open-addressing

Templated type-safe hashmap implementation in C using open addressing and linear probing for collision resolution.

Fast and memory-efficient immutable collections and helper data structures

An open addressing linear probing hash table, tuned for delete heavy workloads

Faster.Map — A high-performance SIMD-accelerated .NET dictionary and hashmap designed for extreme speed, scalability, and low memory overhead. Ideal for real-time systems and game engines.

Fast & memory efficient hash tables for Java

A collection of std-like containers written in C++11. Features fast unordered flat map/set, configurable double-ended vector and sparse deque.

Blazingly fast hash table implementation in C using open addressing with linear probing and Robin Hood hashing for collision resolution.

Optimal open-addressing hash maps (Elastic Hashing & Funnel Hashing) in Rust, with Python bindings.

A lightweight single-header open-addressing hashtable implementation in ANSI C

Comparison of Hashing Algorithms - Double Hashing, Robin Hood Hashing Cuckoo Hashing with Java's inbuilt HashMap/ HastSet over million of add(), contains() and remove() operations.

Data structures and algorithms implementation in pure C#!

Yet another efficient hashmap implementation for Golang based on the hopscotch open addressing scheme.

Implementing Hash-Table Lexicon using open-addressing and quadratic probing.

C Program For Open Address Collision

LinearMap is a minimalistic, high-performance hash map built around open addressing with linear probing. Instead of relying on buckets, used by std::unordered_map, it uses a fully contiguous memory layout to squeeze out every bit of performance modern CPUs can offer.

This repository contains all the data structures and their application in Java.

The project on comparison of different hashing approaches

Hash-Table implementation using Python. (Chaining, Open Addressing & Resizing)

In this project, I used CSV module to implement CRUD operations on CSV file using Python Programming Language. The CSV file has over 400,000 records of phone numbers. Searching them linearly may cause a lot of time. Therefore, I used Hash Table to search phone numbers in O(1).

Simple alternative to hcreate_r, hsearch_r, hdestroy_r GNU extensions