Bounded contexts keep large models usable
Bounded contexts are collections of one or more subdomains, worked on by a single team and unified by a common language. It’s best practice to start out with large contexts and divide as needed. Its size is a function of the model it encompasses, rather than a goal itself. They should not be junk drawers nor jacks of all trades.
A content model with many objects requires an unsustainable level of coordination and can cause cascading changes. Instead, divide a large model into bounded contexts and define collaboration patterns between them.
This is a new idea for IA, where we tend to treat an entire experience as a single context.
References
Khononov, Vladik. Learning Domain-Driven Design . 1st edition, O’Reilly Media, Inc., 2021.
The idea of bounded contexts come from the idea of semantic domains. A port is one thing in hardware and another in shipping. In the context of botany, a tomato is a fruit. In the context of cooking, a tomato is a vegetable. In the context of U.S. tax law, a tomato is a vegetable. In the context of theatrical performances, a tomato is a feedback mechanism. p. 41
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