Open Source Mac Algorithms - Page 11
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Algorithms for Mac
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Implementation of Damerau-Levenshtein fuzzy string matching in Java. Returns the distance adding one point per character insert, deletion, mismatche and swap.. This is an extension of apache/commons/lang/StringUtils.getLevenshteinDistance()
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DXE Encryption Algorithm
DXE (Darkgust's Xor Encoder) is an encryption algorithm made in VB.NET
DXE (Darkgust's Xor Encoder) is an encryption algorithm made in Visual Basic .NET . -
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A light-weight group communication system/library of distributed algorithms implementations for agreement problems (e.g., Consensus, Unreliable Leader Election and Atomic Broadcast).
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Damerau Levenshtein
Java Library for Damerau Levenshtein Algorithm
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This is an implementation of Donald Knuth's Algorithm X ("dancing links"). This is primarily a sudoku generator and solver, though it can be used to solve other exact cover problems.
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Very fast and easy to use Java tool for solving and generating Sudoku puzzles. By using Donald Knuths exact cover algorithmus it can not only solve or create the usual 9x9 but also 4x4, 16x16 or even bigger Sudokus in a very efficient way.
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Data Algorithm/leetcode/lintcode
Data Structure and Algorithm notes
This work is some notes of learning and practicing data structures and algorithms. Part I is a brief introduction of basic data structures and algorithms, such as, linked lists, stack, queues, trees, sorting and etc. This book notes about learning data structure and algorithms. It was written in Simplified Chinese but other languages such as English and Traditional Chinese are also working in progress. -
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The Data Structure & Algorithm Library (DSAL) is a library of classical data structure and algorithm.
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Data Structures and Algorithms in JS
Data Structures and Algorithms explained and implemented in JavaScript
Are you a JavaScript developer looking to improve your craft? Then, this algorithms book is for you. This material contains the fundamental concepts to move your career to the next level. You will be able to solve problems faster in your day-to-day work and ace technical job interviews. Simply put, algorithms are several steps to solve a specific problem (e.g., sort number, search value, transform data, etc.). Algorithms are an essential toolbox for every programmer. Even if you don't realize it, you use them every day. They are built-in in apps, programming languages, and libraries. However, to make use of them properly, you have to know the tradeoffs so you can choose the best tool for the job. Improve your problem-solving skills and become a stronger developer by understanding fundamental computer science concepts. -
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DataUsagePrinter
Creates printable string of data usage
A simple utility which creates a printable string of data usage. E.g. supply the value 1234567890 and DataUsagePrinter will return the string "1GB 153MB 384KB 722B". Available as binary and source downloads for Java and C#. -
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For each Date/Time since 1582-Oct-15 (start Gregorian Calendar): ++ add/sub days&hh:mm:ss - considered all leap years; summer time DST ++ compute start/end of DST ++ compute UTC (Greenwich) to local/DST ++ weekdays ++ Excel compatible date value
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This chess program changes its strength to give the best match against you. Eventually it learns to beat you specifically through learning alogirthms. Features included transposition tables and a elementary 3-piece endgame tablebase.
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DecisionTree.jl
Julia implementation of Decision Tree (CART) Random Forest algorithm
Julia implementation of Decision Tree (CART) and Random Forest algorithms. -
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Delaunator
Fast JavaScript library for Delaunay triangulation of 2D points
Delaunator is a fast library for Delaunay triangulation. It takes as input a set of points. The triangulation is represented as compact arrays of integers. It’s less convenient than other representations but is the reason the library is fast. After constructing a delaunay = Delaunator.from(points) object, it will have a triangles array and a halfedges array, both indexed by half-edge id. What’s a half-edge? A triangle edge may be shared with another triangle. Instead of thinking about each edge A↔︎B, we will use two half-edges A→B and B→A. Having two half-edges is the key to everything this library provides. It will also be useful to have some helper functions to go from one half-edge to the next and previous half-edges in the same triangle. We can draw all the triangle edges without constructing the triangles themselves. -
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Depends implements a generic dependency tracker written in C++ and comes with extensive documentation on how to implement a dependency tracker (and, thus, how this one is implemented). It is very simple to use and provides the tools to "roll your own"
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Detectron2
Next-generation platform for object detection and segmentation
Detectron2 is Facebook AI Research's next generation software system that implements state-of-the-art object detection algorithms. It is a ground-up rewrite of the previous version, Detectron, and it originates from maskrcnn-benchmark. It is powered by the PyTorch deep learning framework. Includes more features such as panoptic segmentation, Densepose, Cascade R-CNN, rotated bounding boxes, PointRend, DeepLab, etc. Can be used as a library to support different projects on top of it. We'll open source more research projects in this way. It trains much faster. Models can be exported to TorchScript format or Caffe2 format for deployment. With a new, more modular design, Detectron2 is flexible and extensible, and able to provide fast training on single or multiple GPU servers. Detectron2 includes high-quality implementations of state-of-the-art object detection. -
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This project is an extended implementation of Knuth's "Dancing Links" algorithm and some use cases (e.g. Sudoku).
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DifferenceKit
A fast and flexible O(n) difference algorithm framework
A fast and flexible O(n) difference algorithm framework for Swift collection. The algorithm is optimized based on the Paul Heckel’s algorithm. This is a diffing algorithm developed for Carbon, works stand alone. The algorithm optimized based on the Paul Heckel’s algorithm. See also his paper A technique for isolating differences between files released in 1978. It allows all kind of diffs to be calculated in linear time O(n). RxDataSources and IGListKit are also implemented based on his algorithm. The type of the element that to take diffs must be conform to the Differentiable protocol. -
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Robust Perl OO Module for Digest based Authentication leveraging DBI as a backend. This Performance oriented Hash Authentication Library is scalable from single pc to multi-database single signon www applications. Optionally uses Javascript and Cookies.
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Distributed Multithread Apriori (DMTA)
A parallel implementation using MPI and OpenMP to Apriori algorithm
DMTA (Distributed Multithreaded Apriori) is a parallel implementation of Apriori algorithm, which exploits the parallelism at the level of threads and processes, seeking to perform load balancing among the cores. Was implemented in C++ language, using the parallelization libraries OpenMP and MPI. The algorithm was generated as a result of a project developed by André Camilo Bolina, under the guidance of teachers Marluce Rodrigues Pereira, Ahmed Ali Abdalla Esmin and Denilson Alves Pereira, in Department of Computer Science at Federal University of Lavras. The results of this project were published in the Revista de Sistemas de Informação da FSMA and is available in http://www.fsma.edu.br/si/edicao11/FSMA_SI_2013_1_Principal_1.html -
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Free scripts & examples- JSP, Eclipse, SQL, PHP, ASP, Win32 Batch, Javascript, Flash/Actionscript. -=-=-=-=-=-=- NOTE: This project is closed. For new development related to integrating Beyond Compare with Eclipse, see http://beyondcvs.sourceforge.net/
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DomainBed
DomainBed is a suite to test domain generalization algorithms
DomainBed is a PyTorch-based research suite created by Facebook Research for benchmarking and evaluating domain generalization algorithms. It provides a unified framework for comparing methods that aim to train models capable of performing well across unseen domains, as introduced in the paper In Search of Lost Domain Generalization. The library includes a wide range of well-known domain generalization algorithms, from classical baselines such as Empirical Risk Minimization (ERM) and Invariant Risk Minimization (IRM) to more advanced techniques like Domain Adversarial Neural Networks (DANN), Adaptive Risk Minimization (ARM), and Invariance Principle Meets Information Bottleneck (IB-ERM/IB-IRM). DomainBed also integrates multiple standard datasets—including RotatedMNIST, PACS, VLCS, Office-Home, DomainNet, and subsets from WILDS—allowing consistent experimentation across image classification tasks. -
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Dopamine
Framework for prototyping of reinforcement learning algorithms
Dopamine is a research framework for fast prototyping of reinforcement learning algorithms. It aims to fill the need for a small, easily grokked codebase in which users can freely experiment with wild ideas (speculative research). This first version focuses on supporting the state-of-the-art, single-GPU Rainbow agent (Hessel et al., 2018) applied to Atari 2600 game-playing (Bellemare et al., 2013). Specifically, our Rainbow agent implements the three components identified as most important by Hessel et al., n-step Bellman updates, prioritized experience replay, and distributional reinforcement learning. For completeness, we also provide an implementation of DQN (Mnih et al., 2015). For additional details, please see our documentation. We provide a set of Colaboratory notebooks which demonstrate how to use Dopamine. We provide a website which displays the learning curves for all the provided agents, on all the games. -
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DualPipe
A bidirectional pipeline parallelism algorithm
DualPipe is a bidirectional pipeline parallelism algorithm open-sourced by DeepSeek, introduced in their DeepSeek-V3 technical framework. The main goal of DualPipe is to maximize overlap between computation and communication phases during distributed training, thus reducing idle GPU time (i.e. “pipeline bubbles”) and improving cluster efficiency. Traditional pipeline parallelism methods (e.g. 1F1B or staggered pipelining) leave gaps because forward and backward phases can’t fully overlap with communication. DualPipe addresses that by scheduling micro-batches from both ends of the pipeline in a bidirectional fashion—i.e. some micro-batches flow forward while others flow backward—so that computation on one partition can coincide with communication for another. -
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DuranDuranbot
Teachable/trainable artificially intelligent music bot
A teachable/trainable artificially intelligent music bot fundamentally inspired by how the new wave band Duran Duran composes music. This program utilizes many algorithmic/AI techniques/processes, including machine learning; which allow you to teach/train it to compose music which you prefer... and the technique which is the foundation of the design of DuranDuranbot, which was directly inspired by how Duran Duran writes music........ Called, "bit by bit circular composition"....... and it's explanation can be found here - https://scsynth.org/t/bit-by-bit-circular-composition/1107 This program is written in the SuperCollider programming language - https://en.wikipedia.org/wiki/SuperCollider Contact - ken_brant@ymail.com
