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Bloom Filter & Hash Function Analysis

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Bloom-Filter

In this program, I create a bloom filter and analyze performances of pairs of integer hash functions and string hash functions. There is a short report on their performances.

Bloom filters are data structures that represent sets and allow the user to query whether a given item is a member of the set or not. They use hash functions and a clever storage mechanism to represent sets using very little memory. The cost of this is the occasional false positive - a Bloom filter may report that an item is in the set when it is not.bf

The integer hash functions I use are: Division Hash, Reciprocal Hash and Squreroot Hash. The string hash functions I use are: Jenkins Hash and Pearson Hash.

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  • C++ 85.7%
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