Browse Source

Add new simplified MM and transformations

Yentl Van Tendeloo 5 years ago
parent
commit
26545926fd

+ 22 - 0
examples/upload_simple_formalisms.py

@@ -0,0 +1,22 @@
+import sys
+sys.path.append("wrappers")
+from modelverse import *
+
+init()
+login("admin", "admin")
+
+model_add("formalisms/FSA/MM", "formalisms/SimpleClassDiagrams", open("models/FiniteStateAutomata/metamodels/simple.mvc", 'r').read())
+transformation_add_AL({"FSA": "formalisms/FSA/MM"}, {}, "formalisms/FSA/simulate", open("models/FiniteStateAutomata/transformations/simple_simulate.alc", 'r').read())
+
+model_add("formalisms/DTCBD/MM", "formalisms/SimpleClassDiagrams", open("models/DTCBD/metamodels/DTCBD_MM.mvc", 'r').read())
+transformation_add_AL({"DTCBD": "formalisms/DTCBD/MM"}, {}, "formalisms/DTCBD/simulate", open("models/DTCBD/transformations/simple_simulate.alc", 'r').read())
+
+model_add("formalisms/CTCBD/MM", "formalisms/SimpleClassDiagrams", open("models/CTCBD/metamodels/CTCBD_MM.mvc", 'r').read())
+transformation_add_MT({"Design": "formalisms/CTCBD/MM"}, {"PartialRuntime": "formalisms/DTCBD/MM"}, "formalisms/CTCBD/discretize", open("models/CTCBD/transformations/to_partial_runtime.mvc", 'r').read())
+
+model_add("formalisms/PN/MM", "formalisms/SimpleClassDiagrams", open("models/PetriNets/metamodels/PetriNets.mvc", 'r').read())
+transformation_add_AL({"PN": "formalisms/PN/MM"}, {"PN": "formalisms/PN/MM"}, "formalisms/PN/simulate", open("models/PetriNets/transformations/simple_simulate.alc", 'r').read())
+
+model_add("formalisms/Query", "formalisms/SimpleClassDiagrams", open("models/SafetyQuery/metamodels/query.mvc", 'r').read())
+model_add("formalisms/PNPath", "formalisms/SimpleClassDiagrams", open("models/PNPath/metamodels/PNPath.mvc", 'r').read())
+transformation_add_AL({"PN": "formalisms/PN/MM", "Query": "formalisms/Query"}, {"Path": "formalisms/PNPath"}, "models/analyze_lola", open("models/PetriNets/transformations/analyze_lola.alc", 'r').read())

+ 570 - 0
models/DTCBD/transformations/simple_simulate.alc

@@ -0,0 +1,570 @@
+include "primitives.alh"
+include "modelling.alh"
+include "object_operations.alh"
+include "conformance_scd.alh"
+include "io.alh"
+include "metamodels.alh"
+include "mini_modify.alh"
+include "utils.alh"
+
+Boolean function main(model : Element):
+	String cmd
+	Boolean running
+	Element schedule_init
+	Element schedule_run
+	Element schedule
+	Float current_time
+
+	String time
+	current_time = 0.0
+
+	schedule_init = create_schedule(model)
+	schedule_run = read_root()
+
+	Element nodes
+	Element inputs
+	String node
+	nodes = allInstances(model, "DTCBD/Block")
+	inputs = dict_create()
+	while (set_len(nodes) > 0):
+		node = set_pop(nodes)
+		dict_add(inputs, node, allAssociationOrigins(model, node, "DTCBD/Link"))
+
+	while (bool_not(has_input())):
+		if (read_attribute(model, time, "start_time") == read_attribute(model, time, "current_time")):
+			schedule = schedule_init
+		else:
+			if (element_eq(schedule_run, read_root())):
+				schedule_run = create_schedule(model)
+			schedule = schedule_run
+		current_time = step_simulation(model, schedule, current_time, inputs)
+
+	output("CLOSE")
+	return True!
+
+Element function create_schedule(model : Element):
+	// Create nice graph first
+	Element nodes
+	Element successors
+	String element_name
+	Element incoming_links
+	Element all_blocks
+
+	nodes = allInstances(model, "DTCBD/Block")
+	successors = set_create()
+	while (set_len(nodes) > 0):
+		element_name = set_pop(nodes)
+
+		if (is_nominal_instance(model, element_name, "DTCBD/ICBlock")):
+			if (bool_not(is_physical_float(read_attribute(model, element_name, "last_in")))):
+				incoming_links = allIncomingAssociationInstances(model, element_name, "DTCBD/InitialCondition")
+			else:
+				incoming_links = create_node()
+		else:
+			incoming_links = allIncomingAssociationInstances(model, element_name, "DTCBD/Link")
+
+		while (set_len(incoming_links) > 0):
+			String source
+			source = readAssociationSource(model, set_pop(incoming_links))
+			list_append(successors, create_tuple(source, element_name))
+
+	Element values
+	values = create_node()
+
+	dict_add(values, "edges", successors)
+	dict_add(values, "nodes", allInstances(model, "DTCBD/Block"))
+	dict_add(values, "dfsCounter", 0)
+	dict_add(values, "orderNumber", dict_create())
+	dict_add(values, "visited_topSort", set_create())
+	dict_add(values, "unvisited_strongComp", set_create())
+
+	dict_overwrite(values, "SCC", strongComp(values))
+
+	return values["SCC"]!
+
+Void function topSort(values : Element):
+	Element nodes_copy
+	String node
+
+	dict_overwrite(values, "visited_topSort", set_create())
+
+	nodes_copy = set_copy(values["nodes"])
+	while (set_len(nodes_copy) > 0):
+		node = set_pop(nodes_copy)
+		if (bool_not(set_in(values["visited_topSort"], node))):
+			dfsLabelling(values, node)
+
+	return!
+
+Element function get_successors(values : Element, node : String, key : String):
+	Element edges
+	Element result
+	String edge
+
+	result = set_create()
+	edges = list_copy(values[key])
+	while (list_len(edges) > 0):
+		edge = list_pop_final(edges)
+		if (cast_string(edge[0]) == node):
+			set_add(result, edge[1])
+
+	return result!
+
+Void function dfsLabelling(values : Element, node : String):
+	Element successors
+	String successor
+
+	// if not node.visited
+	if (bool_not(set_in(values["visited_topSort"], node))):
+		// node.visited = True
+		set_add(values["visited_topSort"], node)
+
+		// for neighbour in node.out_neighbours:
+		//     dfsLabelling(neighbour, graph)
+		successors = get_successors(values, node, "edges")
+		while (set_len(successors) > 0):
+			successor = set_pop(successors)
+			dfsLabelling(values, successor)
+
+		// node.orderNumber = dfsCounter
+		dict_overwrite(values["orderNumber"], node, values["dfsCounter"])
+
+		// dfsCounter += 1
+		dict_overwrite(values, "dfsCounter", cast_integer(values["dfsCounter"]) + 1)
+
+	return !
+
+Element function dfsCollect(values : Element, start_node : String):
+	Element result
+	String successor
+	Element successors
+
+	result = set_create()
+
+	// if not node.visited
+	if (set_in(values["unvisited_strongComp"], start_node)):
+		list_append(result, start_node)
+		// node.visited = True
+		set_remove(values["unvisited_strongComp"], start_node)
+
+		// for neighbour in node.out_neighbours:
+		//     dfsLabelling(neighbour, graph)
+		successors = get_successors(values, start_node, "rev_edges")
+		while (set_len(successors) > 0):
+			successor = set_pop(successors)
+			list_extend(result, dfsCollect(values, successor))
+
+	return result!
+
+String function highest_orderNumber(values : Element):
+	Integer max
+	String max_element
+	Element search
+	String elem
+
+	max = -1
+	search = set_copy(values["unvisited_strongComp"])
+	while (set_len(search) > 0):
+		elem = set_pop(search)
+		if (cast_integer(values["orderNumber"][elem]) > max):
+			max = values["orderNumber"][elem]
+			max_element = elem
+		
+	return max_element!
+
+Element function reverse_edges(edges : Element):
+	Element result
+	Element elem
+
+	result = list_create()
+	edges = list_copy(edges)
+	while (list_len(edges) > 0):
+		elem = list_pop_final(edges)
+		list_append(result, create_tuple(elem[1], elem[0]))
+	return result!
+
+Element function strongComp(values : Element):
+	Element graph
+	Element sccs
+	String start_node
+	Element strong_components
+	Element component
+
+	sccs = list_create()
+
+	topSort(values)
+
+	dict_overwrite(values, "unvisited_strongComp", set_copy(values["nodes"]))
+
+	dict_overwrite(values, "rev_edges", reverse_edges(values["edges"]))
+	strong_components = list_create()
+
+	while (set_len(values["unvisited_strongComp"]) > 0):
+		start_node = highest_orderNumber(values)
+
+		component = dfsCollect(values, start_node)
+		list_append(sccs, component)
+
+	return sccs!
+
+Element function get_topolist(values : Element):
+	Element result
+	Element predecessors
+	Element remaining
+	String current_element
+	Element cur_predecessors
+
+	result = list_create()
+	predecessors = dict_copy(values["predecessors"])
+
+	while (dict_len(predecessors) > 0):
+		remaining = dict_keys(predecessors)
+		while (set_len(remaining) > 0):
+			current_element = set_pop(remaining)
+			cur_predecessors = predecessors[current_element]
+			if (set_len(set_overlap(list_to_set(result), cur_predecessors)) == set_len(cur_predecessors)):
+				// All predecessors of this node have already been visited
+				dict_delete(predecessors, current_element)
+				remaining = dict_keys(predecessors)
+				list_append(result, current_element)
+
+	return result!
+
+Integer function min(a : Integer, b : Integer):
+	if (a < b):
+		return a!
+	else:
+		return b!
+
+Void function strongconnect(v : String, values : Element):
+	// if (v.index is undefined) then
+	//    strongconnect(V)
+	if (dict_in(values["indices"], v)):
+		return!
+
+	// v.index := index
+	dict_overwrite(values["indices"], v, values["index"])
+	// v.lowlink := indwx
+	dict_overwrite(values["lowlink"], v, values["index"])
+	// index := index + 1
+	dict_overwrite(values, "index", cast_integer(values["index"]) + 1)
+
+	// S.push(v)
+	list_append(values["S"], v)
+	// v.onStack := true
+	dict_overwrite(values["onStack"], v, True)
+	
+	Element successors
+	String w
+	successors = values["successors"][v]
+	while (set_len(successors) > 0):
+		// for each (v, w) in E do
+		w = set_pop(successors)
+		// if (w.index is undefined) then
+		if (bool_not(dict_in(values["indices"], w))):
+			// strongconnect(w)
+			strongconnect(w, values)
+			// v.lowlink := min(v.lowlink, w.lowlink)
+			dict_overwrite(values["lowlink"], v, min(values["lowlink"][v], values["lowlink"][w]))
+		elif (dict_in(values["onStack"], w)):
+			// else if (w.onStack)
+			if (values["onStack"][w]):
+				// v.lowlink := min(v.lowlink, w.index)
+				dict_overwrite(values["lowlink"], v, min(values["lowlink"][v], values["indices"][w]))
+	
+	// if (v.lowlink == v.index) then
+	if (value_eq(values["lowlink"][v], values["indices"][v])):
+		Element scc
+		// Start a new strongly connected component
+		scc = create_node()
+		// It will always differ now
+		// w := S.pop()
+		w = list_pop_final(values["S"])
+		// w.onStack = false
+		dict_overwrite(values["onStack"], w, False)
+		// add w to current strongly connected component
+		list_append(scc, w)
+		// while w != v
+		while (w != v):
+			// w := S.pop()
+			w = list_pop_final(values["S"])
+			// w.onStack = false
+			dict_overwrite(values["onStack"], w, False)
+			// add w to current strongly connected component
+			list_append(scc, w)
+		// output the current strongly connected component
+		list_insert(values["SCC"], scc, 0)
+	return!
+
+Boolean function solve_scc(model : Element, scc : Element):
+	Element m
+	Integer i
+	Integer j
+	String block
+	String blocktype
+	Element incoming
+	String selected
+	Float constant
+	Element t
+
+	// Construct the matrix first, with as many rows as there are variables
+	// Number of columns is 1 higher
+	i = 0
+	m = create_node()
+	while (i < read_nr_out(scc)):
+		j = 0
+		t = create_node()
+		while (j < (read_nr_out(scc) + 1)):
+			list_append(t, 0.0)
+			j = j + 1
+		list_append(m, t)
+		i = i + 1
+
+	// Matrix initialized to 0.0
+	i = 0
+	while (i < read_nr_out(scc)):
+		// First element of scc
+		block = scc[i]
+		blocktype = read_type(model, block)
+
+		// First write 1 in the current block
+		dict_overwrite(m[i], i, 1.0)
+
+		// Now check all blocks that are incoming
+		if (blocktype == "DTCBD/AdditionBlock"):
+			constant = 0.0
+		elif (blocktype == "DTCBD/MultiplyBlock"):
+			constant = 1.0
+
+		incoming = allIncomingAssociationInstances(model, block, "DTCBD/Link")
+
+		Integer index_to_write_constant
+		index_to_write_constant = -1
+		while (read_nr_out(incoming) > 0):
+			selected = readAssociationSource(model, set_pop(incoming))
+
+			if (list_in(scc, selected)):
+				// Part of the loop, so in the index of selected in scc
+				// Five options:
+				if (blocktype == "DTCBD/AdditionBlock"):
+					// 1) AdditionBlock
+					// Add the negative of this signal, which is as of yet unknown
+					// x = y + z --> x - y - z = 0
+					dict_overwrite(m[i], list_index_of(scc, selected), -1.0)
+				elif (blocktype == "DTCBD/MultiplyBlock"):
+					// 2) MultiplyBlock
+					if (index_to_write_constant != -1):
+						return False!
+					index_to_write_constant = list_index_of(scc, selected)
+				elif (blocktype == "DTCBD/NegatorBlock"):
+					// 3) NegatorBlock
+					// Add the positive of the signal, which is as of yet unknown
+					dict_overwrite(m[i], list_index_of(scc, selected), 1.0)
+				elif (blocktype == "DTCBD/DelayBlock"):
+					// 5) DelayBlock
+					// Just copies a single value
+					dict_overwrite(m[i], list_index_of(scc, selected), -1.0)
+				else:
+					// Block that cannot be handled
+					return False!
+			else:
+				// A constant, which we can assume is already computed and thus usable
+				if (blocktype == "DTCBD/AdditionBlock"):
+					constant = constant + cast_float(read_attribute(model, selected, "signal"))
+					dict_overwrite(m[i], read_nr_out(scc), constant)
+				elif (blocktype == "DTCBD/MultiplyBlock"):
+					constant = constant * cast_float(read_attribute(model, selected, "signal"))
+					// Not written to constant part, as multiplies a variable
+
+				// Any other block is impossible:
+				// * Constant would never be part of a SCC
+				// * Delay would never get an incoming constant
+				// * Negation and Inverse only get 1 input, which is a variable in a loop
+				// * Integrator and Derivator never get an incoming constant
+
+		if (index_to_write_constant != -1):
+			dict_overwrite(m[i], index_to_write_constant, -constant)
+
+		i = i + 1
+
+	// Solve matrix now
+	eliminateGaussJordan(m)
+
+	// Now go over m and set signals for each element
+	// Assume that everything worked out...
+	i = 0
+	while (i < read_nr_out(m)):
+		block = scc[i]
+		instantiate_attribute(model, block, "signal", m[i][read_nr_out(scc)])
+		i = i + 1
+
+	return True!
+
+Integer function list_index_of(lst : Element, elem : Element):
+	Integer i
+	i = 0
+	while (i < read_nr_out(lst)):
+		if (value_eq(list_read(lst, i), elem)):
+			return i!
+		else:
+			i = i + 1
+	return -1!
+
+Float function step_simulation(model : Element, schedule : Element, time : Float, inputs : Element):
+	Float signal
+	Element incoming
+	String selected
+	String block
+	String elem
+	String blocktype
+	Element memory_blocks
+	Integer i
+	Float delta_t
+	Element scc
+
+	delta_t = 0.1
+
+	memory_blocks = set_create()
+	i = 0
+	while (i < list_len(schedule)):
+		scc = list_read(schedule, i)
+		i = i + 1
+
+		if (list_len(scc) > 1):
+			if (bool_not(solve_scc(model, scc))):
+				output("ALGEBRAIC_LOOP")
+				return time!
+		else:
+			block = list_read(scc, 0)
+
+			// Execute "block"
+			blocktype = read_type(model, block)
+			incoming = set_copy(inputs[block])
+			if (blocktype == "DTCBD/ConstantBlock"):
+				signal = cast_float(read_attribute(model, block, "value"))
+			elif (blocktype == "DTCBD/AdditionBlock"):
+				signal = 0.0
+				while (set_len(incoming) > 0):
+					selected = set_pop(incoming)
+					signal = signal + cast_float(read_attribute(model, selected, "signal"))
+			elif (blocktype == "DTCBD/MultiplyBlock"):
+				signal = 1.0
+				while (set_len(incoming) > 0):
+					selected = set_pop(incoming)
+					signal = signal * cast_float(read_attribute(model, selected, "signal"))
+			elif (blocktype == "DTCBD/NegatorBlock"):
+				signal = 0.0
+				while (set_len(incoming) > 0):
+					selected = set_pop(incoming)
+					signal = float_neg(cast_float(read_attribute(model, selected, "signal")))
+			elif (blocktype == "DTCBD/InverseBlock"):
+				signal = 0.0
+				while (set_len(incoming) > 0):
+					selected = set_pop(incoming)
+					signal = float_division(1.0, cast_float(read_attribute(model, selected, "signal")))
+			elif (blocktype == "DTCBD/DelayBlock"):
+				signal = 0.0
+				if (bool_not(is_physical_float(read_attribute(model, block, "last_in")))):
+					// No memory yet, so use initial condition
+					incoming = allAssociationOrigins(model, block, "DTCBD/InitialCondition")
+					while (set_len(incoming) > 0):
+						selected = set_pop(incoming)
+						signal = cast_float(read_attribute(model, selected, "signal"))
+				else:
+					signal = read_attribute(model, block, "last_in")
+				set_add(memory_blocks, block)
+			elif (blocktype == "DTCBD/ProbeBlock"):
+				signal = 0.0
+				while (set_len(incoming) > 0):
+					signal = cast_float(read_attribute(model, set_pop(incoming), "signal"))
+					output(cast_string(time) + " " + cast_string(read_attribute(model, block, "name")) + " " + cast_string(signal))
+					log(cast_string(time) + " " + cast_string(read_attribute(model, block, "name")) + " " + cast_string(signal))
+
+			instantiate_attribute(model, block, "signal", signal)
+	
+	while (set_len(memory_blocks) > 0):
+		block = set_pop(memory_blocks)
+		// Update memory
+		incoming = set_copy(inputs[block])
+		while (set_len(incoming) > 0):
+			selected = set_pop(incoming)
+			instantiate_attribute(model, block, "last_in", cast_float(read_attribute(model, selected, "signal")))
+
+	// Increase simulation time
+	return time + delta_t!
+
+Void function eliminateGaussJordan(m : Element):
+	Integer i
+	Integer j
+	Integer f
+	Integer g
+	Boolean searching
+	Element t
+	Float divisor
+
+	i = 0
+	j = 0
+
+	while (i < read_nr_out(m)):
+		// Make sure pivot m[i][j] != 0, swapping if necessary
+		while (cast_float(m[i][j]) == 0.0):
+			// Is zero, so find row which is not zero
+			f = i + 1
+			searching = True
+			while (searching):
+				if (f >= read_nr_out(m)):
+					// No longer any rows left, so just increase column counter
+					searching = False
+					j = j + 1
+				else:
+					if (cast_float(m[f][j]) == 0.0):
+						// Also zero, so continue
+						f = f + 1
+					else:
+						// Found non-zero, so swap row
+						t = cast_float(m[f])
+						dict_overwrite(m, f, cast_float(m[i]))
+						dict_overwrite(m, i, t)
+						searching = False
+			// If we have increased j, we will just start the loop again (possibly), as m[i][j] might be zero again
+
+		// Pivot in m[i][j] guaranteed to not be 0
+		// Now divide complete row by value of m[i][j] to make it equal 1
+		f = j
+		divisor = cast_float(m[i][j])
+		while (f < read_nr_out(m[i])):
+			dict_overwrite(m[i], f, float_division(cast_float(m[i][f]), divisor))
+			f = f + 1
+
+		// Eliminate all rows in the j-th column, except the i-th row
+		f = 0
+		while (f < read_nr_out(m)):
+			if (bool_not(f == i)):
+				g = j
+				divisor = cast_float(m[f][j])
+				while (g < read_nr_out(m[f])):
+					dict_overwrite(m[f], g, cast_float(m[f][g]) - (divisor * cast_float(m[i][g])))
+					g = g + 1
+			f = f + 1
+
+		// Increase row and column
+		i = i + 1
+		j = j + 1
+
+	return !
+
+String function matrix2string(m : Element):
+	Integer i
+	Integer j
+	String result
+
+	result = ""
+	i = 0
+	while (i < read_nr_out(m)):
+		j = 0
+		while (j < read_nr_out(m[i])):
+			result = result + cast_string(m[i][j]) + ", "
+			j = j + 1
+		i = i + 1
+		result = result + "\n"
+	return result!

+ 17 - 0
models/FiniteStateAutomata/metamodels/simple.mvc

@@ -0,0 +1,17 @@
+include "primitives.alh"
+
+SimpleAttribute String {}
+SimpleAttribute Boolean {}
+ActionLanguage Action {}
+
+Class State {
+    name = "State"
+    name : String
+    initial : Boolean
+}
+
+Association Transition (State, State) {
+    trigger? : String {}
+    raise? : String {}
+    script : Action {}
+}

+ 53 - 0
models/FiniteStateAutomata/transformations/simple_simulate.alc

@@ -0,0 +1,53 @@
+include "primitives.alh"
+include "modelling.alh"
+include "object_operations.alh"
+include "conformance_scd.alh"
+include "io.alh"
+include "metamodels.alh"
+include "mini_modify.alh"
+include "library.alh"
+
+Boolean function main(model : Element):
+	String input_value
+	Float start_time
+	String current_state
+	String old_state
+	Element transitions
+	String transition
+
+	start_time = time()
+
+	Element all_states
+	String element_name
+	all_states = allInstances(model, "FSA/State")
+	while (set_len(all_states) > 0):
+		element_name = set_pop(all_states)
+		if (value_eq(read_attribute(model, element_name, "initial"), True)):
+			current_state = element_name
+			old_state = element_name
+			break!
+
+	while (True):
+		if (has_input()):
+			input_value = list_read(string_split(input(), "\n"), 0)
+
+			if (input_value == "__EXIT__"):
+				break!
+
+			transitions = allOutgoingAssociationInstances(model, current_state, "FSA/Transition")
+			while (set_len(transitions) > 0):
+				transition = set_pop(transitions)
+				if (cast_string(read_attribute(model, transition, "trigger")) == input_value):
+					if (element_neq(read_attribute(model, transition, "raise"), read_root())):
+						log(cast_value(time() - start_time) + " output " + cast_string(read_attribute(model, transition, "raise")))
+						output(cast_value(time() - start_time) + " output " + cast_string(read_attribute(model, transition, "raise")))
+					if (element_neq(read_attribute(model, transition, "script"), read_root())):
+						Element func
+						func = get_func_AL_model(import_node(read_attribute(model, transition, "script")))
+						func()
+					current_state = readAssociationDestination(model, transition)
+					break!
+
+		output(cast_value(time() - start_time) + " " + cast_string(read_attribute(model, current_state, "name")))
+		sleep(0.2)
+	return True!

+ 47 - 0
models/PetriNets/transformations/simple_simulate.alc

@@ -0,0 +1,47 @@
+include "primitives.alh"
+include "modelling.alh"
+include "object_operations.alh"
+
+Boolean function main(model : Element):
+	Element transitions
+	Element links
+	String transition
+	String link
+	String place
+	Boolean enabled
+
+	transitions = allInstances(model, "PetriNet/Transition")
+	// Iterate over all transitions
+	while (set_len(transitions) > 0):
+		// Check if it is enabled
+		transition = set_pop(transitions)
+
+		// Check all incoming P2T links
+		links = allIncomingAssociationInstances(model, transition, "PetriNet/P2T")
+		enabled = True
+		while (set_len(links) > 0):
+			link = set_pop(links)
+
+			if (cast_integer(read_attribute(model, link, "weight")) > cast_integer(read_attribute(model, readAssociationSource(model, link), "tokens"))):
+				// Too few tokens, so skip
+				enabled = False
+				break!
+
+		if (enabled):
+			// All checks OK, so update the out locations
+			links = allOutgoingAssociationInstances(model, transition, "PetriNet/T2P")
+			while (set_len(links) > 0):
+				link = set_pop(links)
+				place = readAssociationDestination(model, link)
+				instantiate_attribute(model, place, "tokens", cast_integer(read_attribute(model, place, "tokens")) + cast_integer(read_attribute(model, link, "weight")))
+
+			// All checks OK, and update the in locations
+			links = allOutgoingAssociationInstances(model, transition, "PetriNet/P2T")
+			while (set_len(links) > 0):
+				link = set_pop(links)
+				place = readAssociationSource(model, link)
+				instantiate_attribute(model, place, "tokens", cast_integer(read_attribute(model, place, "tokens")) - cast_integer(read_attribute(model, link, "weight")))
+
+			return True!
+
+	return False!