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Binary Search Trees

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23 diapositives · 541 Views · Dec 03, 2012

Binary Search Trees . Eileen Kraemer CSCI 2720 The University of Georgia Spring 2007. Overview. Binary trees Binary search trees Find Insert Delete. Hierarchical Data Structures. One-to-many relationship between elements Tree Single parent, multiple children Binary tree

#tree rotation #splay tree #red-black tree #binary logarithm #binary tree #binary search tree #treap #avl tree
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Binary Search Trees
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  1. Binary Search Trees Eileen Kraemer CSCI 2720 The University of Georgia Spring 2007

  2. Overview • Binary trees • Binary search trees • Find • Insert • Delete

  3. Hierarchical Data Structures • One-to-many relationship between elements • Tree • Single parent, multiple children • Binary tree • Tree with 0–2 children per node Tree Binary Tree

  4. Trees • Terminology • Root no predecessor • Leaf no successor • Interior non-leaf • Height distance from root to leaf Root node Height Interior nodes Leaf nodes

  5. Types of Binary Trees • Degenerate – only one child • Balanced – mostly two children • Complete – always two children Degenerate binary tree Balanced binary tree Complete binary tree

  6. Degenerate Height = O(n) for n nodes Similar to linear list Balanced Height = O( log(n) ) for n nodes Useful for searches Binary Trees Properties Degenerate binary tree Balanced binary tree

  7. Binary Search Trees • Key property • Value at node • Smaller values in left subtree • Larger values in right subtree • Example • X > Y • X < Z X Y Z

  8. Binary Search Trees • Examples 5 10 10 2 45 5 30 5 45 30 2 25 45 2 25 30 10 25 Binary search trees Non-binary search tree

  9. Binary Tree Implementation Class Node { Value data; Node left, right; // null if empty void insert ( Value data1 ) { … } void delete ( Value data2 ) { … } Node find ( Value data3 ) { … } … }

  10. Polymorphic Binary Tree Implement. Interface Node { Node insert ( Value data1 ) { … } } Class EmptyNode { Node insert ( Value data1 ) { … } } Class NonEmptyNode { Value data; Node left, right; // Either Empty or NonEmpty void insert ( Value data1 ) { … } }

  11. Iterative Search of Binary Tree Node Find( Node n, Value key) { while (n != null) { if (n.data == key) // Found it return n; if (n.data > key) // In left subtree n = n.left; else // In right subtree n = n.right; } return null; } … Find( root,key_val );

  12. Recursive Search of Binary Tree Node Find( Node n, Value key) { if (n == null) // Not found return( n ); elseif (n.data == key) // Found it return( n ); else if (n.data > key) // In left subtree return Find( n.left ); else // In right subtree return Find( n.right ); } Find( root );

  13. Example Binary Searches • Find ( 2 ) 5 10 10 > 2, left 5 > 2, left 2 = 2, found 5 > 2, left 2 = 2, found 2 45 5 30 30 2 25 45 10 25

  14. Example Binary Searches • Find ( 25 ) 5 10 10 < 25, right 30 > 25, left 25 = 25, found 5 < 25, right 45 > 25, left 30 > 25, left 10 < 25, right 25 = 25, found 2 45 5 30 30 2 25 45 10 25

  15. Binary Search Properties • Time of search • Proportional to height of tree • Balanced binary tree • O( log(n) ) time • Degenerate tree • O( n ) time • Like searching linked list / unsorted array • Requires • Ability to compare key values

  16. Binary Search Tree Construction • How to build & maintain binary trees? • Insertion • Deletion • Maintain key property (invariant) • Smaller values in left subtree • Larger values in right subtree

  17. Binary Search Tree – Insertion • Algorithm • Perform search for value X • Search will end at node Y (if X not in tree) • If X < Y, insert new leaf X as new left subtree for Y • If X > Y, insert new leaf X as new right subtree for Y • Observations • O( log(n) ) operation for balanced tree • Insertions may unbalance tree

  18. Example Insertion • Insert ( 20 ) 10 10 < 20, right 30 > 20, left 25 > 20, left Insert 20 on left 5 30 2 25 45 20

  19. Binary Search Tree – Deletion • Algorithm • Perform search for value X • If X is a leaf, delete X • Else // must delete internal node • a) Replace with largest value Y on left subtree OR smallest value Z on right subtree • b) Delete replacement value (Y or Z) from subtree • Observation • O( log(n) ) operation for balanced tree • Deletions may unbalance tree

  20. Example Deletion (Leaf) • Delete ( 25 ) 10 10 10 < 25, right 30 > 25, left 25 = 25, delete 5 30 5 30 2 25 45 2 45

  21. Example Deletion (Internal Node) • Delete ( 10 ) 10 5 5 5 30 5 30 2 30 2 25 45 2 25 45 2 25 45 Replacing 10 with largest value in left subtree Replacing 5 with largest value in left subtree Deleting leaf

  22. Example Deletion (Internal Node) • Delete ( 10 ) 10 25 25 5 30 5 30 5 30 2 25 45 2 25 45 2 45 Replacing 10 with smallest value in right subtree Deleting leaf Resulting tree

  23. Still need to talk about … • Static BSTs (we looked at some example) • Optimal BSTs • Probability-balanced trees • Median split trees • but in the meantime, let’s jump forward to AVL trees.