modeltotext

ModeltoText is a term used in software engineering and information systems to describe tools and libraries that convert formal models into textual descriptions. It encompasses both template-based approaches and natural language generation techniques, and it is applied across modeling languages such as UML, SysML, BPMN, ER diagrams, and various domain-specific languages. The goal is to produce readable documentation, concise summaries of model content, or human-friendly explanations of model behavior.

Typical capabilities include model parsing from exchange formats such as XMI, XML, or JSON, as well as the generation of structured text, natural language, or lightweight documentation. Toolchains may provide template engines, glossaries, and style guides to ensure consistent terminology and formatting. Many implementations support customization to reflect project standards, domain-specific vocabulary, and audience needs. Output formats often include plain text, Markdown, and integration-ready artifacts for documentation systems or wikis. Localization and multilingual generation are also supported in some variants.

Architecture and workflows usually involve a model parser or reader, a transformation or reasoning layer, and a text generation component. Some solutions rely on rule-based templates, while others employ statistical or neural natural language generation to adapt descriptions to context. Automation features, such as integration with model repositories, continuous integration pipelines, or event-based triggers on model changes, are common to facilitate up-to-date documentation.

Use of ModeltoText ranges from automated documentation generation and accessibility improvements to support for model reviews, compliance reporting, and knowledge transfer. As a class of tools, it refers to approaches rather than a single standardized product.