Page 112 - Data Structures Handout

This example shows how a poor hash function (always returning 0) causes all keys to

collide at the same index, degrading performance to ( ).

9.5.3 Trade-offs in Hash Table Design

Designing an efficient hash table involves balancing several trade-offs:
• Memory vs Speed: Larger tables reduce collisions but consume more memory.

• Load Factor Thresholds: Lower thresholds improve performance but require

frequent resizing.

• Collision Resolution Strategy: Chaining uses extra memory but handles collisions
gracefully, while open addressing is memory-efficient but can suffer from

clustering.

• Hash Function Quality: A good hash function distributes keys evenly, minimizing

collisions.

9.6 Applications of Hashing

Hashing is not just a theoretical concept; it is widely used in practical computing

systems. Its ability to provide fast access and efficient storage makes it indispensable in many
domains. Let’s explore some of the most important applications.

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