shomali11/go-interview
Go Interview
This project is a Go algorithm implementation library designed for technical interview preparation. It provides a collection of common data structures and algorithmic solutions to help practice for software engineering coding assessments.
The library includes a custom data structure collection featuring linked lists, stacks, queues, trees, and hash maps. It also implements specific algorithmic solutions, such as A* pathfinding for calculating the shortest path between nodes and a real-time stream processor for computing moving averages and running medians from continuous data inputs.
Features
- Algorithmic Problem Solving - Provides a collection of algorithmic solutions specifically designed for technical interview and coding assessment preparation.
- Algorithm Implementations - Provides practical code implementations of algorithms and design patterns for computational problems.
- Technical Interview Preparation - Offers a comprehensive set of resources and implementations for preparing for technical coding interviews.
- Data Structures - Implements fundamental memory-based structures including linked lists, stacks, queues, and trees.
- Algorithm Libraries - A comprehensive library of common data structures and algorithms implemented in Go.
- Data Structure Implementations - Provides practical implementations of fundamental structures like linked lists, stacks, and hash maps.
- Linked Data Structures - Implements fundamental pointer-based structures like linked lists for efficient data organization.
- Real-Time Data Processors - Implements a real-time data processor to ingest and transform streams for continuous analytics.
- Stream Median Calculators - Implements specialized calculators for determining the median of a continuous number stream.
- Stream Analytics - Computes real-time moving averages and running medians from continuous data inputs.
- Sliding Window Algorithms - Implements sliding window techniques to process contiguous data buffers for real-time metrics.
- Heuristic Graph Search Algorithms - Implements graph traversal algorithms that use heuristic estimates to optimize pathfinding.
- Shortest Path Algorithms - Provides algorithms to calculate the most efficient route between nodes in a graph.
- Pathfinding Algorithms - Implements graph traversal and pathfinding algorithms to find optimal routes.
- Median Tracking - Implements a two-heap system to track the running median of a continuous data input.
- Priority Queues - Utilizes priority queues to manage and track the lowest-cost nodes during pathfinding.
