Background:
A Bloom Filter is a probabilistic data structure for efficient set membership testing. It provides a way to check whether an element is definitely not in a set or possibly in it, with a small probability of false positives.
A Bloom Filter uses multiple hash functions to map elements to a fixed-size bit array. Checking for membership involves verifying if all corresponding bits are set. They do not directly store data and, therefore, are space-efficient. However, it does not support deletions.
Expected Behaviour
- Implementation of a space-efficient Bit array to be utilized by the bloom filter
- Should support multiple Data-types
- Utilize various hash functions to add elements and check membership
Background:
A Bloom Filter is a probabilistic data structure for efficient set membership testing. It provides a way to check whether an element is definitely not in a set or possibly in it, with a small probability of false positives.
A Bloom Filter uses multiple hash functions to map elements to a fixed-size bit array. Checking for membership involves verifying if all corresponding bits are set. They do not directly store data and, therefore, are space-efficient. However, it does not support deletions.
Expected Behaviour