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Merged
sebinside merged 12 commits into from
Apr 9, 2024
Merged

Provide unified copying of PFGs and more query methods in Vertices #135

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4b0f857
feat(core): implement common copy method for partial flow graphs
Entenwilli Mar 12, 2024
9547767
feat(core): remove mapping parameter from copy method
Entenwilli Mar 12, 2024
a7333ad
feat(core): implement more accessor methods for node characteristics …
Entenwilli Mar 12, 2024
daaccc6
refactor(core): rename getAllNodeCharacteristics to getAllVertexChara…
Entenwilli Mar 31, 2024
df367f4
refactor(core): rename occurences of data flow variable to data chara…
Entenwilli Mar 31, 2024
681e373
fix(converter): fix missed renamed methods
Entenwilli Mar 31, 2024
d13b67b
style(core): remove autoformatted wildcard import
Entenwilli Mar 31, 2024
d9a26eb
refactor(core): make naming in abstract vertex consistent
Entenwilli Mar 31, 2024
5c5fd24
refactor: rename all occurences of data flow variable to data charact…
Entenwilli Apr 2, 2024
3cf0a0b
refactor(converter): find missing (and generally inconsistent) data c…
Entenwilli Apr 3, 2024
14ea2e5
style: apply formatter
Entenwilli Apr 3, 2024
cd6b385
fix: merge upstream
Entenwilli Apr 3, 2024
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10 changes: 5 additions & 5 deletions ...analysis.analysis.converter/src/org/dataflowanalysis/analysis/converter/PCMConverter.java
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Expand Up @@ -9,7 +9,7 @@
import org.dataflowanalysis.analysis.core.AbstractTransposeFlowGraph;
import org.dataflowanalysis.analysis.core.AbstractVertex;
import org.dataflowanalysis.analysis.core.CharacteristicValue;
import org.dataflowanalysis.analysis.core.DataFlowVariable;
import org.dataflowanalysis.analysis.core.DataCharacteristic;
import org.dataflowanalysis.analysis.core.FlowGraphCollection;
import org.dataflowanalysis.analysis.pcm.PCMDataFlowConfidentialityAnalysisBuilder;
import org.dataflowanalysis.analysis.pcm.core.AbstractPCMVertex;
Expand Down Expand Up @@ -180,9 +180,9 @@ private void createFlowBetweenPreviousAndCurrentNode(Node source, Node dest, Abs
if (source == null || dest == null) {
return;
}
List<DataFlowVariable> flowVariables = pcmVertex.getAllDataFlowVariables();
for (DataFlowVariable flowVariable : flowVariables) {
String flowName = flowVariable.variableName();
List<DataCharacteristic> dataCharacteristics = pcmVertex.getAllDataCharacteristics();
for (DataCharacteristic dataCharacteristic : dataCharacteristics) {
String flowName = dataCharacteristic.variableName();

dataFlowDiagram.getFlows()
.stream()
Expand Down Expand Up @@ -262,7 +262,7 @@ private Node getDFDNode(AbstractPCMVertex<? extends Entity> pcmVertex) {
dfdNode = createDFDNode(pcmVertex);
}

addNodeCharacteristicsToNode(dfdNode, pcmVertex.getAllNodeCharacteristics());
addNodeCharacteristicsToNode(dfdNode, pcmVertex.getAllVertexCharacteristics());

return dfdNode;
}
Expand Down
6 changes: 6 additions & 0 deletions ...alysis.analysis.dfd/src/org/dataflowanalysis/analysis/dfd/core/DFDTransposeFlowGraph.java
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Expand Up @@ -30,4 +30,10 @@ public AbstractTransposeFlowGraph evaluate() {
return new DFDTransposeFlowGraph(newSink);
}

@Override
public AbstractTransposeFlowGraph copy() {
DFDVertex copiedSink = ((DFDVertex) sink).clone();
copiedSink.unify(new HashSet<>());
return new DFDTransposeFlowGraph(copiedSink);
}
}
34 changes: 17 additions & 17 deletions ...g.dataflowanalysis.analysis.dfd/src/org/dataflowanalysis/analysis/dfd/core/DFDVertex.java
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Expand Up @@ -12,7 +12,7 @@
import java.util.stream.Collectors;
import org.dataflowanalysis.analysis.core.AbstractVertex;
import org.dataflowanalysis.analysis.core.CharacteristicValue;
import org.dataflowanalysis.analysis.core.DataFlowVariable;
import org.dataflowanalysis.analysis.core.DataCharacteristic;
import org.dataflowanalysis.dfd.datadictionary.AND;
import org.dataflowanalysis.dfd.datadictionary.AbstractAssignment;
import org.dataflowanalysis.dfd.datadictionary.Assignment;
Expand Down Expand Up @@ -50,7 +50,7 @@ public DFDVertex(Node node, Map<Pin, DFDVertex> pinDFDVertexMap, Map<Pin, Flow>
}

/**
* Evaluates the given vertex by determining incoming and outgoing data flow variables and node characteristics
* Evaluates the given vertex by determining incoming and outgoing data characteristics and node characteristics
*/
@Override
public void evaluateDataFlow() {
Expand All @@ -59,19 +59,19 @@ public void evaluateDataFlow() {
}
evaluatePreviousVertices();

List<CharacteristicValue> nodeCharacteristics = determineNodeCharacteristics();
List<CharacteristicValue> vertexCharacteristics = determineNodeCharacteristics();

Map<Pin, List<Label>> inputPinsIncomingLabelMap = new HashMap<>();
this.getPinFlowMap()
.keySet()
.forEach(pin -> this.fillMapOfIncomingLabelsPerPin(pin, inputPinsIncomingLabelMap));

List<DataFlowVariable> dataFlowVariables = new ArrayList<>(this.createDataFlowVariablesFromLabels(inputPinsIncomingLabelMap));
List<DataCharacteristic> dataCharacteristics = new ArrayList<>(this.createDataCharacteristicsFromLabels(inputPinsIncomingLabelMap));

Map<Pin, List<Label>> outputPinsOutgoingLabelMap = determineOutputPinOutgoingLabelMap(inputPinsIncomingLabelMap);

List<DataFlowVariable> outgoingDataFlowVariables = new ArrayList<>(this.createDataFlowVariablesFromLabels(outputPinsOutgoingLabelMap));
this.setPropagationResult(dataFlowVariables, outgoingDataFlowVariables, nodeCharacteristics);
List<DataCharacteristic> outgoingDataCharacteristics = new ArrayList<>(this.createDataCharacteristicsFromLabels(outputPinsOutgoingLabelMap));
this.setPropagationResult(dataCharacteristics, outgoingDataCharacteristics, vertexCharacteristics);
}

/**
Expand Down Expand Up @@ -120,16 +120,16 @@ private void evaluatePreviousVertices() {
private void fillMapOfIncomingLabelsPerPin(Pin pin, Map<Pin, List<Label>> inputPinsIncomingLabelMap) {
for (var previousVertex : this.getPinDFDVertexMap()
.values()) {
for (var dfv : previousVertex.getAllOutgoingDataFlowVariables()) {
if (dfv.variableName()
for (var dataFlowCharacteristics : previousVertex.getAllOutgoingDataCharacteristics()) {
if (dataFlowCharacteristics.getVariableName()
.equals(this.getPinFlowMap()
.get(pin)
.getSourcePin()
.getId())) {
inputPinsIncomingLabelMap.putIfAbsent(pin, new ArrayList<>());
for (var cv : dfv.getAllCharacteristics()) {
for (var characteristicValue : dataFlowCharacteristics.getAllCharacteristics()) {
inputPinsIncomingLabelMap.get(pin)
.add(((DFDCharacteristicValue) cv).getLabel());
.add(((DFDCharacteristicValue) characteristicValue).getLabel());
}
}
}
Expand Down Expand Up @@ -163,16 +163,16 @@ private void handleOutgoingAssignments(AbstractAssignment assignment, Map<Pin, L
}

/**
* Create Data Flow Variables from Map mapping Input/Output Pin to labels. Important: The name of the data flow variable
* is equal to the id of the pin. Any changes in the data flow variable naming scheme will require changes in the
* evaluation logic
* Create data characteristics from Map mapping Input/Output Pin to labels. Important: The name of the data
* characteristic is equal to the id of the pin. Any changes in the data characteristics naming scheme will require
* changes in the evaluation logic
* @param pinToLabelMap Map mapping Input/Output Pin to labels
* @return List of created Data Flow Variables
* @return List of created data characteristics
*/
private List<DataFlowVariable> createDataFlowVariablesFromLabels(Map<Pin, List<Label>> pinToLabelMap) {
private List<DataCharacteristic> createDataCharacteristicsFromLabels(Map<Pin, List<Label>> pinToLabelMap) {
return pinToLabelMap.keySet()
.stream()
.map(pin -> new DataFlowVariable(pin.getId(), this.getCharacteristicValuesForPin(pin, pinToLabelMap)))
.map(pin -> new DataCharacteristic(pin.getId(), this.getCharacteristicValuesForPin(pin, pinToLabelMap)))
.toList();
}

Expand Down Expand Up @@ -270,7 +270,7 @@ public void unify(Set<DFDVertex> vertices) {
}

/**
* Creates a clone of the vertex without considering data flow variables nor characteristics
* Creates a clone of the vertex without considering data characteristics nor vertex characteristics
*/
public DFDVertex clone() {
Map<Pin, DFDVertex> copiedPinDFDVertexMap = new HashMap<>();
Expand Down
30 changes: 15 additions & 15 deletions ...owanalysis.analysis.pcm/src/org/dataflowanalysis/analysis/pcm/core/AbstractPCMVertex.java
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Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,7 @@
import org.apache.log4j.Logger;
import org.dataflowanalysis.analysis.core.AbstractVertex;
import org.dataflowanalysis.analysis.core.CharacteristicValue;
import org.dataflowanalysis.analysis.core.DataFlowVariable;
import org.dataflowanalysis.analysis.core.DataCharacteristic;
import org.dataflowanalysis.analysis.resource.ResourceProvider;
import org.dataflowanalysis.pcm.extension.model.confidentiality.ConfidentialityVariableCharacterisation;
import org.palladiosimulator.pcm.core.composition.AssemblyContext;
Expand Down Expand Up @@ -50,19 +50,19 @@ public AbstractPCMVertex(T referencedElement, List<? extends AbstractPCMVertex<?
this.previousElements = previousElements;
}

public abstract AbstractPCMVertex<?> deepCopy(Map<AbstractPCMVertex<?>, AbstractPCMVertex<?>> vertexMapping);
public abstract AbstractPCMVertex<?> copy(Map<AbstractPCMVertex<?>, AbstractPCMVertex<?>> vertexMapping);

/**
* Sets the propagation result of the Vertex to the given result. This method should only be called once on elements
* that are not evaluated.
* @param incomingDataFlowVariables Incoming data flow variables that flow into the vertex
* @param outgoingDataFlowVariables Outgoing data flow variables that flow out of the vertex
* @param incomingDataCharacteristics Incoming data characteristics that flow into the vertex
* @param outgoingDataCharacteristics Outgoing data characteristics that flow out of the vertex
* @param vertexCharacteristics Vertex characteristics present at the node
*/
@Override
protected void setPropagationResult(List<DataFlowVariable> incomingDataFlowVariables, List<DataFlowVariable> outgoingDataFlowVariables,
protected void setPropagationResult(List<DataCharacteristic> incomingDataCharacteristics, List<DataCharacteristic> outgoingDataCharacteristics,
List<CharacteristicValue> vertexCharacteristics) {
super.setPropagationResult(incomingDataFlowVariables, outgoingDataFlowVariables, vertexCharacteristics);
super.setPropagationResult(incomingDataCharacteristics, outgoingDataCharacteristics, vertexCharacteristics);
}

@Override
Expand All @@ -74,7 +74,7 @@ public void setPreviousElements(List<? extends AbstractPCMVertex<?>> previousEle
this.previousElements = previousElements;
}

protected List<DataFlowVariable> getIncomingDataFlowVariables() {
protected List<DataCharacteristic> getIncomingDataCharacteristics() {
if (super.isSource())
return List.of();

Expand All @@ -84,7 +84,7 @@ protected List<DataFlowVariable> getIncomingDataFlowVariables() {
.forEach(AbstractVertex::evaluateDataFlow);
return this.getPreviousElements()
.stream()
.flatMap(it -> it.getAllOutgoingDataFlowVariables()
.flatMap(it -> it.getAllOutgoingDataCharacteristics()
.stream())
.collect(Collectors.toList());
}
Expand All @@ -100,15 +100,15 @@ protected List<CharacteristicValue> getVertexCharacteristics() {

/**
* Calculate the data characteristics for the vertex with the given vertex characteristics, variable characterizations
* and old data flow variables
* and old data characteristics
* @param vertexCharacteristics Vertex characteristics present at the vertex
* @param variableCharacterisations Variable characterizations present in the model
* @param oldDataFlowVariables Old data flow variables present at the node
* @param oldDataCharacteristics Old data characteristics present at the node
* @return Returns a list of data characteristics that are applied to the sequence element
*/
protected List<DataFlowVariable> getDataFlowVariables(List<CharacteristicValue> vertexCharacteristics,
List<ConfidentialityVariableCharacterisation> variableCharacterisations, List<DataFlowVariable> oldDataFlowVariables) {
PCMDataCharacteristicsCalculator dataCharacteristicsCalculator = new PCMDataCharacteristicsCalculator(oldDataFlowVariables,
protected List<DataCharacteristic> getDataCharacteristics(List<CharacteristicValue> vertexCharacteristics,
List<ConfidentialityVariableCharacterisation> variableCharacterisations, List<DataCharacteristic> oldDataCharacteristics) {
PCMDataCharacteristicsCalculator dataCharacteristicsCalculator = new PCMDataCharacteristicsCalculator(oldDataCharacteristics,
vertexCharacteristics, this.resourceProvider);
variableCharacterisations.forEach(dataCharacteristicsCalculator::evaluate);
return dataCharacteristicsCalculator.getCalculatedCharacteristics();
Expand Down Expand Up @@ -141,13 +141,13 @@ protected void checkCallParameter(OperationSignature callSignature, List<Confide

protected AbstractPCMVertex<?> updateCopy(AbstractPCMVertex<?> copy, Map<AbstractPCMVertex<?>, AbstractPCMVertex<?>> vertexMapping) {
if (this.isEvaluated()) {
copy.setPropagationResult(this.getAllIncomingDataFlowVariables(), this.getAllOutgoingDataFlowVariables(),
copy.setPropagationResult(this.getAllIncomingDataCharacteristics(), this.getAllOutgoingDataCharacteristics(),
this.getVertexCharacteristics());
}
vertexMapping.put(this, copy);

List<? extends AbstractPCMVertex<?>> clonedPreviousElements = this.previousElements.stream()
.map(it -> it.deepCopy(vertexMapping))
.map(it -> it.copy(vertexMapping))
.toList();

copy.setPreviousElements(clonedPreviousElements);
Expand Down
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