checks
@@ -1060,9 +1084,6 @@ Element function add_tokens(model:Element, self: Element):
 	unset_attribute(model, getName(model, place_after), "tokens")
 	instantiate_attribute(model, getName(model, place_after), "tokens", tokens+weight)
 	return 0
-	
-	
-	
 
 Element function pn_operations():
 	Element ops