How do I use an algorithm from xtaci/algorithms in my C++ project?

Simply include the relevant header file from the include directory in your code. Each algorithm has a demo in the src folder that shows usage, so refer to those for practical examples and verification.

Is xtaci/algorithms compatible with C++17?

The implementations may not fully utilize C++17 features, as the project focuses on correctness and simplicity with older C++ styles. Check individual headers, but expect potential integration challenges with modern codebases.

xtaci/algorithms vs the C++ Standard Template Library (STL) for data structures?

xtaci/algorithms provides educational, single-header implementations focused on correctness and learning, while STL offers optimized, standardized containers and algorithms integrated into C++. Use this for reference or specific needs, and STL for production-ready code.

Can I contribute to xtaci/algorithms, and how?

Yes, contributions are encouraged via pull requests. The README states that correctness is the top priority, so ensure your implementations are verified through demos before submitting, following the convention of one header file per algorithm.

Does xtaci/algorithms have performance benchmarks?

No, the project does not emphasize performance benchmarks; it prioritizes correctness and ease of use with demo programs. For performance-critical applications, you may need to optimize the code or seek other libraries.

What license does xtaci/algorithms use?

The license is not explicitly stated in the provided README, so check the repository's LICENSE file or GitHub page for details. Common open-source licenses like MIT or GPL might apply, affecting usage in commercial projects.

Open-Awesome

algorithms

MITC++v1.0

A collection of classic algorithms and data structures implemented as single-header C++ files with demo programs.

GitHub

5.4k stars1.5k forks0 contributors

What is algorithms?

Algorithms & Data Structures in C++ is a library providing implementations of classic computer science algorithms and data structures. It solves the problem of needing reliable, modular, and easy-to-integrate algorithmic code for C++ projects, particularly in server-side environments. Each algorithm is self-contained in a single header file and includes a demo program for verification.

Target Audience

C++ developers, especially those working on Linux server applications, students learning algorithms, and engineers needing ready-to-use implementations of data structures and algorithms.

Value Proposition

Developers choose this for its correctness, simplicity, and modularity—each algorithm is a single header file with a demo, making it easy to learn, integrate, and modify without external dependencies.

Overview

Algorithms & Data structures in C++.

Use Cases

Best For

Learning classic algorithms through clean C++ implementations
Integrating specific data structures into server-side C++ projects
Quickly prototyping algorithms without writing from scratch
Studying algorithm design and optimization techniques
Referencing correct implementations for educational purposes
Building foundational knowledge for coding interviews

Not Ideal For

Projects requiring modern C++ standards (C++11/14/17/20) or seamless STL integration
Cross-platform applications targeting Windows with MSVC or other non-Linux environments
Performance-critical systems where optimized, benchmarked implementations are essential
Teams needing an actively maintained library with comprehensive documentation and regular updates

Pros & Cons

Pros

Modular Single-Header Design

Each algorithm is self-contained in a single .h file, making it easy to include and modify without external dependencies, as emphasized in the README.

Educational Demos Included

Every algorithm comes with a demo program that illustrates usage and verifies correctness, aiding in learning and integration, as stated in the goal.

Broad Algorithm Coverage

Implements a wide range from sorting to graph theory and cryptography, providing a comprehensive reference set for classical algorithms.

Server-Side Focus

Optimized for Linux/gcc environments, aligning with common backend development setups and reducing compatibility issues there.

Cons

Outdated C++ Standards

Implementations may not leverage modern C++ features, potentially clashing with contemporary codebases that use C++11 or later for better performance and safety.

Cross-Platform Limitations

Primarily designed for Linux/gcc, so porting to other platforms like Windows requires extra effort, as hinted by the contribution for MSVC compatibility.

Inconsistent Maintenance

Relies on community pull requests, which can lead to gaps in updates and long-term support for all algorithms, despite correctness being a priority.

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