clean-architecture

Clean Architecture Framework

A disciplined approach to structuring software so that business rules remain independent of frameworks, databases, and delivery mechanisms. Apply these principles when designing system architecture, reviewing module boundaries, or advising on dependency management.

Core Principle

Source code dependencies must point inward — toward higher-level policies. Nothing in an inner circle can know anything about an outer circle. This single rule produces systems that are testable and independent of frameworks, UI, database, and any external agency. Business rules are what matter; databases, web frameworks, and delivery mechanisms are details — when details depend on policies, you can defer decisions, swap implementations, and test business logic in isolation.

Scoring

Goal: 10/10. Score one point for each of the seven Quick Diagnostic rows the architecture satisfies (0-7), then map to a 0-10 band: 6-7 satisfied = 9-10 (Dependency Rule holds, business logic is framework- and DB-independent); 4-5 = 6-8 (core is testable but some details leak inward); 2-3 = 3-5 (framework or persistence dictates structure); 0-1 = 0-2 (no boundaries — business rules live in controllers and ORM models). Report the score, the failed diagnostic rows, and the specific inversion needed to fix each.

1. Dependency Rule and Concentric Circles

Core concept: Organize the architecture as concentric circles — Entities (enterprise business rules) innermost, then Use Cases (application business rules), then Interface Adapters, with Frameworks and Drivers outermost. Source code dependencies always point inward.

Why it works: When high-level policies don't depend on low-level details, you can swap the database, web framework, or API style without touching business logic — the system becomes resilient to the most volatile parts of the stack.

Key insights:

Inner circles cannot mention outer circle names — no classes, functions, variables, or data formats from outside
Data crossing a boundary must be in the form most convenient for the inner circle, never dictated by the outer
Dependency Inversion (interfaces defined inward, implemented outward) is the mechanism that enforces the rule
The number of circles is not fixed — four is typical; the rule stays the same
Frameworks are details, not architecture — they belong in the outermost circle

Code applications:

Context	Pattern	Example
Layer direction	Inner circles define interfaces; outer implement	`UserRepository` interface in Use Cases; `PostgresUserRepository` in Adapters
Data crossing	DTOs cross boundaries, not ORM entities	Use Case returns `UserResponse` DTO, not an ActiveRecord model
Dependency direction	Import arrows always point inward	Controller imports Use Case; Use Case never imports Controller

See references/dependency-rule.md when an inner-circle import points outward and you need the four-circle code walkthrough, the data-crossing rules, and the four-step dependency-inversion procedure to fix it.

2. Entities and Use Cases

Core concept: Entities encapsulate enterprise-wide business rules — rules that would exist even without software. Use Cases contain application-specific rules that orchestrate the flow of data to and from Entities.

Why it works: Separating what the business does (Entities) from how the application orchestrates it (Use Cases) lets you reuse Entities across applications and change application behavior without altering core business rules.

Key insights:

Entities are not database rows — they are objects or pure functions encapsulating critical business rules
Use Cases accept Request Models and return Response Models — never framework objects
Each Use Case is a single application operation (CreateOrder, ApproveExpense)
The Interactor pattern: a Use Case class implements an input boundary interface and calls an output boundary interface
Changes to a Use Case should never affect an Entity; Entity changes may ripple to Use Cases

Code applications:

Context	Pattern	Example
Entity design	Critical business rules, zero framework dependencies	`Order.calculateTotal()` applies tax rules; knows nothing about HTTP
Request/Response	Simple data structures cross the boundary	`CreateOrderRequest { items, customerId }` — no ORM models
Single responsibility	One Use Case per operation	`PlaceOrder`, `CancelOrder`, `RefundOrder` as separate classes
Interactor	Implements Input Port, calls Output Port	`PlaceOrderInteractor implements PlaceOrderInput`

See references/entities-use-cases.md when designing an Interactor or deciding what belongs in an Entity versus a Use Case — full Enterprise vs. Application Business Rules treatment with request/response model examples.

3. Interface Adapters and Frameworks

Core concept: Interface Adapters convert data between the form convenient for Use Cases/Entities and the form required by external agencies. Frameworks and Drivers are the outermost layer — glue code to the outside world.

Why it works: When the web framework, ORM, or message queue is confined to the outer circles, replacing any of them is a localized change. The database is a detail; the web is a detail; details should be plugins to your business rules, not the skeleton of the application.

Key insights:

Controllers translate HTTP into Use Case input; Presenters translate Use Case output into view models
Gateways implement repository interfaces defined by Use Cases — the inner circle defines the contract, the outer fulfills it
Business rules never know whether data lives in SQL, NoSQL, or flat files, or that delivery is HTTP
Treat frameworks with suspicion — they want you to couple to them; keep them at arm's length

Code applications:

Context	Pattern	Example
Controller	Delivery mechanism → Use Case input	`OrderController.create(req)` builds `CreateOrderRequest`, calls Interactor
Presenter	Use Case output → view model	`OrderPresenter.present(response)` formats for JSON/HTML
Gateway	Repository interface implemented per DB	`SqlOrderRepository implements OrderRepository`
Framework boundary	Framework calls inward, never the reverse	Express route handler calls Controller; Controller never imports Express

See references/adapters-frameworks.md when wiring controllers, presenters, or gateways, or arguing that the database/web is a detail — covers plugin architecture and how to confine a framework to the edges.

4. Component Principles

Core concept: Components are the units of deployment. Three cohesion principles govern what goes inside a component; three coupling principles govern relationships between components.

Why it works: Poorly composed components create ripple effects where one change forces redeployment of unrelated code; the principles keep changes localized and releases independent.

Key insights:

REP (Reuse/Release Equivalence): classes in a component must be versionable and releasable as a unit
CCP (Common Closure): classes that change for the same reason at the same time belong together — SRP for components
CRP (Common Reuse): don't force users to depend on classes they don't use
ADP (Acyclic Dependencies): the component graph must have no cycles — break them with DIP or a new component
SDP (Stable Dependencies): depend in the direction of stability
SAP (Stable Abstractions): stable components should be abstract; unstable ones concrete

Code applications:

Context	Pattern	Example
Component grouping	Group classes that change together (CCP)	All order-related Use Cases in one component
Breaking cycles	Apply DIP to invert a dependency edge	Extract an interface into a new component to break the cycle
Stability metrics	Instability I = Ce / (Ca + Ce)	Many incoming, no outgoing deps → I near 0 (stable)

See references/component-principles.md when grouping classes into deployable components or breaking a dependency cycle — each of REP, CCP, CRP, ADP, SDP, SAP worked through with the instability metric.

5. SOLID Principles

Core concept: Five class-and-module-level principles — Single Responsibility, Open-Closed, Liskov Substitution, Interface Segregation, Dependency Inversion — the mid-level building blocks that make the Dependency Rule possible.

Why it works: Each principle addresses a specific way dependencies go wrong, preventing the rigidity, fragility, and immobility that turn codebases into legacy nightmares.

Key insights:

SRP: a module has one reason to change — it serves one actor (not "does one thing")
OCP: extend behavior by adding new code, not modifying existing code — strategy and plugin patterns
LSP: subtypes must be usable through the base interface without the client knowing — violated by unexpected exceptions or ignored methods
ISP: clients should not depend on methods they don't use — fat interfaces create needless coupling
DIP: high-level modules and low-level modules both depend on abstractions defined by the high-level module

Code applications:

Context	Pattern	Example
SRP violation	Class serves multiple actors	`Employee` handles pay (CFO), reporting (COO), persistence (CTO)
OCP via strategy	New behavior through new classes	Add `ExpressShipping` implementing `ShippingStrategy`; `Order` untouched
LSP violation	Subtype changes expected behavior	`Square extends Rectangle` breaks the `setWidth()`/`setHeight()` contract
ISP application	Split fat interfaces into role interfaces	`Printer`, `Scanner`, `Fax` instead of one `MultiFunctionDevice`
DIP wiring	High-level defines interface; low-level implements	`OrderService` depends on `PaymentGateway`, not `StripeClient`

See references/solid-principles.md when applying SRP/OCP/LSP/ISP/DIP to a specific class or diagnosing a violation — each principle worked through with code examples and the smell it prevents.

6. Boundaries and Boundary Anatomy

Core concept: A boundary is a line between things that matter and things that are details, implemented through polymorphism: dependencies cross pointing inward while control flow may cross either way.

Why it works: Every boundary buys the option to defer a decision or swap an implementation; strategic boundary placement determines whether a system is a joy or a pain to maintain over years.

Key insights:

Full boundaries use reciprocal interfaces on both sides; partial boundaries use a simpler strategy or facade
Humble Object pattern: split boundary code into a hard-to-test part (close to the boundary) and an easy-to-test part (the logic)
Services are not automatically architectural boundaries — a microservice with a fat shared data model is a monolith with network calls
Tests are the most isolated component: they depend inward, nothing depends on them
Premature boundaries are expensive, but so are missing ones — draw them at points of likely volatility

Code applications:

Context	Pattern	Example
Full vs. partial boundary	Reciprocal ports, or a lone strategy	Use Case defines `PlaceOrderInput`/`PlaceOrderOutput`; simpler cases take a `ShippingStrategy`
Humble Object	Separate testable logic from infrastructure	`PresenterLogic` (testable) produces `ViewModel`; `View` (humble) renders it
Main as plugin	Composition root assembles the system	`main()` wires all concrete implementations and starts the app

See references/boundaries.md when deciding where to draw a boundary, choosing full vs. partial, or applying the Humble Object pattern — also covers services as boundaries, test boundaries, and Main as the ultimate plugin.

Common Mistakes

Mistake	Why It Fails	Fix
ORM leaking into business logic	Entities couple to the schema; DB changes rewrite business rules	Separate domain entities from persistence models; map at the adapter layer
Business rules in controllers	Untestable without HTTP; duplicated across endpoints	Move logic into Use Case Interactors; controllers only translate and delegate
Framework-first architecture	Framework dictates structure; swapping means a rewrite	Treat the framework as a plugin; structure code by business capability
Circular component dependencies	Changes ripple unpredictably; no independent releases	Apply DIP or extract a shared abstraction component
One giant Use Case per feature	Bloated thousand-line orchestrators	Split into focused single-operation Use Cases
Skipping boundaries "because it's simple"	Coupling accumulates silently until the cost is enormous	Draw boundaries proactively at points of likely volatility
Microservices as automatic good architecture	A distributed monolith is worse than a clean monolith	Apply the Dependency Rule within and across services; services are deployment boundaries, not architectural ones

Quick Diagnostic

Question	If No	Action
Can you test business rules without DB, web server, or framework?	Rules coupled to infrastructure	Extract entities and use cases behind interfaces; mock outer layers
Do all source dependencies point inward?	Dependency Rule violated	Introduce boundary interfaces; invert the offending dependency
Can you swap the database without touching business logic?	Persistence leaking inward	Repository pattern; isolate persistence in adapters
Are Use Cases independent of delivery mechanism?	Use Cases know HTTP/CLI/queues	Use plain DTOs in Use Case signatures
Is the framework confined to the outermost circle?	Framework is your architecture	Wrap framework calls behind interfaces; push to the edges
Is the component graph cycle-free?	Circular dependencies exist	Apply ADP: DIP or new components to break every cycle
Does Main (composition root) wire all dependencies?	Concrete classes instantiated in inner circles	Move construction to Main; use DI or factories

About the Author

Robert C. Martin ("Uncle Bob") is a software engineer programming since 1970, a founding signatory of the Agile Manifesto, and the author of Clean Code, The Clean Coder, Clean Architecture, and Clean Agile. His SOLID principles are foundational vocabulary in object-oriented design, and his work argues that architecture is about managing dependencies and keeping business rules independent of infrastructure details.