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AccuRev is a centralized version control system which uses a client–server model. Communication is performed via TCP/IP using a proprietary protocol. Servers function as team servers, continuous integration servers, or build servers. AccuRev is built around a stream-based architecture in which streams form a hierarchical structure of code ...
Version control is a component of software configuration management. [1] A version control system is a software tool that automates version control. Alternatively, version control is embedded as a feature of some systems such as word processors, spreadsheets, collaborative web docs, [2] and content management systems, e.g., Wikipedia's page ...
In the world of open source software, the Concurrent Version System (CVS) has long been the tool of choice for version control. And rightly so. CVS itself is free software, and its non-restrictive modus operandi and support for networked operation—which allow dozens of geographically dispersed programmers to share their work—fits the ...
The following table contains relatively general attributes of version-control software systems, including: Repository model, the relationship between copies of the source code repository. Client–server, users access a master repository via a client; typically, their local machines hold only a working copy of a project tree. Changes in one ...
Darcs is a distributed version control system created by David Roundy.Key features include the ability to choose which changes to accept from other repositories, interaction with either other local (on-disk) repositories or remote repositories via SSH, HTTP, or email, and an unusually interactive interface.
The Librarian [proprietary, shared] – Around since 1969, source control for IBM mainframe computers; from Applied Data Research, later acquired by Computer Associates; Vault [proprietary, client-server] – version control tool by SourceGear; first installation can be used for free
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DVC is a free and open-source, platform-agnostic version system for data, machine learning models, and experiments. [1] It is designed to make ML models shareable, experiments reproducible, [2] and to track versions of models, data, and pipelines. [3] [4] [5] DVC works on top of Git repositories [6] and cloud storage. [7]