Added missing javadocs and fixed javadoc errors

Author: “jklein94”

org-tweetyproject-arg-aba/src/main/java/org/tweetyproject/arg/aba/parser/AbaParser.java

@@ -175,7 +175,6 @@ public void setSymbolTrue(String symbolTrue) {
 
     /**
      * Gets the symbol used to separate the head and body in rules.
-     * This is the arrow symbol used to define rules in the form of head <- body.
      *
      * @return the symbol separating the head and body in rules
      */

org-tweetyproject-arg-bipolar/src/main/java/org/tweetyproject/arg/bipolar/syntax/ArgumentSet.java

@@ -43,7 +43,6 @@
  * @see Collection
  * @see Comparable
  *
- * @param <BArgument> the type of argument used in the argument set
  *
  * @author Lars Bengel
  */

org-tweetyproject-arg-deductive/src/main/java/org/tweetyproject/arg/deductive/syntax/SimplePlLogicArgument.java

@@ -91,8 +91,7 @@ public PlFormula getClaim() {
     }
 
     /**
-     * Returns a string representation of this argument in the form
-     * "<support, claim>".
+     * Returns a string representation
      *
      * @return The string representation of this argument.
      */

org-tweetyproject-arg-delp/src/main/java/org/tweetyproject/arg/delp/semantics/CriterionOptionHandler.java

@@ -33,8 +33,6 @@
  * in the command line and convert them into {@link ComparisonCriterion} instances.
  * </p>
  *
- * @param <ComparisonCriterion> the type of the comparison criterion handled by this option handler
- *
  * @author Linda Briesemeister
  */
 public final class CriterionOptionHandler extends OptionHandler<ComparisonCriterion> {

org-tweetyproject-arg-dung/src/main/java/org/tweetyproject/arg/dung/analysis/NonGroundedCountInconsistencyMeasure.java

@@ -31,10 +31,6 @@
  * Calculates the non-grounded count inconsistency measure of the given argumentation framework.
  * Non-grounded count inconsistency measure is the count of arguments in the argumentation framework
  * that are neither in any grounded extension nor attacked by any argument in grounded extensions.
- *
- * @param argumentationFramework The argumentation framework for which to calculate the non-grounded count inconsistency measure.
- * @return The non-grounded count inconsistency measure of the argumentation framework.
- *         Returns the count of arguments that are not part of any grounded extension or attacked by any argument in grounded extensions.
  */
 public class NonGroundedCountInconsistencyMeasure<T extends DungTheory> implements InconsistencyMeasure<T> {
 

org-tweetyproject-arg-dung/src/main/java/org/tweetyproject/arg/dung/causal/syntax/CounterfactualStatement.java

@@ -28,11 +28,12 @@
 /**
  * This class describes a counterfactual causal statement like:
  * given phi, if v had been x then rho would be true
- * 
+ *
  * Reference: "Argumentation-based Causal and Counterfactual Reasoning" by
- * Lars Bengel, Lydia Blümel, Tjitze Rienstra and Matthias Thimm, published at 1st International Workshop on Argumentation
+ * Lars Bengel, Lydia Blümel, Tjitze Rienstra and Matthias Thimm, published at
+ * 1st International Workshop on Argumentation
  * for eXplainable AI (ArgXAI, co-located with COMMA ’22), September 12, 2022
- * 
+ *
  * @author Julian Sander
  * @version TweetyProject 1.23
  *
@@ -41,9 +42,13 @@ public class CounterfactualStatement extends InterventionalStatement {
 
 	/**
 	 * Creates a new counterfactual causal statement.
-	 * @param conclusions Conclusions, which would be true, iff this statement is true and the interventions were realized and the premises are met.
+	 *
+	 * @param conclusions   Conclusions, which would be true, iff this statement is
+	 *                      true and the interventions were realized and the
+	 *                      premises are met.
 	 * @param interventions Maps explainable atoms to boolean values.
-	 * @param premises PlFormulas which have to be true, so that the conclusions can be drawn.
+	 * @param premises      PlFormulas which have to be true, so that the
+	 *                      conclusions can be drawn.
 	 */
 	public CounterfactualStatement(HashSet<PlFormula> conclusions, HashMap<Proposition, Boolean> interventions,
 			HashSet<PlFormula> premises) {
@@ -52,39 +57,56 @@ public CounterfactualStatement(HashSet<PlFormula> conclusions, HashMap<Propositi
 
 	@Override
 	public boolean holds(CausalKnowledgeBase cKbase) {
-		for(var conclusion : this.getConclusions()) {
-			if(!checkCounterFactualStatement(cKbase, conclusion)) {
+		for (var conclusion : this.getConclusions()) {
+			if (!checkCounterFactualStatement(cKbase, conclusion)) {
 				return false;
 			}
 		}
-		
+
 		return true;
 	}
-	
+
 	@Override
-	public void VisualizeHolds(CausalKnowledgeBase cKbase)
-	{
+	public void VisualizeHolds(CausalKnowledgeBase cKbase) {
 		var causalKnowledgeBaseCopy = getIntervenedTwinModel(cKbase);
 		causalKnowledgeBaseCopy.addAll(this.getPremises());
 		var inducedAF = new InducedTheory(causalKnowledgeBaseCopy);
-		DungTheoryPlotter.plotFramework(inducedAF, 3000, 2000,  
-				"Premises: " + this.getPremises().toString() 
-				+ " \n Interventions: " + this.getInterventions().toString()
-				+ " \n Conclusions: " + this.getConclusions().toString());
+		DungTheoryPlotter.plotFramework(inducedAF, 3000, 2000,
+				"Premises: " + this.getPremises().toString()
+						+ " \n Interventions: " + this.getInterventions().toString()
+						+ " \n Conclusions: " + this.getConclusions().toString());
 	}
-	
+
 	private boolean checkCounterFactualStatement(CausalKnowledgeBase cKbase, PlFormula conclusion) {
 		var newKnowledgeBase = getIntervenedTwinModel(cKbase);
 		return newKnowledgeBase.entails(this.getPremises(), conclusion);
 	}
 
+	/**
+	 * Creates a new intervened twin model from the provided causal knowledge base.
+	 *
+	 * <p>
+	 * This method generates the twin model from the given causal knowledge base,
+	 * applies the specified
+	 * interventions to this twin model, and returns a new
+	 * {@code CausalKnowledgeBase} containing the
+	 * intervened twin model, assumptions, and beliefs from the original knowledge
+	 * base.
+	 *
+	 * @param cKbase The original {@code CausalKnowledgeBase} from which the twin
+	 *               model and interventions are derived.
+	 * @return A new {@code CausalKnowledgeBase} that represents the intervened twin
+	 *         model, including the original
+	 *         assumptions and beliefs (excluding structural equations) from the
+	 *         input knowledge base.
+	 */
 	protected CausalKnowledgeBase getIntervenedTwinModel(CausalKnowledgeBase cKbase) {
 		var twin = cKbase.getCausalModel().getTwinModel();
 		var interventions = this.getInterventions();
-		for(var expAtom : interventions.keySet()) {
-			twin.intervene( new Proposition(expAtom.getName() + "*"), interventions.get(expAtom).booleanValue());
+		for (var expAtom : interventions.keySet()) {
+			twin.intervene(new Proposition(expAtom.getName() + "*"), interventions.get(expAtom).booleanValue());
 		}
-		
+
 		var newKnowledgeBase = new CausalKnowledgeBase(twin, cKbase.getAssumptions());
 		newKnowledgeBase.addAll(cKbase.getBeliefsWithoutStructuralEquations());
 		return newKnowledgeBase;

org-tweetyproject-arg-dung/src/main/java/org/tweetyproject/arg/dung/causal/syntax/InterventionalStatement.java

@@ -28,75 +28,101 @@
 /**
  * This class describes an interventional causal statement like:
  * given phi, if v would be x then rho would be true
- * 
+ *
  * Reference: "Argumentation-based Causal and Counterfactual Reasoning" by
- * Lars Bengel, Lydia Blümel, Tjitze Rienstra and Matthias Thimm, published at 1st International Workshop on Argumentation
+ * Lars Bengel, Lydia Blümel, Tjitze Rienstra and Matthias Thimm, published at
+ * 1st International Workshop on Argumentation
  * for eXplainable AI (ArgXAI, co-located with COMMA ’22), September 12, 2022
- * 
+ *
  * @author Julian Sander
  * @version TweetyProject 1.23
  *
  */
-public class InterventionalStatement extends CausalStatement{
+public class InterventionalStatement extends CausalStatement {
 
 	private HashMap<Proposition, Boolean> interventions;
+
 	/**
 	 * Creates a new interventional causal statement.
-	 * @param conclusions Conclusions, which would be true, iff this statement is true and the interventions were realized and the premises are met.
+	 *
+	 * @param conclusions   Conclusions, which would be true, iff this statement is
+	 *                      true and the interventions were realized and the
+	 *                      premises are met.
 	 * @param interventions Maps explainable atoms to boolean values.
-	 * @param premises PlFormulas which have to be true, so that the conclusions can be drawn.
+	 * @param premises      PlFormulas which have to be true, so that the
+	 *                      conclusions can be drawn.
 	 */
 	public InterventionalStatement(HashSet<PlFormula> conclusions, HashMap<Proposition, Boolean> interventions,
 			HashSet<PlFormula> premises) {
 		super(conclusions, premises);
-		
+
 		this.interventions = interventions;
 	}
-	
-    /**
-     * Retrieves the interventions of this causal statement.
-     * 
-     * @return A HashMap containing the interventions mapped from explainable atoms to their respective boolean values.
-     */
-	public HashMap<Proposition, Boolean> getInterventions(){
+
+	/**
+	 * Retrieves the interventions of this causal statement.
+	 *
+	 * @return A HashMap containing the interventions mapped from explainable atoms
+	 *         to their respective boolean values.
+	 */
+	public HashMap<Proposition, Boolean> getInterventions() {
 		return new HashMap<Proposition, Boolean>(this.interventions);
 	}
 
 	@Override
 	public boolean holds(CausalKnowledgeBase cKbase) {
-		for(var conclusion : this.getConclusions()) {
-			if(!checkInterventionalStatement(cKbase, conclusion)) {
+		for (var conclusion : this.getConclusions()) {
+			if (!checkInterventionalStatement(cKbase, conclusion)) {
 				return false;
 			}
 		}
-		
+
 		return true;
 	}
-	
+
 	@Override
-	public void VisualizeHolds(CausalKnowledgeBase cKbase)
-	{
+	public void VisualizeHolds(CausalKnowledgeBase cKbase) {
 		var causalKnowledgeBaseCopy = getIntervenedCopy(cKbase);
 		causalKnowledgeBaseCopy.addAll(this.getPremises());
 		var inducedAF = new InducedTheory(causalKnowledgeBaseCopy);
-		DungTheoryPlotter.plotFramework(inducedAF, 3000, 2000,  
-				"Premises: " + this.getPremises().toString() 
-				+ " \n Interventions: " + this.getInterventions().toString()
-				+ " \n Conclusions: " + this.getConclusions().toString());
+		DungTheoryPlotter.plotFramework(inducedAF, 3000, 2000,
+				"Premises: " + this.getPremises().toString()
+						+ " \n Interventions: " + this.getInterventions().toString()
+						+ " \n Conclusions: " + this.getConclusions().toString());
 	}
-	
+
 	private boolean checkInterventionalStatement(CausalKnowledgeBase cKbase, PlFormula conclusion) {
 		var newKnowledgeBase = getIntervenedCopy(cKbase);
 		return newKnowledgeBase.entails(this.getPremises(), conclusion);
 	}
 
+	/**
+	 * Creates a new intervened copy of the provided causal knowledge base.
+	 *
+	 * <p>
+	 * This method clones the causal model from the given causal knowledge base,
+	 * applies the specified
+	 * interventions to the cloned model, and returns a new
+	 * {@code CausalKnowledgeBase} containing the
+	 * intervened model, along with the original assumptions and beliefs from the
+	 * input knowledge base
+	 * (excluding structural equations).
+	 *
+	 * @param cKbase The original {@code CausalKnowledgeBase} from which the causal
+	 *               model is cloned and
+	 *               interventions are derived.
+	 * @return A new {@code CausalKnowledgeBase} that represents the intervened copy
+	 *         of the original causal
+	 *         knowledge base, including the original assumptions and beliefs
+	 *         (excluding structural equations).
+	 */
 	protected CausalKnowledgeBase getIntervenedCopy(CausalKnowledgeBase cKbase) {
 		var interventions = this.getInterventions();
 		var causalModel = cKbase.getCausalModel().clone();
-		for(var expAtom : interventions.keySet()) {
+		for (var expAtom : interventions.keySet()) {
 			causalModel.intervene(expAtom, interventions.get(expAtom).booleanValue());
 		}
-		
+
 		var newKnowledgeBase = new CausalKnowledgeBase(causalModel, cKbase.getAssumptions());
 		newKnowledgeBase.addAll(cKbase.getBeliefsWithoutStructuralEquations());
 		return newKnowledgeBase;

org-tweetyproject-arg-dung/src/main/java/org/tweetyproject/arg/dung/examples/EquivalenceExample.java

@@ -32,10 +32,19 @@
  * @author Lars Bengel
  */
 public class EquivalenceExample {
+
+    /** Constructor */
+    public EquivalenceExample() {
+    }
+
     /**
      * Example for Equivalence of Argumentation Frameworks
      */
-    public static void main(String[] args) {
+    /**
+     * Example
+     * @param args args
+     */
+     public static void main(String[] args) {
 
         // Initialize Example Argumentation Frameworks
         Argument a = new Argument("a");