Huffman Coding Checkpoint

Tree construction, canonical codes, and optimality.

1. Huffman coding is optimal for:

Known symbol probabilities Any unknown distribution Only uniform distributions Only binary alphabets

2. If only one symbol appears, its Huffman code length should be:

0 1 2 Depends on frequency

3. Canonical Huffman codes are determined by:

Code lengths and symbol order Tree shape Random tie-breaking Symbol frequencies only

4. Tie-breaking in Huffman matters because:

It affects determinism and reproducibility It changes entropy It violates Kraft's inequality It changes symbol probabilities

5. Huffman codes are:

Prefix-free Suffix-free Fixed-length Non-decodable

6. Canonical codes are useful because:

They reduce header size and allow fast decoding They avoid the need for frequencies They always beat entropy They remove the need for bit I/O

7. True/False: Huffman coding can produce expected length smaller than entropy.

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