Search Results for "graph algorithm"

ngraph.path is a JavaScript library that implements efficient pathfinding algorithms for graphs, primarily designed to compute shortest paths in weighted or unweighted networks. It provides a clean API for constructing graph models, assigning weights to edges, and querying for optimal routes between nodes, making it useful for routing, games, maps, and network optimization. The library includes several algorithm implementations such as A*, Dijkstra’s, and breadth-first search, each suited to different types of graph structure and performance needs. It can be integrated with visualization libraries like VivaGraphJS to animate or highlight computed paths in a rendered graph, enabling interactive routing features. ...

The Pythonic Data Structures and Algorithms repository by keon is a hands-on collection of implementations of classical data structures and algorithms written in Python. It offers working, often well-commented code for many standard algorithmic problems — from sorting/searching to graph algorithms, dynamic programming, data structures, and more — making it a valuable resource for learning and reference. For students preparing for technical interviews, self-learners brushing up on fundamentals, or developers wanting to understand algorithm internals, this repository provides ready-to-run examples, and can serve as a sandbox to experiment, benchmark, or adapt code. ...

javascript-algorithms is a repository that implements a comprehensive collection of classic data structures and algorithmic solutions in JavaScript — including sorting, searching, graph algorithms, dynamic programming, and more. It serves as a learning and reference resource for developers wanting to understand how standard algorithms can be expressed in JavaScript, bridging the gap between theoretical algorithm knowledge and practical implementation usable in web or Node.js contexts. Because algorithms are implemented in a language (JavaScript) many developers use daily, the repo becomes especially useful for students, interview-preparation candidates, or anyone wanting to learn algorithmic thinking without switching languages. ...

Algorithms in Python is a collection of algorithm and data structure implementations (primarily in Python) meant to serve as both learning material and reference code for engineers. It includes code for graph algorithms, heap data structures, stacks, queues, and more — each implemented cleanly so learners can trace logic and adapt for their problems. The repository is particularly useful for people preparing for competitive programming, job interviews, or building a foundational understanding of algorithmic patterns. ...

Graphal is an interpreter of a programming language that is mainly oriented to graph algorithms. There is a command line interpreter and a graphical integrated development environment. The IDE contains text editor for programmers, compilation and script output, advanced debugger and visualization window. The progress of the interpreted and debugged graph algorithm can be displayed in 3D scene.

The subgraph matching problem (subgraph isomorphism) is NP-complete. Previously, we designed an exact subgraph matching (ESM) algorithm for dependency graphs using a backtracking approach (http://esmalgorithm.sourceforge.net). We further designed an approximate subgraph matching (ASM) algorithm that is capable of detecting approximate subgraph matching based on a subgraph distance. Assume that the graph G and the subgraph Gs have m and n vertices, and km and kn edges respectively, the total worst-case algorithm complexity is O(m^n * n(n-1)/2 * km * log m). ...

Game Toolbox is a C# assembly designed to facilitate the creation of games and game prototypes. It contains no graphics code, does not depend on XNA, and is Mono-compatible. It provides implementations of A*, GOAP, a genetic algorithm, and more.

LSGTL means LLX’s Static Graph Template Library which is a light-weighted header-only template library developed mainly for static graph analysis. LSGTL is expected to be used in laboratories for research purposes mostly.

A threaded Web graph (Power law random graph) generator written in Python. It can generate a synthetic Web graph of about one million nodes in a few minutes on a desktop machine. It implements a threaded variant of the RMAT algorithm.