What Is Collision Resolution Techniques in Data Structure?

What Is Collision Resolution Techniques in Data Structure?

In data structure, collision refers to the situation where two or more elements of a hash table are mapped to the same index or location. This can happen due to various reasons, such as a limited number of available indices or a hash function that generates the same hash value for different keys.

Collision resolution techniques are methods used to handle collisions and ensure that all elements can be stored and retrieved correctly from the hash table. These techniques aim to find alternative locations for colliding elements, allowing them to coexist without overwriting each other.

Types of Collision Resolution Techniques

There are several collision resolution techniques commonly used in data structures:

• 1. Separate Chaining:

This technique involves maintaining a linked list at each index of the hash table. When a collision occurs, the colliding elements are added to the linked list at that index. This way, multiple elements can exist at the same index without overwriting each other.

• 2. Open Addressing:

In open addressing, when a collision occurs, an alternative empty location within the hash table is searched for and used to store the colliding element. There are different strategies within open addressing:

• Linear Probing:

In linear probing, if a collision occurs at index ‘i’, the next available empty slot is searched starting from i+1 until an empty slot is found.

• Quadratic Probing:

This technique uses a quadratic function to probe for an empty slot after collisions occur.

The probing sequence follows a quadratic equation until an empty slot is found.

• Double Hashing:

In double hashing, two hash functions are used to probe for empty slots. If a collision occurs at index ‘i’, the second hash function is applied to find the next available empty slot.

• 3. Robin Hood Hashing:

This technique aims to minimize the variance in probe lengths that can occur with linear probing. When a collision occurs, it checks the difference between the original slot and the current slot being probed. If the current slot has less difference, it swaps places with the colliding element.

Choosing Collision Resolution Techniques

The choice of collision resolution techniques depends on various factors, including:

• The expected number of elements in the hash table
• The memory restrictions and efficiency requirements of the system
• The distribution of keys and potential collisions
• The complexity and speed of different techniques

It’s important to consider these factors during implementation to ensure efficient storage and retrieval operations for data stored in a hash table.

Conclusion

Collision resolution techniques are essential in data structures to handle collisions that occur when multiple elements map to the same location in a hash table. Whether using separate chaining, open addressing, or other methods, choosing an appropriate technique depends on various factors specific to the system’s requirements. By implementing effective collision resolution techniques, developers can ensure efficient storage and retrieval operations within their applications.