feat: spring 2025, all hands project 3, team 4 - Hashing Algorithm Runtime and Collision Analysis #37
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This PR was not submitted by the entire team and is superseded by a different PR and thus I am closing this PR. With that said, my impression is that this PR did contain the majority of the required content for the article. |
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Description:
This pull request delves into the analysis of various hashing algorithms, focusing on their performance in terms of collision frequency and runtime efficiency. The algorithms explored include Python's built-in hash(), MurmurHash, DJB2, and a custom modulo hash. The analysis is based on datasets of varying sizes (5k, 10k, and 20k entries) to assess how each algorithm behaves in different conditions. This PR provides insights into the strengths and weaknesses of these algorithms and contributes to understanding their efficiency in dictionary-based data storage scenarios.
Key Changes:
Added performance benchmarks for different hashing algorithms.
Included collision frequency and runtime analysis for datasets of 5k, 10k, and 20k entries.
Included comparison across multiple algorithms for better understanding of their efficiency..