generic

Introduction to Generic Data Structures

The Generic Data Structures project is an impressive initiative that provides a comprehensive suite of generic data structures. This project is meticulously crafted to serve developers seeking efficient and ready-to-use data structures in their software projects.

Overview of the Package

This package is designed to be a go-to tool for various generic data structures, encapsulating several useful and essential structures. Here is an overview of the key structures included in the project:

• array2d: This is a two-dimensional array, perfect for scenarios requiring matrix-like data storage.

• avl: An AVL tree, offering a balanced binary search tree that ensures logarithmic time complexity for insertion, deletion, and lookup operations.

• bimap: A bidirectional map that allows users to look up keys through values and vice versa, enhancing flexibility in managing associations.

• btree: A B-tree used for storage, which maintains sorted data and allows searches, sequential access, insertions, and deletions in logarithmic time.

• cache: A map wrapper utilizing a maximum size, wherein elements are evicted using the Least Recently Used (LRU) policy when the cache is full.

• hashmap and hashset: These are integral storage structures; the hashmap uses linear probing for efficient key-value mapping, supporting efficient copying via copy-on-write. The hashset uses the hashmap for storage, offering a set abstraction.

• heap: A binary heap useful for priority queue applications, characterized by its property where parent nodes are ordered by value with respect to their children.

• interval: An interval tree based on an augmented AVL tree, allowing for efficient overlap queries which are crucial in many computational tasks involving ranges.

• list and ulist: These structures offer linked lists—list being a standard doubly-linked list, while ulist provides an un-rolled version for enhanced efficiency in specific use cases.

• mapset: A simple set that leverages Go's native map functionality for storage.

• multimap: Enables associative containment where multiple items can be stored for a single key, useful in multi-valued contexts.

• queue and stack: Fundamental data structures following FIFO (First In First Out) and LIFO (Last In First Out) methodologies, respectively.

• rope and prope: The rope structure allows efficient manipulation (insertion and deletion) of arrays, particularly useful for byte arrays, while prope extends this by enabling persistent versions managing multiple versions with minimal resource overhead.

• trie: A ternary search trie structure, streamlined for efficient string storage and retrieval tasks.

Developers and Contribution

The project's ethos encourages open-source collaboration, welcoming developers to contribute. Contributions might include introducing new data structures such as bloom filters or graph structures, implementing sophisticated benchmarks for optimization, or enhancing tests using Go's fuzzing capabilities.

Documentation and Usage

To assist developers in integrating these data structures, each subpackage is accompanied by detailed documentation and examples. This ensures that users can quickly adopt and deploy the data structures in their applications.

The Generic Data Structures project represents a valuable resource for developers, offering robust, well-tested structures ready to support efficient data handling in various applications. With its commitment to collaboration and innovation, the project continues to evolve, adapting to the latest needs in software development.