Separate Chaining - Coursera Algorithms

To deal with collisions in hashing, separate chaining implementation can be used, where M linked lists(<number of elements N) are used such that :

1. Hash - map key to i between 0 and M-1.
2. Insert - at the front of ith chain.

3. Search - in ith chain.

Easier to implement and clustering less sensitive to poorly designed hash function.

Following is the implementation:

Hash Functions - Coursera Algorithms

We can do better than the sequential/binary search or search through BST/red-black BST, by storing the data in key-indexed table. Hash functions compute the array index from key. We need to handle the hash implementation, equality test and collision resolution when two keys hash to the same index.

There are several hashing implementations, some of them being :
1. 31*initial_hash_value+ current element value or current object hashcode.
2. Modular - Math.abs(key.hashCode() & 0x7fffffff)%M returning a hash between 0 and M-1

Following code experiments with what happens when we override equals/hashcode: