Add inorder binary tree traversal (#3898)

src/main/java/com/thealgorithms/datastructures/trees/InorderTraversal.java

@@ -0,0 +1,60 @@
+package com.thealgorithms.datastructures.trees;
+
+import java.util.ArrayDeque;
+import java.util.ArrayList;
+import java.util.Deque;
+import java.util.List;
+
+/**
+ * Given tree is traversed in an 'inorder' way: LEFT -> ROOT -> RIGHT.
+ * Below are given the recursive and iterative implementations.
+ *
+ * Complexities:
+ * Recursive: O(n) - time, O(n) - space, where 'n' is the number of nodes in a tree.
+ *
+ * Iterative: O(n) - time, O(h) - space, where 'n' is the number of nodes in a tree
+ * and 'h' is the height of a binary tree.
+ * In the worst case 'h' can be O(n) if tree is completely unbalanced, for instance:
+ * 5
+ *  \
+ *   6
+ *    \
+ *     7
+ *      \
+ *       8
+ *
+ * @author Albina Gimaletdinova on 21/02/2023
+ */
+public class InorderTraversal {
+    public static List<Integer> recursiveInorder(BinaryTree.Node root) {
+        List<Integer> result = new ArrayList<>();
+        recursiveInorder(root, result);
+        return result;
+    }
+
+    public static List<Integer> iterativeInorder(BinaryTree.Node root) {
+        List<Integer> result = new ArrayList<>();
+        if (root == null) return result;
+
+        Deque<BinaryTree.Node> stack = new ArrayDeque<>();
+        while (!stack.isEmpty() || root != null) {
+            while (root != null) {
+                stack.push(root);
+                root = root.left;
+            }
+            root = stack.pop();
+            result.add(root.data);
+            root = root.right;
+        }
+        return result;
+    }
+
+    private static void recursiveInorder(BinaryTree.Node root, List<Integer> result) {
+        if (root == null) {
+            return;
+        }
+        recursiveInorder(root.left, result);
+        result.add(root.data);
+        recursiveInorder(root.right, result);
+    }
+}