Prove that a binary tree that is not full cannot correspond to an optimal prefix free code. Note: a full binary tree is a tree in which any non-leaf node has 2 children (see page 430). Your proof (which is very simple) should have the following structure: Consider a prefix-free code C, whose corresponding binary tree T has some node with only one child; show that you can transform T into another binary tree T', whose corresponding code C' has smaller average length and so is better than C (which means that C is not optimal). In your proof you need to indicate the transformation from T into T' and explain why the code C' is better than C.

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
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**Binary Trees and Prefix Free Codes**

To explore the concept of optimal prefix-free codes using binary trees, we need to establish why a non-full binary tree cannot represent such a code optimally.

**Definition:**

A *full binary tree* is defined as a tree where every non-leaf node has exactly two children.

**Problem Statement:**

Demonstrate that if a binary tree is not full, it cannot correlate with an optimal prefix-free code. 

**Steps for Proof:**

1. **Consider a Prefix-Free Code (C):**
   - Use a corresponding binary tree, T, that has at least one node with a single child.

2. **Transformation of Tree (T to T'):**
   - Show that tree T can be modified into another binary tree, T′.
   - Tree T′ should be structured such that the new code, C′, derived from it, has a reduced average length compared to C. 

3. **Reasoning:**
   - Demonstrate why C′, the code from T′, is more efficient than C. 
   - A smaller average length indicates better codification efficiency, confirming that C was suboptimal.

The key aspect of the proof involves transforming the binary tree to decrease the code's average length, proving that having nodes with single children does not lead to optimal coding efficiency. This demonstrates why a full binary tree must be used for optimal prefix-free codes.
Transcribed Image Text:**Binary Trees and Prefix Free Codes** To explore the concept of optimal prefix-free codes using binary trees, we need to establish why a non-full binary tree cannot represent such a code optimally. **Definition:** A *full binary tree* is defined as a tree where every non-leaf node has exactly two children. **Problem Statement:** Demonstrate that if a binary tree is not full, it cannot correlate with an optimal prefix-free code. **Steps for Proof:** 1. **Consider a Prefix-Free Code (C):** - Use a corresponding binary tree, T, that has at least one node with a single child. 2. **Transformation of Tree (T to T'):** - Show that tree T can be modified into another binary tree, T′. - Tree T′ should be structured such that the new code, C′, derived from it, has a reduced average length compared to C. 3. **Reasoning:** - Demonstrate why C′, the code from T′, is more efficient than C. - A smaller average length indicates better codification efficiency, confirming that C was suboptimal. The key aspect of the proof involves transforming the binary tree to decrease the code's average length, proving that having nodes with single children does not lead to optimal coding efficiency. This demonstrates why a full binary tree must be used for optimal prefix-free codes.
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