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android-clean-architecture

Android 및 Kotlin Multiplatform 프로젝트를 위한 클린 아키텍처 패턴 — 모듈 구조, 의존성 규칙, UseCase, Repository 및 데이터 계층 패턴. Android 또는 KMP 프로젝트에서 모듈, 계층 또는 데이터 흐름을 구조화할 때 사용합니다.

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이 스킬은 Android 및 Kotlin Multiplatform 프로젝트에서 Clean Architecture를 적용하기 위한 포괄적인 가이드를 제공합니다. 모듈 경계, 의존성 역전(Dependency Inversion), UseCase/Repository 패턴, 그리고 Room, SQLDelight, Ktor를 활용한 데이터 계층 설계를 다룹니다. 개발자는 이 스킬을 통해 `domain` 계층이 순수 Kotlin으로 유지되도록 하면서 데이터 흐름을 명확하게 분리하고, UseCase 기반의 비즈니스 로직, Repository 구현, 매퍼 패턴, 의존성 주입(Koin/Hilt), 오류 처리 및 Gradle 컨벤션 플러그인 설정까지 모범 사례를 얻을 수 있습니다. KMP와 Android 플랫폼 모두를 지원하며, 안티패턴을 피하는 방법도 함께 제시합니다.

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문서

Android Clean Architecture

Android 및 KMP 프로젝트를 위한 Clean Architecture 패턴입니다. 모듈 경계, 의존성 역전, UseCase/Repository 패턴, Room, SQLDelight, Ktor를 활용한 데이터 계층 설계를 다룹니다.

활성화 시점

  • Android 또는 KMP 프로젝트 모듈 구조화
  • UseCase, Repository 또는 DataSource 구현
  • 계층 간 데이터 흐름 설계 (domain, data, presentation)
  • Koin 또는 Hilt를 사용한 의존성 주입 설정
  • 계층형 아키텍처에서 Room, SQLDelight 또는 Ktor 작업

모듈 구조

권장 레이아웃

project/
├── app/                  # Android 진입점, DI 연결, Application 클래스
├── core/                 # 공통 유틸리티, 기본 클래스, 오류 타입
├── domain/               # UseCase, 도메인 모델, Repository 인터페이스 (순수 Kotlin)
├── data/                 # Repository 구현, DataSource, DB, 네트워크
├── presentation/         # 화면, ViewModel, UI 모델, 네비게이션
├── design-system/        # 재사용 가능한 Compose 컴포넌트, 테마, 타이포그래피
└── feature/              # 기능 모듈 (선택 사항, 대규모 프로젝트용)
    ├── auth/
    ├── settings/
    └── profile/

의존성 규칙

app → presentation, domain, data, core
presentation → domain, design-system, core
data → domain, core
domain → core (또는 의존성 없음)
core → (의존성 없음)

중요: domain은 절대 data, presentation 또는 어떤 프레임워크에도 의존해서는 안 됩니다. 순수 Kotlin만 포함합니다.

도메인 계층

UseCase 패턴

각 UseCase는 하나의 비즈니스 작업을 나타냅니다. 깔끔한 호출을 위해 operator fun invoke를 사용하세요:

class GetItemsByCategoryUseCase(
    private val repository: ItemRepository
) {
    suspend operator fun invoke(category: String): Result<List<Item>> {
        return repository.getItemsByCategory(category)
    }
}

// 리액티브 스트림을 위한 Flow 기반 UseCase
class ObserveUserProgressUseCase(
    private val repository: UserRepository
) {
    operator fun invoke(userId: String): Flow<UserProgress> {
        return repository.observeProgress(userId)
    }
}

도메인 모델

도메인 모델은 일반 Kotlin 데이터 클래스입니다 — 프레임워크 애노테이션이 없습니다:

data class Item(
    val id: String,
    val title: String,
    val description: String,
    val tags: List<String>,
    val status: Status,
    val category: String
)

enum class Status { DRAFT, ACTIVE, ARCHIVED }

Repository 인터페이스

도메인에 정의되고 데이터에서 구현됩니다:

interface ItemRepository {
    suspend fun getItemsByCategory(category: String): Result<List<Item>>
    suspend fun saveItem(item: Item): Result<Unit>
    fun observeItems(): Flow<List<Item>>
}

데이터 계층

Repository 구현

로컬 및 원격 데이터 소스를 조정합니다:

class ItemRepositoryImpl(
    private val localDataSource: ItemLocalDataSource,
    private val remoteDataSource: ItemRemoteDataSource
) : ItemRepository {

    override suspend fun getItemsByCategory(category: String): Result<List<Item>> {
        return runCatching {
            val remote = remoteDataSource.fetchItems(category)
            localDataSource.insertItems(remote.map { it.toEntity() })
            localDataSource.getItemsByCategory(category).map { it.toDomain() }
        }
    }

    override suspend fun saveItem(item: Item): Result<Unit> {
        return runCatching {
            localDataSource.insertItems(listOf(item.toEntity()))
        }
    }

    override fun observeItems(): Flow<List<Item>> {
        return localDataSource.observeAll().map { entities ->
            entities.map { it.toDomain() }
        }
    }
}

매퍼 패턴

매퍼는 데이터 모델 근처에 확장 함수로 유지하세요:

// data 계층
fun ItemEntity.toDomain() = Item(
    id = id,
    title = title,
    description = description,
    tags = tags.split("|"),
    status = Status.valueOf(status),
    category = category
)

fun ItemDto.toEntity() = ItemEntity(
    id = id,
    title = title,
    description = description,
    tags = tags.joinToString("|"),
    status = status,
    category = category
)

Room 데이터베이스 (Android)

@Entity(tableName = "items")
data class ItemEntity(
    @PrimaryKey val id: String,
    val title: String,
    val description: String,
    val tags: String,
    val status: String,
    val category: String
)

@Dao
interface ItemDao {
    @Query("SELECT * FROM items WHERE category = :category")
    suspend fun getByCategory(category: String): List<ItemEntity>

    @Upsert
    suspend fun upsert(items: List<ItemEntity>)

    @Query("SELECT * FROM items")
    fun observeAll(): Flow<List<ItemEntity>>
}

SQLDelight (KMP)

-- Item.sq
CREATE TABLE ItemEntity (
    id TEXT NOT NULL PRIMARY KEY,
    title TEXT NOT NULL,
    description TEXT NOT NULL,
    tags TEXT NOT NULL,
    status TEXT NOT NULL,
    category TEXT NOT NULL
);

getByCategory:
SELECT * FROM ItemEntity WHERE category = ?;

upsert:
INSERT OR REPLACE INTO ItemEntity (id, title, description, tags, status, category)
VALUES (?, ?, ?, ?, ?, ?);

observeAll:
SELECT * FROM ItemEntity;

Ktor 네트워크 클라이언트 (KMP)

class ItemRemoteDataSource(private val client: HttpClient) {

    suspend fun fetchItems(category: String): List<ItemDto> {
        return client.get("api/items") {
            parameter("category", category)
        }.body()
    }
}

// 콘텐츠 협상을 포함한 HttpClient 설정
val httpClient = HttpClient {
    install(ContentNegotiation) { json(Json { ignoreUnknownKeys = true }) }
    install(Logging) { level = LogLevel.HEADERS }
    defaultRequest { url("https://api.example.com/") }
}

의존성 주입

Koin (KMP 호환)

// Domain 모듈
val domainModule = module {
    factory { GetItemsByCategoryUseCase(get()) }
    factory { ObserveUserProgressUseCase(get()) }
}

// Data 모듈
val dataModule = module {
    single<ItemRepository> { ItemRepositoryImpl(get(), get()) }
    single { ItemLocalDataSource(get()) }
    single { ItemRemoteDataSource(get()) }
}

// Presentation 모듈
val presentationModule = module {
    viewModelOf(::ItemListViewModel)
    viewModelOf(::DashboardViewModel)
}

Hilt (Android 전용)

@Module
@InstallIn(SingletonComponent::class)
abstract class RepositoryModule {
    @Binds
    abstract fun bindItemRepository(impl: ItemRepositoryImpl): ItemRepository
}

@HiltViewModel
class ItemListViewModel @Inject constructor(
    private val getItems: GetItemsByCategoryUseCase
) : ViewModel()

오류 처리

Result/Try 패턴

오류 전파를 위해 Result<T> 또는 사용자 정의 sealed 타입을 사용하세요:

sealed interface Try<out T> {
    data class Success<T>(val value: T) : Try<T>
    data class Failure(val error: AppError) : Try<Nothing>
}

sealed interface AppError {
    data class Network(val message: String) : AppError
    data class Database(val message: String) : AppError
    data object Unauthorized : AppError
}

// ViewModel에서 — UI 상태로 매핑
viewModelScope.launch {
    when (val result = getItems(category)) {
        is Try.Success -> _state.update { it.copy(items = result.value, isLoading = false) }
        is Try.Failure -> _state.update { it.copy(error = result.error.toMessage(), isLoading = false) }
    }
}

컨벤션 플러그인 (Gradle)

KMP 프로젝트의 경우 컨벤션 플러그인을 사용하여 빌드 파일 중복을 줄이세요:

// build-logic/src/main/kotlin/kmp-library.gradle.kts
plugins {
    id("org.jetbrains.kotlin.multiplatform")
}

kotlin {
    androidTarget()
    iosX64(); iosArm64(); iosSimulatorArm64()
    sourceSets {
        commonMain.dependencies { /* 공통 의존성 */ }
        commonTest.dependencies { implementation(kotlin("test")) }
    }
}

모듈에 적용:

// domain/build.gradle.kts
plugins { id("kmp-library") }

피해야 할 안티패턴

  • domain에 Android 프레임워크 클래스 임포트 — 순수 Kotlin 유지
  • 데이터베이스 엔티티 또는 DTO를 UI 계층에 노출 — 항상 도메인 모델로 매핑
  • ViewModel에 비즈니스 로직 배치 — UseCase로 추출
  • GlobalScope 또는 구조화되지 않은 코루틴 사용 — viewModelScope 또는 구조화된 동시성 사용
  • 비대한 Repository 구현 — 집중된 DataSource로 분할
  • 순환 모듈 의존성 — A가 B에 의존하면 B는 A에 의존해서는 안 됨

참고 자료

UI 패턴은 compose-multiplatform-patterns 스킬을 참조하세요. 비동기 패턴은 kotlin-coroutines-flows 스킬을 참조하세요.

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/claude-api

Anthropic Claude API patterns for Python and TypeScript. Covers Messages API, streaming, tool use, vision, extended thinking, batches, prompt caching, and Claude Agent SDK. Use when building applications with the Claude API or Anthropic SDKs.

affaan-m/everything-claude-code

End-to-end marketing campaign planning and execution. Covers audience research, positioning, campaign angle definition, landing page copy, email sequences, social posts, ad copy, short-form video scripts, and content calendars. Use as the orchestration layer for multi-channel product launches. Use when planning or executing a multi-channel product launch, or producing landing page, email, social, or ad copy.

affaan-m/everything-claude-code

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/everything-claude-code-conventions

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/frontend-design

Create distinctive, production-grade frontend interfaces with high design quality. Use when the user asks to build web components, pages, or applications and the visual direction matters as much as the code quality.

affaan-m/gget

gget CLI and Python workflow for quick genomic database queries, sequence lookup, BLAST-style searches, enrichment checks, and reproducible bioinformatics evidence logs.

affaan-m/literature-review

Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.

affaan-m/motion-ui

Production-ready UI motion system for React/Next.js. Use when implementing animations, transitions, or motion patterns.

affaan-m/project-guidelines-example

Example project-specific skill template based on a real production application.

affaan-m/pubmed-database

Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring.

affaan-m/scholar-evaluation

Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.

affaan-m/uspto-database

USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

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