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Data-oriented programming

Data-oriented programming is an approach to structuring software around data representations, access patterns, and operations suited to the data's characteristics and intended use.

How 2 Manning books explain it

Data-Oriented Programming: Reduce software complexity

A programming paradigm that organizes software around data and seeks to reduce system complexity by separating data from code and avoiding unnecessary mutation and encapsulation.

How it is used
Reduces system complexity and adapts behavior to changing requirements by separating data entities from stateless code modules.
How deep it goes
Works through architecture, data representation, permissions, database access, immutability, testing, and reproducible debugging.
Examples
Uses library permissions, map-based book records, relational database collections, and reproducible catalog-search debugging.
What you can do after
Apply it by designing stateless modules, generic records, explicit data flow, and reproducible data-driven debugging experiments.

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The Art of Code

A programming paradigm that models data as simple immutable structures and expresses behavior through standalone functions operating on that data.

How it is used
Centers design on explicit data so code communicates the problem and its intent clearly.
How deep it goes
Defines full data-oriented programming, then develops practical modeling principles rather than requiring a pure paradigm shift.
Examples
Contrasts an ambiguous User constructor with a PhysicalProfile using explicit weight and height types.
What you can do after
Evaluate/understand when explicit data carriers, local invariants, immutability, and flatter models improve clarity.

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Related concepts

These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.