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Course: Programming II - Abstract Data Types Red-Black TreesSlide Number 1 Balanced Search Trees Binary Search Tree data structures can allow insertion, deletion and search operations of the order O(log n) (if balanced). Binary balanced search-trees AVL trees Red-black trees Splay trees. General balanced search-trees 2-3 trees, 2-3-4 trees and B-trees Balanced search-tree data structures are trees that guarantee insertion, deletion and search operations of the order O(log n) by maintaining a balanced tree.

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Course: Programming II - Abstract Data Types Red-Black Trees Slide Number 2Red-Black Trees Definition A Red-Black Tree is a Binary Search Tree where nodes have a color (Red or Black) and that satisfies the following properties Red-Black properties Every node is either Red or Black. The root node is Black If a node is Red, then all of its children are Black Every simple path from a given node x to any of its descendant leaves contains the same number of black nodes. (black-height(x)). No consecutive red nodes in a path.

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Course: Programming II - Abstract Data Types Examples Slide Number 3Red-Black Trees Every node is either red or black The root node is black Red nodes have black parents Every simple path from a given node x to its descendant leaf has the same number of black nodes black-height(x). bh=0 bh=1 bh=2bh=1 bh=2 red-black tree Not red-black trees

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Course: Programming II - Abstract Data Types Height of a Red-Black Tree Slide Number 4Red-Black Trees Theorem 1: A red-black tree with n elements has height h ≤ 2 log(n +1) Intuition: Merge red nodes into their black parents

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Course: Programming II - Abstract Data Types Height of a Red-Black Tree Slide Number 5Red-Black Trees Theorem 1: A red-black tree with n elements has height h ≤ 2 log(n +1) Intuition: Merge red nodes into their black parents h’h’

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Course: Programming II - Abstract Data Types Height of a Red-Black Tree Slide Number 6Red-Black Trees Theorem 1: A red-black tree with n elements has height h ≤ 2 log(n +1) Number of null leaves in each tree is n+1 h’h’ h Number of null leaves in a 2-3-4 tree is at least 2 h’ 2 h’ ≤ n+1 ⇒ h’ ≤ log(n+1) Also h ≤ 2 h’ h ≤ 2 log(n +1)

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Course: Programming II - Abstract Data Types Interface for Red-Black trees Slide Number 7 public interface RBT,V>{ public boolean contains(K searchKey); //Post: Searches for an element with key equal to searchKey in the tree. //Post: Returns false if no element is found. public V retrieve(K searchKey); //Post: Retrieves an element with key equal to searchKey from the tree. Returns either the value of //Post: the element if found, or null if no element with given searchKey exists. public void insert(K key, V newValue); //Post: Adds a new element to the tree with given key and newValue, preserving the properties of //Post: the red-black tree. If the tree includes already an element with the given key, it replaces its //Post: value with newValue. public void delete(K searchKey) throws TreeException; //Post: Removes an element with key equal to searchKey from the tree, preserving the properties of //Post: the red-black tree. Throws an exception if such element is not found. } Red-Black Trees

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Course: Programming II - Abstract Data Types Data Structure for Red-Black Trees Slide Number 8Red-Black Trees

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Course: Programming II - Abstract Data Types Rotation revisited Slide Number 9Red-Black Trees Rotate right (B) rotateRight( ){ // Rotates the current object to the right and returns its new parent get leftChild of B; set T2 to be the left subtree of B; reparent the old leftChild of B; set B to be the right child of the old leftChild of B }

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Course: Programming II - Abstract Data Types Rotation revisited Slide Number 10Red-Black Trees Rotate left (A) rotateLeft( ){ // Rotates the current object to the right and returns its new parent get rightChild of A; set T2 to be the right subtree of A; reparent the old rightChild of A; set A to be the left child of the old rightChild of B }

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Course: Programming II - Abstract Data Types Insertion Slide Number 11Red-Black Trees insert new node as per insert operation in binary search tree color the new node red (to preserve property 4) if new node is root node, repaint it black (Case 1) if parent is black, property 3 is satisfied (Case 2) if parent is red, property 3 is violated The operation performs the following steps: Double red problem Recoloring Restructuring the links of the tree by rotation Three more cases

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Course: Programming II - Abstract Data Types Insertion (continue..) Slide Number 12 Resolving double-red problem Parent node is Red, and Uncle node is Red Case 3: Recolor grandparent Red Recolor parent Black Recolor uncle Black Check cases again for grandparent Red-Black Trees

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Course: Programming II - Abstract Data Types Insertion (continue..) Slide Number 13 Rotate right (parent node) Current node is old parent Case 5 on current node Red-Black Trees Resolving double-red problem Parent node is Red, and Uncle node is Black (or null) Parent is right child of grandparent, and Current node is left child of parent Case 4: 4b

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Course: Programming II - Abstract Data Types Insertion (continue..) Slide Number 14Red-Black Trees Parent becomes Black Grandparent becomes Red Rotate left (grandparent node) Resolving double-red problem Parent node is Red, and Uncle node is Black (or null) Parent is right child of grandparent, and Current node is right child of parent Case 5: 5a

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Course: Programming II - Abstract Data Types Summary of Cases Slide Number 15 Case 2 DONE Case 3 Recolor go to Case 1 with current = G + Red-Black Trees Case 1 Recolor node. DONE

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Course: Programming II - Abstract Data Types Slide Number 16 Case 4a Rotates left parent go to Case 5 with current = P + Case 4b Rotates right P go to Case 5 with current = P + Summary of Cases Red-Black Trees

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Course: Programming II - Abstract Data Types Slide Number 17 Case 5a Recolor P and G, rotate right G DONE Summary of Cases Case 5b Recolor P and G, rotate left G DONE Red-Black Trees

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Course: Programming II - Abstract Data Types Slide Number 18 Implementing RedBlackTree Red-Black Trees public class RedBlackTree, V> implements RBT { private RBTNode root; public RedBlackTree() { this.root = null;} public V retrieve(K key){ RBTNode node = retrieveElem(root, key).getValue(); if (node == null){throw new NoSuchElementException();} return node.getValue(); } public void insert(K key, V newValue){ > }

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Course: Programming II - Abstract Data Types Slide Number 19 Implementing Insert Red-Black Trees public void insert(K key, V newValue){ Tuple, RBTNode > pair = findNode(key); RBTNode parent = pair.getX(); RBTNode current = pair.getY(); if (current != null) { Set the value of current to be newValue;} else if (parent == null){ Set the root to the be new RBTNode; Set the color of the root to BLACK; } else { Create a new RBTNode with color RED; if (key < parent.getKey()) Set the newRBTNode to be the left child of parent; else Set the newRBTNode to be the right child of parent; insertCaseOne(newRBTNode); } } Key already exists The tree is empty, create root node Check properties of RedBlack Tree

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Course: Programming II - Abstract Data Types Analysis Red-Black TreesSlide Number 20 AVL trees and Red-Black trees are data structure that guarantee insertion, deletion and search operations to be of the order O(log n). How do AVL trees and Red-Black trees compare? The height of an AVL tree is also logarithmic in n. An AVL tree can be colored to become a Red-Black tree, A Red-Black tree cannot be seen as an AVL tree: o Red-black trees can have larger heights than AVL trees o AVL trees are more rigidly balanced than Red-Black trees Red-Black tree have slightly faster insertions and deletion than AVL trees (TreeMap in Java uses Red-Black trees).

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© 2004 Goodrich, Tamassia Red-Black Trees1 6 3 8 4 v z.

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