Open Source UML Tools
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UML Tools
View 4980 business solutionsBrowse free open source UML tools and projects below. Use the toggles on the left to filter open source UML tools by OS, license, language, programming language, and project status.
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SafetyIQ is revolutionizing the way businesses approach safety. As a leading provider of comprehensive workplace safety software, we cater to four key areas: Mobile Worker Safety, EHS (Environment, Health, and Safety), Fatigue Management, and Training. Our platform is designed to safeguard your workers, no matter their location or task, ensuring all-around safety compliance. Unlike most safety software providers that only react to incidents or implement proactive measures, SafetyIQ introduces a third pillar to safety management - predictive analytics. We transform the untapped wealth of safety data within your organization into actionable insights to inform safety strategies, mitigating risks even before they aris
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Ditch those spreadsheets, shared drives & crazy-expensive solutions with too many bells & whistles. ContractSafe offers the simplest way to manage your contracts efficiently without breaking the bank.
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crystal-facet-uml
Create consistent Uml diagrams
As software architect, you create a set of diagrams describing use-cases, requirements, structural views, behavioral and deployment views. crystal_facet_uml keeps element names and element hierarchies consistent. It exports diagrams in svg, pdf, ps and png formats to be used in text processing systems like docbook, html, latex. This tool runs on your local PC and is based on glib, gdk, gtk, cairo, pango, sqlite. -
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ECLiPSe CLP
ECLiPSe Constraint Logic Programming System
The ECLiPSe Constraint Logic Programming System is designed for solving combinatorial optimization problems, for the development of new constraint solver technology and their hybrids, and for the teaching of modelling, solving and search techniques. -
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AWS Deep Learning Containers
A set of Docker images for training and serving models in TensorFlow
AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet. Deep Learning Containers provide optimized environments with TensorFlow and MXNet, Nvidia CUDA (for GPU instances), and Intel MKL (for CPU instances) libraries and are available in the Amazon Elastic Container Registry (Amazon ECR). The AWS DLCs are used in Amazon SageMaker as the default vehicles for your SageMaker jobs such as training, inference, transforms etc. They've been tested for machine learning workloads on Amazon EC2, Amazon ECS and Amazon EKS services as well. This project is licensed under the Apache-2.0 License. Ensure you have access to an AWS account i.e. setup your environment such that awscli can access your account via either an IAM user or an IAM role. -
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ConceptBase.cc
A Database System for Metamodeling and Method Engineering
ConceptBase.cc is a multi-user deductive and object-oriented database system for metamodeling and method engineering. Includes a graphical client that builds upon the logic-based features of the ConceptBase.cc server. The data model is O-Telos. ConceptBase.cc can represent information at the data level (example data, traces of process executions etc.), the class level (schemas, process definitions etc.), the metaclass level (constructs of modeling languages), the meta-metaclass level (constructs for defining modeling languages), and so forth. ConceptBase.cc is developed by the ConceptBase Team at University of Skövde (HIS). ConceptBase.cc supports Linux, Mac OS X and Windows. ConceptBase.cc is free software distributed under a FreeBSD-style license. -
Chat with your business data with Looker. More than just a modern business intelligence platform, you can turn to Looker for self-service or governed BI, build your own custom applications with trusted metrics, or even bring Looker modeling to your existing BI environment.
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SimpleDiagramControl
Control to create diagrams in winform applications in C# (.NET)
Diagram control to allow the creation of many types of diagrams in .NET. The behaviour of the control is determined by implementing a controller Created in C# -
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Mongoose
Elegant mongodb object modeling for node.js
Mongoose is a MongoDB object modeling tool that was built to answer the need for better ways to model your application data. It's designed to work in an asynchronous environment, providing a simple, straightforward approach to object modeling that skips out on the tedious tasks of writing MongoDB validation, casting and business logic boilerplate. Mongoose offers an uncomplicated schema-based solution, and comes with nifty features like type casting, validation, query building, and business logic hooks right out of the box. Mongoose also has a rich set of plugins made by the community and you can write your own to make Mongoose an even better solution for your needs. -
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Laravel MongoDB
MongoDB based eloquent model and Query builder for Laravel
This package adds functionalities to the Eloquent model and Query builder for MongoDB, using the original Laravel API. This library extends the original Laravel classes, so it uses exactly the same methods. Make sure you have the MongoDB PHP driver installed. In case your Laravel version does NOT autoload the packages, add the service provider to config/app.php. For usage with Lumen, add the service provider in bootstrap/app.php. In this file, you will also need to enable Eloquent. You must however ensure that your call to $app->withEloquent(); is below where you have registered the MongodbServiceProvider. The service provider will register a MongoDB database extension with the original database manager. There is no need to register additional facades or objects. When using MongoDB connections, Laravel will automatically provide you with the corresponding MongoDB objects. -
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statsmodels
Statsmodels, statistical modeling and econometrics in Python
statsmodels is a Python module that provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests, and statistical data exploration. An extensive list of result statistics are available for each estimator. The results are tested against existing statistical packages to ensure that they are correct. The package is released under the open source Modified BSD (3-clause) license. Generalized linear models with support for all of the one-parameter exponential family distributions. Markov switching models (MSAR), also known as Hidden Markov Models (HMM). Vector autoregressive models, VAR and structural VAR. Vector error correction model, VECM. Robust linear models with support for several M-estimators. statsmodels supports specifying models using R-style formulas and pandas DataFrames. -
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NOTE: The GROOVE codebase has moved to https://github.com/nl-utwente-groove
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Whether natural disaster, cyberattack, or plain-old human error, data can disappear in the blink of an eye. ConnectWise BCDR (formerly Recover) delivers reliable and secure backup and disaster recovery backed by powerful automation and a 24/7 NOC to get your clients back to work in minutes, not days.
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SageMaker Training Toolkit
Train machine learning models within Docker containers
Train machine learning models within a Docker container using Amazon SageMaker. Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. To train a model, you can include your training script and dependencies in a Docker container that runs your training code. A container provides an effectively isolated environment, ensuring a consistent runtime and reliable training process. The SageMaker Training Toolkit can be easily added to any Docker container, making it compatible with SageMaker for training models. If you use a prebuilt SageMaker Docker image for training, this library may already be included. Write a training script (eg. train.py). Define a container with a Dockerfile that includes the training script and any dependencies. -
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Extracts dependencies and OO metrics from Java class files produced by most Java compilers. Computes API differences between versions. No source needed. Includes both Swing and command-line interfaces, with XSL stylesheets for formatting output.
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TRAK Viewpoints
Specifications for TRAK architecture views
The architecture viewpoints (specifications for architecture views iaw ISO 42010) for TRAK. TRAK is a general systems-thinkers'/system engineering enterprise architecture framework. It is simple, user-friendly, pragmatic and not limited to IT. 100% triple-centric and semantically-sound. Defines a total of 24 viewpoints. The ones needed are selected by taking the task sponsor's concerns and matching them to the typical concerns that each TRAK viewpoint addresses. The triples that address each concern are defined in the TRAK metamodel (https://sf.net/p/trakmetamodel). The mapping between metamodel triple and architecture viewpoint is held with a Neo4J graph model (https://doi.org/10.1002/eng2.12168) and defined using (more) architecture viewpoints (https://www.researchgate.net/publication/335176248_Architecture_Description_Viewpoints_Metamodel_Description_Implementation_and_Model_Changes). The minimal process is defined in the overall TRAK specification (https://sf.net/p/trak) -
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TensorFlow.js
TensorFlow.js is a library for machine learning in JavaScript
TensorFlow.js is a library for machine learning in JavaScript. Develop ML models in JavaScript, and use ML directly in the browser or in Node.js. Use off-the-shelf JavaScript models or convert Python TensorFlow models to run in the browser or under Node.js. Retrain pre-existing ML models using your own data. Build and train models directly in JavaScript using flexible and intuitive APIs. Tensors are the core datastructure of TensorFlow.js They are a generalization of vectors and matrices to potentially higher dimensions. Built on top of TensorFlow.js, the ml5.js library provides access to machine learning algorithms and models in the browser with a concise, approachable API. Comfortable with concepts like Tensors, Layers, Optimizers and Loss Functions (or willing to get comfortable with them)? TensorFlow.js provides flexible building blocks for neural network programming in JavaScript. -
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Laravel Media Library
Associate files with Eloquent models
This package can associate all sorts of files with Eloquent models. It provides a simple, fluent API to work with. The Pro version of the package offers Blade, Vue and React components to handle uploads to the media library and to administer the content of a medialibrary collection. The storage of the files is handled by Laravel's Filesystem, so you can use any filesystem you like. Additionally the package can create image manipulations on images and pdfs that have been added in the media library. -
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OrientDB
DBMS supporting graph, document, full-text and geospatial models
OrientDB is an Open Source Multi-Model NoSQL DBMS with the support of Native Graphs, Documents, Full-Text search, Reactivity, Geo-Spatial and Object Oriented concepts. It's written in Java and it's amazingly fast. No expensive run-time JOINs, connections are managed as persistent pointers between records. You can traverse thousands of records in no time. Supports schema-less, schema-full and schema-mixed modes. Has a strong security profiling system based on user, roles and predicate security and supports SQL amongst the query languages. Thanks to the SQL layer it's straightforward to use for people skilled in the Relational world. OrientDB adheres to the NoSQL movement even though it supports ACID Transactions and SQL as query language. In this way it's easy to start using it without having to learn too much new stuff. -
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DMF: Distributed Multiplatform Framework
Development framework including code generator and UML ex/import
A component based programming framework. This project is aimed to support various target frameworks. A wxWidgets based GUI application is the major sample which also provides rapid database GUI design with UML import and export (db reverse engineering). -
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torchvision
Datasets, transforms and models specific to Computer Vision
The torchvision package consists of popular datasets, model architectures, and common image transformations for computer vision. We recommend Anaconda as Python package management system. Torchvision currently supports Pillow (default), Pillow-SIMD, which is a much faster drop-in replacement for Pillow with SIMD, if installed will be used as the default. Also, accimage, if installed can be activated by calling torchvision.set_image_backend('accimage'), libpng, which can be installed via conda conda install libpng or any of the package managers for debian-based and RHEL-based Linux distributions, and libjpeg, which can be installed via conda conda install jpeg or any of the package managers for debian-based and RHEL-based Linux distributions. It supports libjpeg-turbo as well. libpng and libjpeg must be available at compilation time in order to be available. TorchVision also offers a C++ API that contains C++ equivalent of python models. -
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Linguistic Tree Constructor
Syntax tree editor for rapid annotation of existing text
Linguistic Tree Constructor (LTC) is a tool for drawing lingusitic syntax trees of already-existing text. It is a syntax editor, not a text editor, so the text has to exist already. It is best suited for large-scale, rapid creation of hand-annotated treebanks. The user can define their own node categories, and can label each node with labels, also definable by the user. LTC supports "generic", X-Bar and RRG trees. Supports interlinear texts in SIL SFM format. -
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The GR module for Julia
Plotting for Julia based on GR
This is the GR module for Julia. It places a Julia interface to GR, a universal framework for visualization applications. GR allows users to create high quality, engaging visualizations, everything from 2D graphs to complex 3D scenes. With this module simply type in Julia 'using gr', and you can instantly start calling functions in the GR framework API. GR is based on an implementation of a Graphical Kernel System (GKS) and OpenGL. As a self-contained system, integration into existing applications is quick and easy-- simply use a direct call from Julia with ccall syntax. -
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Software developed for the analysis of Neutron Reflectivity data.
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TensorFlow Model Garden
Models and examples built with TensorFlow
The TensorFlow Model Garden is a repository with a number of different implementations of state-of-the-art (SOTA) models and modeling solutions for TensorFlow users. We aim to demonstrate the best practices for modeling so that TensorFlow users can take full advantage of TensorFlow for their research and product development. To improve the transparency and reproducibility of our models, training logs on TensorBoard.dev are also provided for models to the extent possible though not all models are suitable. A flexible and lightweight library that users can easily use or fork when writing customized training loop code in TensorFlow 2.x. It seamlessly integrates with tf.distribute and supports running on different device types (CPU, GPU, and TPU). -
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PyMC3
Probabilistic programming in Python
PyMC3 allows you to write down models using an intuitive syntax to describe a data generating process. Fit your model using gradient-based MCMC algorithms like NUTS, using ADVI for fast approximate inference — including minibatch-ADVI for scaling to large datasets, or using Gaussian processes to build Bayesian nonparametric models. PyMC3 includes a comprehensive set of pre-defined statistical distributions that can be used as model building blocks. Sometimes an unknown parameter or variable in a model is not a scalar value or a fixed-length vector, but a function. A Gaussian process (GP) can be used as a prior probability distribution whose support is over the space of continuous functions. PyMC3 provides rich support for defining and using GPs. Variational inference saves computational cost by turning a problem of integration into one of optimization. PyMC3's variational API supports a number of cutting edge algorithms, as well as minibatch for scaling to large datasets. -
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A multi-notational modeling toolkit that supports the NFR framework, i* Framework, KAOS, Problem Frames, BPMN and UML notations. For more information, please visit the project's Wiki page at https://sourceforge.net/p/re-tools/wiki/Home/.
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Open tool platform for the cost effective rigorous development of dependable complex software systems services. This platform is based on the event-B formal method and provides natural support for refinement and mathematical proof.
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oracle-architect-tools
oracle pl/sql based tools for design development and maintenance
A suite of open source utilities written in Oracle PL/SQL for schema instrumentation, auditing, schema administration scripting, ddl mapping and migration code generation, dml package generation, and xml service package generation based on metadata tables
Guide to Open Source UML Tools
Open source UML tools are typically programs available to users at no cost and can be modified by anyone who has access to the source code. These types of tools allow users greater freedom and flexibility when constructing, designing, analyzing, and maintaining diagrams related to Unified Modeling Language (UML). Various types of UML include uses cases, class diagrams, activity diagrams, sequence diagrams, state machines, etc.
Using an open source UML tool typically requires very little in terms of hardware specifications. The majority of these tools provide support for most common desktop operating systems such as Windows or macOS as well as Linux-based distributions. Open source UML tools also usually contain all the necessary features that you would expect from a standard modeling language such as drag-and-drop components for creating models quickly and easily. Many open source UML tools also allow for collaborative work on projects which allows multiple people with varied experience levels to work together in real time and contribute their own ideas to the process.
In addition to being free and user friendly often times many open source UML tools contain plug-ins that expand upon the provided features allowing users even more customization capabilities depending on their needs. Furthermore many of these plugins extend support beyond just basic modelling into areas like code engineering which can allow existing code bases to be visually represented through various graphical elements such as sequence diagrams making analysis easier than ever before.
The benefits of using an open source UML tool to create various models are numerous far ranging from cost savings due not needing any proprietary software license fees all the way up too improved collaboration opportunities among companies when working on joint projects over long distances without ever having met face-to-face in person; overall it is hard to argue against using this type of technology when developing applications or services on a budget while still getting professional quality results in a timely manner every single time.
Features Offered by Open Source UML Tools
- Diagram Modeling: Open source UML tools provide the ability to create a variety of diagrams, including class, sequence, use case, and activity diagrams. These diagrams help to illustrate how components relate to each other and can be used to plan out the structure of an application or system being developed.
- Drag-and-Drop Interaction: Most open source UML tools support drag-and-drop interaction, which allows users to quickly create and arrange elements in their diagram with just a few clicks or keystrokes. This makes it easier for developers to visualize their ideas quickly.
- Version Control: Open source UML tools often come with version control capabilities that enable users to keep track of all changes made in the various models they have created. This helps ensure that modifications are managed efficiently and prevents conflicting versions from arising at any time down the line.
- Automated Code Generation: Many open source UML tools also offer automated code generation features that allow users to easily generate programming code from a given diagram model or models. This reduces development time and ensures accuracy when creating complex applications or systems.
- Collaboration Features: Open source UML tools typically provide collaboration features such as chat rooms or forums where teams of developers can communicate with each other about their models in real-time. This helps make projects run smoother since everyone is kept up-to-date on progress at all times.
What Are the Different Types of Open Source UML Tools?
- StarUML: This type of open source UML tool is popular among developers who use model-driven development. It provides a set of broad features that allow visual modelling and code generation, as well as other useful extras such as project management tools, integration libraries, and access to an online library containing thousands of available model elements.
- Papyrus: Papyrus is a user-friendly UML modeling environment designed to help software architects quickly create UML diagrams of their systems. It offers basic functions for diagramming and can easily be integrated into larger projects using specialized plugins to extend its capabilities.
- ArgoUML: ArgoUML provides powerful techniques for editing large models, diagram creation from existing sources, object orientation support, and requirements management support via the Critic feature. Additionally, its ability to automatically generate code in multiple languages makes it an especially valuable asset for teams with tight time constraints.
- UMLet: UMLet allows users to rapidly draw custom UML diagrams with a focus on usability over detailed graphical capability. Its main draw is simplicity--users can rapidly construct diagrams with minimal effort or prior knowledge of the software platform itself.
- Violet: Violet is another user-friendly open source UML modeling tool which allows for simple drag & drop creation of class diagrams and other types of visual models. It has full support for the most popular programming languages like Java & Python and supports reverse engineering through files or live connections to applications running locally or remotely on a computer network.
Benefits Provided by Open Source UML Tools
- Cost effective: Open source UML tools are usually free of charge, allowing organizations to reap the benefits of a powerful tool without having to pay for it. This can save a lot of money in the long run.
- Flexibility: Open source UML tools allow developers to modify and adjust the software as needed, providing them with the flexibility they need to add features that make sense for their organization or project.
- Support and community: Many open source projects have active communities that provide support and documentation when needed, helping users fix any issues they encounter while using the software.
- Security: Open source UML tools are often better tested than proprietary options, meaning there is less chance of security vulnerabilities being exploited by malicious actors.
- Versatility: Open source UML tools can be used across different platforms, so if an organization needs to use their designs on multiple systems, this is possible with open source tools.
- Extensibility: Since open source projects are designed for customization and modification, users can extend existing functionality or create new ones as needed. This makes it easier to tailor the software to specific requirements.
What Types of Users Use Open Source UML Tools?
- Beginner Users: Those just getting started with a UML (Unified Modeling Language) tool and looking for an easy to use, no-cost solution.
- Hobbyists: Those who are interested in learning more about the capabilities of a UML tool and those who are interested in experimenting with different tools at their own pace.
- Educators: Teachers and professors using open source UML tools to teach students the basics of modeling language development.
- Small Business Owners & Professionals: Individuals looking for a cost effective way to create high quality UML diagrams without spending too much money on premium tools.
- Large Corporation Employees/IT Departments: Companies that want to keep costs low while still delivering high quality visualizations of their systems or processes.
- Researchers: Academic researchers or those from the private sector studying larger systems that require detailed diagrams and analysis over time.
- Open Source Software Developers: Programmers looking for an easy way to visualize code and understand complex underlying processes generated by existing codebases as part of debugging activities or working towards creating viable new software applications or services.
How Much Do Open Source UML Tools Cost?
Open source UML tools are a great way to visualize the design of your applications without having to pay an arm and a leg. They often come with all sorts of features that allow you to draw diagrams, create relationships between objects, and generate code from your designs. Best of all, open source UML tools don’t cost anything. That's right - free as in no charge at all. Of course, you may need to invest some time into learning how to use them effectively, but once you do so there shouldn't be any fees associated with the software itself. This makes them ideal for those who want to build large projects on a budget or just get started quickly and easily on small projects. There are plenty of excellent open source UML tools available today developed by both professional companies and dedicated volunteers from around the world; take advantage of this free resource today.
What Software Can Integrate With Open Source UML Tools?
Open source UML tools are compatible with many types of software. For example, they can be integrated with programming languages such as Python and Java; development environments like Eclipse and IntelliJ IDEA; and issue tracking platforms such as Trac and JIRA. Additionally, open source UML tools can be connected to build automation frameworks like Jenkins, version control systems like Subversion or Git, continuous integration servers such as CruiseControl and Hudson, databases like PostgreSQL and Oracle, and application servers like Tomcat. By connecting these applications to a UML tool, users can automatically generate diagrams from the output of other programs in order to visualize complex data structures more easily.
Recent Trends Related to Open Source UML Tools
- Open source UML tools allow software developers to create models of their code and applications, helping to reduce development time and costs.
- Open source UML tools are becoming increasingly popular because they are free to use and offer a wide range of features that are often superior to those offered in commercial UML tools.
- Open source UML tools have gained traction with developers due to their user-friendly interface, wide range of features, low cost and availability.
- Many open source UML tools offer visual modeling capabilities, which allow developers to easily create diagrams that illustrate the structure of their systems.
- Open source UML tools are also becoming more powerful, offering features such as real-time collaboration, version control, automated code generation and more.
- Some open source UML tools even come with plug-ins that add additional features or enable integration with other applications.
- Open source UML tools are becoming increasingly important for agile development projects, where the ability to quickly build models without the overhead of acquiring commercial licenses is a major benefit.
How To Get Started With Open Source UML Tools
Getting started with open source UML tools is easy and can be done in a few steps. First, pick an open source UML tool that best fits your project needs. This could range from tools like ArgoUML to Visual Paradigm Community Edition to StarUML and more. These tools are available for download online for free, so look around and find the one that works best for you. After that, familiarize yourself with the tool's terminology, functionalities and interface. Most of these tools are reasonably intuitive to grasp but there may still be some learning curve involved depending on how experienced you are with working on diagrams or programs of this kind.
Once you have the basics down of your chosen tool, it's time to start drawing out your models. Start off by understanding the different types of UML diagrams that exist such as class diagrams, sequence diagrams, activity diagrams and more—each one will allow you to communicate/model different aspects of your software/system design differently so decide which ones will serve you best for what purpose. Once you've decided on one or multiple diagram types to work with, dive in and begin making them with what your open source UML tool provides - create classes using shapes like rounded rectangles or nodes if needed; use arrows or plugs & sockets to show associations between elements; add notes or comments when necessary etcetera – things should become easier gradually as you move along due to repeated exposure.
Finally, review what has been created so far – make sure all relevant information exists in each element/diagram; take some time away from it then come back later to see if any changes need to be made; discuss it together (if possible) with other members who have experience in creating UML models etcetera before finally moving forward into implementation phase which involves going against the same process but at code level (if such is required). And there you go. You're now all set up and ready to go with creating awesome software designs through open source UML tools.