# Dependency injection Dependency injection is a software design pattern that injects objects into a class instead of having the class create them itself. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## A Multi-Module Android Template with Kotlin Convention Plugins, Lint Rules, and Design System Tokens DevFeed: [A Multi-Module Android Template with Kotlin Convention Plugins, Lint Rules, and Design System Tokens]() Original publisher: [Read original article]() Author: Shamil Gulmetov Published: 2026-09-09T01:34:18Z Content type: tutorial Language: en Sources: [ProAndroidDev - Medium]() Topics: [Template](), [Android](), [Architecture & Design](), [Kotlin](), [Gradle](), [Jetpack Compose](), [Dependency injection](), [Automation](), [Refactoring](), [now-in-android]() Tags: [android](), [android-app-development](), [android-architecture](), [android-studio](), [architecture](), [automation](), [best-practices](), [build](), [compose](), [dependency-injection](), [gradle](), [how-to](), [jetpack-compose](), [kotlin](), [now-in-android](), [refactoring]() ### AI overview This tutorial presents an Android Architecture Template based on patterns from Google's Now in Android repository. It describes a multi-module structure with Gradle Version Catalogs, Kotlin Convention Plugins, Jetpack Compose design tokens and dark-theme support, dependency injection, custom Lint rules, and a terminal-based renaming tool. ### Source excerpt How to streamline your development workflow with pre-configured Kotlin Convention Plugins, custom Lint rules, and unified design system tokens. Creating a new Android application from scratch in modern engineering is rarely as simple as clicking File -> New -> New Project in Android Studio. Before writing a single line of business logic, developers face hours -- or even days -- of repetitive infrastructure setup: Configuring a scalable multi-module architecture. Setting up Gradle Version Catalogs and writing custom Kotlin Convention Plugins to eliminate build script duplication. Standardizing design tokens and dark theme support in Jetpack Compose. Wiring up Hilt Dependency Injection for Coroutine Dispatchers, network, and Application Scopes. Enforcing architectural boundaries and team coding standards using custom static analysis (Lint) rules. Google's official Now in Android (NiA) repository is the recognized gold standard for modern Android engineering. However, because NiA is a full-featured showcase app with domain logic (news feeds, authors, bookmarks, offline sync), using it as a starter kit is cumbersome: developers must strip out existing features while risking breaking build pipelines. This Android Architecture Template bridges that gap: a clean, production-ready starter kit that extracts NiA's best architectural patterns into an isolated foundation. To make it enterprise-ready with zero room for error, it includes a standalone automation tool. Instead of manual refactoring, run a single terminal command to rename and brand the entire architecture in seconds. Acknowledgments & Credits Core architectural decisions, build-logic convention plugins, and static analysis infrastructure in this template are directly inspired by Google's official Now in Android (NiA) repository. Rather than reinventing the wheel, this template focuses on developer ergonomics--making Google's best practices instantly usable out of the box. 1. Modular Project Architecture The repository ## AI Made Code Generation Cheaper, but Developer Judgment Still Depends on Context DevFeed: [AI Made Code Generation Cheaper, but Developer Judgment Still Depends on Context]() Original publisher: [Read original article]() Author: Paweł Ostromecki Published: 2026-08-24T15:52:12Z Content type: opinion Language: en Sources: [Daniel Glejzner]() Topics: [Code](), [Artificial Intelligence](), [Angular](), [Maintainers](), [Dependency injection](), [Testing]() Tags: [agent](), [ai](), [angular](), [code](), [dependency-injection](), [developer](), [maintainers](), [testing]() ### AI overview This opinion article argues that AI has made code generation, syntax recall, and familiar implementations less scarce, but has not eliminated the value of developer knowledge. The author emphasizes that evaluating solutions for a real system still depends on product, codebase, team, failure costs, and future changes. It also notes that productivity findings vary by AI tool, developer experience, and task, citing differing METR results. ### Source excerpt When implementation becomes abundant, selection becomes the work. For roughly eight years, I had a simple model of becoming a better developer. Read the documentation. Learn Angular properly. Understand RxJS, dependency injection, change detection, testing, state management, architecture. Look at how other people solve problems. Make enough mistakes to understand ## Add the dependency graph to a Kotlin K2 migration checklist DevFeed: [Add the dependency graph to a Kotlin K2 migration checklist]() Original publisher: [Read original article]() Published: 2026-08-18T00:00:00Z Content type: tutorial Language: en Sources: [Koin - Cloud-Inject.io -Kotzilla]() Topics: [Kotlin](), [migration](), [Dependency injection](), [Graphs](), [Compiler](), [toolchain](), [Android Gradle Plugin](), [Compose]() Tags: [android-gradle-plugin](), [compiler](), [compose](), [dependency-injection](), [graph](), [kotlin](), [migration](), [rollback](), [toolchain](), [verification]() ### AI overview A practical checklist for Kotlin K2 migrations in projects that generate or validate dependency wiring. It recommends mapping the compiler and build toolchain, upgrading from a known compatibility matrix, cleaning and inspecting generated output, verifying dependency graphs across flavors and targets, testing runtime slices, and keeping rollback changes coherent. ### Source excerpt A K2 migration is usually planned around source compatibility and compiler diagnostics. Projects that generate or validate dependency wiring need another checklist: compiler plugin versions, generated sources, metadata compatibility, and graph verification on every target. Map the toolchain first Record the Kotlin plugin, Compose compiler plugin, KSP or annotation tooling, dependency-injection compiler plugin, Android Gradle plugin, and target libraries. Upgrade from a known matrix instead of selecting each latest version independently. ## Build a dependency-graph inventory before changing the container DevFeed: [Build a dependency-graph inventory before changing the container]() Original publisher: [Read original article]() Published: 2026-08-18T00:00:00Z Content type: tutorial Language: en Sources: [Koin - Cloud-Inject.io -Kotzilla]() Topics: [Dependency injection](), [Android](), [test](), [Gradle]() Tags: [android](), [build](), [configuration](), [dependency](), [graph](), [process](), [test]() ### AI overview This tutorial recommends creating a framework-independent dependency-graph inventory before migrating dependency injection. It explains how to document entry points, ownership, implementations, lifetimes, qualifiers, modules, replacement values for tests, and architectural constraints, then validate the design through smaller executable test slices. ### Source excerpt A dependency-injection migration often starts with framework syntax. That is too late. First describe the graph without using the framework's vocabulary. The inventory should show which objects exist, who owns them, and which runtime fact selects one implementation over another. Start from entry points List application entry points: the Android application, a worker, a navigation destination, a command-line process, and each test fixture. Trace the objects requested at each entry point. Stop the trace at explicit boundaries such as a database driver, HTTP transport, clock, file system, or platform service. ## Review a Koin upgrade as a graph change, not a version bump DevFeed: [Review a Koin upgrade as a graph change, not a version bump]() Original publisher: [Read original article]() Published: 2026-08-18T00:00:00Z Content type: tutorial Language: en Sources: [Koin - Cloud-Inject.io -Kotzilla]() Topics: [Dependency injection](), [upgrade](), [modules](), [test](), [Compose]() Tags: [android](), [compose](), [dependency-injection](), [modules](), [test](), [upgrade]() ### AI overview This tutorial explains how to review a Koin dependency-injection upgrade as an architecture change rather than a simple version bump. It recommends recording the existing dependency graph, modules, warnings, startup results, and verification output; upgrading mechanisms separately; checking all startup variants; and maintaining tested rollback procedures. ### Source excerpt Dependency-injection upgrades can change more than API names. Verification behavior, annotation processing, Compose packages, compiler integration, and deprecations can all alter how the graph is built. Treat the upgrade as an architecture change with a defined before-and-after record. Freeze the current graph Before changing versions, save the dependency lock or resolved graph, the list of DI modules, startup smoke-test results, and verification-test output. Record warnings that already exist so a new warning is not confused with old noise. ## Find technical debt at dependency-injection boundaries DevFeed: [Find technical debt at dependency-injection boundaries]() Original publisher: [Read original article]() Published: 2026-08-18T00:00:00Z Content type: article Language: en Sources: [Koin - Cloud-Inject.io -Kotzilla]() Topics: [Dependency injection](), [Framework](), [Code]() Tags: [architecture](), [defects](), [dependency-injection](), [errors](), [review](), [structure](), [technical](), [test](), [tests]() ### AI overview This article explains how dependency-injection code can expose architectural debt. It identifies signals such as oversized modules, string qualifiers, lifetime inversion, construction that starts work, broad production-container tests, and definitions spread across UI locations. It recommends paying down debt at product-slice boundaries, separating construction from behavior, adding focused graph and behavior tests, and measuring ownership, verification, startup, and test setup. ### Source excerpt Dependency-injection code is often treated as plumbing. It is also a compact map of architecture decisions. Review it for debt signals before adding another binding. Signals worth investigating An oversized application module usually means feature boundaries are not explicit. String qualifiers can hide a missing type. Definitions that open databases or start jobs during graph creation mix construction with behavior. A process-scoped object that accepts a screen-owned dependency indicates lifetime inversion. ## Make scalable routing system for your Flutter Apps DevFeed: [Make scalable routing system for your Flutter Apps]() Original publisher: [Read original article]() Author: Kanan Yusubov Published: 2026-07-29T15:25:43Z Content type: tutorial Language: en Sources: [Flutter Community - Medium]() Topics: [Flutter](), [Routing (disambiguation)](), [navigation](), [modules](), [Dependency injection](), [Usability]() Tags: [clean-architecture](), [dependency-injection](), [flutter](), [go-router](), [modular-router](), [modules](), [navigation](), [router](), [routing](), [routing-system](), [usability]() ### AI overview This tutorial describes a scalable, decoupled routing system for Flutter apps. It explains a wrapper built on go_router that adds typed route arguments, native and path parameters, cross-module modularization, nested routes, presentation modes, and type-safe route guards. ### Source excerpt Recently, I've been working on migrating our app's routing system. We previously used auto_route, but eventually realized its tightly coupled nature made it incredibly difficult to scale across independent modules. Furthermore, its heavy reliance on code generation became a bottleneck for our workflow. To resolve this, we decided to architect a clean, scalable, and highly decoupled routing system. Our new solution is a powerful wrapper built on top of go_router. It abstracts away the raw string navigation and supercharges the router with custom features to maximize usability and type safety. In this blog post, I will walk you through the core benefits of this new routing system, covering the following key topics: Unified Routing Protocol (AppRouteInfo) Strictly Typed Route Arguments Native & Path Parameters Support Cross-Module Modularization (AppModuleRouter) Hierarchical Back stack & Sub-Routes (Nested Route Definitions, Decoupled Cross-Module Navigation) Dynamic Presentation Modes (e.g., Native, ModalSheet, NoTransition) Guard Interceptor Mechanism (Type-Safe Redirects, Global Interceptors) Note: This blog will show the general usage and problems it solved. For more detailed code, you can check the following link: https://github.com/thisisyusub/scalable-routing-system-demoArchitectural Structure of Routing System Here is how the demo application is structured to achieve a fully decoupled, scalable routing system: scalable_routing_system_demo (main app): The entry point of the application responsible for wiring up all services, dependency injection, and global route configurations. app_routes: Houses all route definitions, parameters, routing protocols, and models to ensure fully type-safe navigation. This is decoupled from the core routing package to separate app-specific business needs from generic routing mechanics. routing_system (core router): A generic, domain-agnostic router package that has zero knowledge of the app's specific routes. It exclusively provid ## Starlette vs FastAPI: what FastAPI actually adds DevFeed: [Starlette vs FastAPI: what FastAPI actually adds]() Original publisher: [Read original article]() Author: Farhan Hasin Chowdhury Published: 2026-07-20T07:00:00Z Content type: comparison Language: en Sources: [Honeybadger]() Topics: [FastAPI](), [Pydantic](), [ASGI](), [OpenAPI Specification](), [Dependency injection](), [Python](), [WebSocket](), [Cross-origin resource sharing (CORS)]() Tags: [cors](), [data-validation](), [dependency-injection](), [fastapi](), [frameworks](), [openapi](), [python](), [python-articles](), [starlette](), [websocket]() ### AI overview This comparison explains how FastAPI builds on Starlette and Pydantic. Starlette provides the ASGI-based HTTP layer, while Pydantic handles typed data validation; FastAPI adds type-driven parameter parsing, dependency injection, and automatic OpenAPI documentation. It also discusses when using raw Starlette may be preferable. ### Source excerpt FastAPI is built on Starlette, but most developers never look at what's underneath. Learn what FastAPI actually adds on top of Starlette and Pydantic, what comes straight from Starlette, and when dropping down to raw Starlette makes more sense than pulling in the full stack. ## Incremental Maintenance DevFeed: [Incremental Maintenance]() Original publisher: [Read original article]() Published: 2026-05-14T01:53:09Z Content type: opinion Language: en Sources: [Blogs on Ryan Harter]() Topics: [maintenance](), [Dependency injection](), [implementation](), [screen](), [App]() Tags: [core](), [dependencies](), [dependency-injection](), [incremental](), [maintenance](), [patterns](), [product](), [screen]() ### AI overview An opinion article about incremental maintenance in a large, aging application. It argues that small refactoring choices can reduce entrenched patterns, using dependency injection to keep feature-gating details out of a monolithic tab-host screen. ### Source excerpt I recently reviewed some code at work that made me pause. The change affected a part of the codebase that we affectionately call "The Monolith", which is some of the oldest code in our 16 year old app. While there are reasonable arguments that it's hard to tease apart this older hairball of code, there are often small choices that can either move you closer to the decoupled promised land, or further entrench you in bad patterns. ## Metro 1.0.0 Is Stable as a Kotlin Multiplatform Compile-Time Dependency Injection Framework DevFeed: [Metro 1.0.0 Is Stable as a Kotlin Multiplatform Compile-Time Dependency Injection Framework]() Original publisher: [Read original article]() Author: Zac Sweers Published: 2026-04-27T21:07:22Z Content type: release Language: en Sources: [Zac Sweers]() Topics: [Kotlin](), [Dependency injection](), [multiplatform](), [Compiler](), [Framework](), [gradle-plugin]() Tags: [build-performance](), [build-times](), [compilation](), [compiler](), [dependency-injection](), [experimental](), [gradle](), [gradle-plugin](), [incremental](), [kotlin](), [metro](), [multiplatform](), [open-source](), [perfetto](), [stable]() ### AI overview Metro 1.0.0 is now stable. The Kotlin multiplatform compile-time dependency injection framework uses a compiler plugin and provides API-stable runtime APIs, MetroX artifacts, and a Gradle plugin unless marked experimental. The article also describes build-performance improvements and compile-time validation features. ### Source excerpt New here? Metro is a multiplatform, compile-time dependency injection framework for Kotlin implemented as a compiler plugin. Metro 1.0.0 is out now and stable. This means that its runtime APIs (runtime, MetroX artifacts, Gradle plugin, etc.) are now API-stable unless annotated with an experimental annotation. This ## Unlocking Koin Compile Safety -- Koin Compiler Plugin 1.0.0-RC1 DevFeed: [Unlocking Koin Compile Safety -- Koin Compiler Plugin 1.0.0-RC1]() Original publisher: [Read original article]() Author: Arnaud Giuliani Published: 2026-04-14T08:08:36Z Content type: release Language: en Sources: [Koin developers - Medium]() Topics: [koin](), [Compiler](), [Dependency injection](), [Kotlin](), [Code generation]() Tags: [compilation](), [compiler](), [dependency](), [dependency-injection](), [generation](), [koin](), [kotlin](), [kotlin-multiplatform](), [plugin](), [release](), [safety]() ### AI overview Koin announces Compiler Plugin 1.0.0-RC1 for Kotlin and KMP. The release candidate validates dependency graphs during compilation and adds constructor auto-wiring across DSL and annotations. ### Source excerpt Koin Compiler Plugin 1.0.0-RC1 -- Unlocking Compile-Safe Dependency Injection for Kotlin & KMP Hello Koin Community 👋 Compile-time safety has been one of the most requested features by the community. For years, verifying your Koin dependency graph required runtime tools with checkModules()and verify()in your test suite. They run after compilation. If something is missing, you find out in test results, not at build time. It's now time for new generation of tools for Koin. My Linkedin post for AndroidMakers Last week at Android Makers (Paris, France), we announced Koin Compiler Plugin 1.0.0-RC1! This release candidate brings compile-time safety, constructor auto-wiring, and a unified developer experience for both DSL and Annotations, all powered by a native Kotlin Compiler Plugin. Aligned with Koin 4.2.1 and Kotlin 2.3.20. Check out the roadmap and documentation to get started. Dependency graph validation is done in the Koin Compiler Plugin itself: your graph is verified as part of the build (no need to run tests). DSL, annotations, and even individual call sites are checked. The Kotlin compiler plugin ecosystem has matured, and new DI approaches are emerging. Koin's answer is straightforward: lighter Compiler codegen, an existing runtime container, and validation by design of the compilation. Koin Compiler Plugin -- 1.0.0-RC1Check the online Koin documentation for further information: https://insert-koin.io/docs/intro/koin-compiler-plugin We are also gathering some "playground apps" to showcase different scenarios of Koin Compiler Usages (https://github.com/InsertKoinIO/playground-apps) Koin Compiler Plugin Setup 🔎 Below, you will find the minimum versions of Koin & Koin Compiler Plugin that are allowed to enable compile safety (note that you need Kotlin 2.3.20): [versions] kotlin = "2.3.20" koin = "4.2.1" koin-plugin = "1.0.0-RC1" [libraries] koin-core = { module = "io.insert-koin:koin-core", version.ref = "koin" } # if using annotations koin-annotations = { module = ## Dependency Injection and Dependency Inversion in Node.js and TypeScript DevFeed: [Dependency Injection and Dependency Inversion in Node.js and TypeScript]() Original publisher: [Read original article]() Author: Petar Ivanov Published: 2026-03-29T12:19:37Z Content type: tutorial Language: en Sources: [The T-Shaped Dev]() Topics: [Dependency injection](), [Node.js](), [Dependency Inversion](), [TypeScript](), [Express](), [PostgreSQL](), [Drizzle](), [SendGrid](), [Amazon Web Services]() Tags: [dependency-inversion](), [di](), [node-js](), [testing](), [typescript]() ### AI overview A tutorial on using plain TypeScript dependency injection in Node.js. It distinguishes dependency injection from dependency inversion and argues that explicit dependencies can improve testability and make implementations easier to swap. ### Source excerpt Learn the hidden costs about importing everything directly and the structural change you need to make. (8 min) ## Re: Dependency Injection vs. Service Locators DevFeed: [Re: Dependency Injection vs. Service Locators]() Original publisher: [Read original article]() Author: Zac Sweers Published: 2026-02-20T05:10:16Z Content type: opinion Language: en Sources: [Zac Sweers]() Topics: [Dependency injection](), [Dagger](), [koin](), [Kotlin](), [service](), [multiplatform]() Tags: [dagger](), [dependency-injection](), [koin](), [kotlin](), [metro](), [service]() ### AI overview The article compares dependency injection frameworks with service locators, focusing on compile-time validation, testing, isolation, generated performance, and the tradeoff of requiring more explicit code. It discusses Metro, Dagger, Hilt, Anvil, kotlin-inject, Koin, and manual dependency injection. ### Source excerpt This is a port of a write-up I did in the Kotlin Lang slack here in response to the question "Dagger vs. Hilt vs. Koin vs. Metro vs. . Serious question: Are there any compelling reasons to switch from Koin to Metro in a ## From Dagger to Metro DevFeed: [From Dagger to Metro]() Original publisher: [Read original article]() Author: Andrius Semionovas Published: 2026-02-12T00:00:00Z Content type: article Language: en Sources: [Vinted]() Topics: [Dependency injection](), [Android](), [migration](), [Kotlin](), [Dagger](), [interoperability](), [Compiler](), [modules](), [Gradle]() Tags: [android](), [compatibility](), [compilation](), [dagger](), [dependency-injection](), [gradle](), [interoperability](), [kotlin](), [migration](), [modules]() ### AI overview Vinted's Android developers describe their migration from Dagger and related dependency-injection tools to Metro. The article covers their large, modular codebase, Anvil's maintenance status and K2 migration pressure, and Metro's interoperability with Dagger, Anvil, and kotlin-inject. ### Source excerpt Metro - modern and kotlin injection framework created by Zac Sweers. And we, Android developers at Vinted, officially and fully migrated to it! It was quite a bumpy ride for our huge codebase. Our story begins... ## Flattening my Dependency Graph DevFeed: [Flattening my Dependency Graph]() Original publisher: [Read original article]() Author: Jesse Wilson Published: 2026-02-03T05:28:50Z Content type: opinion Language: en Sources: [Public Object]() Topics: [Kotlin](), [Persistence](), [Dependency injection](), [PostgreSQL](), [Ktor]() Tags: [dependency-injection](), [kotlin](), [ktor](), [modules](), [persistence](), [postgresql]() ### AI overview The author describes structuring a Kotlin server's dependency graph using a three-module pattern for each feature: public API, implementation, and dependency-injection wiring. The approach aims to support parallel builds, reduce unnecessary rebuilds, and keep dependencies manageable. ### Source excerpt Rounds has a Kotlin server that integrates a few things: PostgreSQL persistence via SQLDelight (hosted on PlanetScale!) WebAuthn4J for Passkeys kotlinx.html for dynamic web pages Ktor for HTTP binding The service uses six database tables. The business domain tables are Game and GameEvent. Support for auth, sessions, and collaborative ## Why I'm Seeking Sponsors for Metro, a Kotlin Dependency Injection Compiler DevFeed: [Why I'm Seeking Sponsors for Metro, a Kotlin Dependency Injection Compiler]() Original publisher: [Read original article]() Author: Zac Sweers Published: 2026-01-29T15:56:29Z Content type: opinion Language: en Sources: [Zac Sweers]() Topics: [Compiler](), [Dependency injection](), [build performance](), [build times](), [Kotlin](), [Mobile](), [monorepo]() Tags: [android](), [build-performance](), [build-times](), [compiler](), [dependency-injection](), [developer-productivity](), [kotlin](), [metro](), [monorepo](), [open-source]() ### AI overview The author discusses opening GitHub sponsorship for Metro, a Kotlin dependency injection project. They report build-performance gains, benchmark results against Dagger, compatibility across Kotlin and IDE versions, and adoption by several engineering teams. ### Source excerpt Metro is the proudest work of my career. Ever since starting it on vacation in November 2024, building it has been an incredible journey and the community reception has been nothing short of wonderful. It sits at the intersection of several fields I've come to specialize in, ranging ## Cash Android Moves to Metro DevFeed: [Cash Android Moves to Metro]() Original publisher: [Read original article]() Author: Egor Andreevich Published: 2025-11-18T00:00:00Z Content type: article Language: en Sources: [Cash App Code Blog]() Topics: [migration](), [Android](), [Dependency injection](), [Kotlin](), [Dagger]() Tags: [android](), [dagger](), [dependency-injection](), [kotlin](), [migration]() ### AI overview The Cash Android team completed a migration from Dagger and Anvil to Metro, a compile-time dependency injection framework. The move was driven by the Kotlin-heavy codebase, the complexity of Dagger's Java-based build pipeline, and Anvil's lack of K2 support. ### Source excerpt The Cash Android team have completed the migration to Metro. ## Design Patterns Are Everywhere in Laravel. The Artisan of the Day Is Mary Perry. DevFeed: [Design Patterns Are Everywhere in Laravel. The Artisan of the Day Is Mary Perry.]() Original publisher: [Read original article]() Author: Ana Tavares Published: 2025-08-07T12:49:56Z Content type: article Language: en Sources: [Laravel Blog]() Topics: [Laravel](), [Code](), [Dependency injection](), [Databases]() Tags: [architecture](), [code](), [community](), [database](), [dependency-injection](), [design-patterns](), [developer](), [ecosystem](), [framework](), [laravel]() ### AI overview This Laravel article profiles Mary Perry and her Laracon talk about the design patterns embedded in Laravel's architecture. It describes singleton and factory patterns, facades as encapsulation, dependency injection through the service container, and the builder pattern in the middleware pipeline. ### Source excerpt When it comes to finding the poetry hidden in Laravel's architecture, Mary Perry sees what others miss. ## Simplifying a Proposed File-List Composable Through Architecture Review DevFeed: [Simplifying a Proposed File-List Composable Through Architecture Review]() Original publisher: [Read original article]() Published: 2025-06-06T03:47:36Z Content type: opinion Language: en Sources: [Blogs on Ryan Harter]() Topics: [Code](), [Dependency injection](), [interfaces](), [App]() Tags: [architecture](), [code](), [dependency-injection](), [interfaces](), [simplify]() ### AI overview An architecture and tech-spec review of a proposed file-list Composable revealed that its dependency-injection machinery and added interfaces created unnecessary complexity. By examining use cases, letting callers construct data sources, and removing interfaces that added no value, the team simplified the design until the proposed code was eliminated. ### Source excerpt Over the past few years I've been driving an architecture and tech spec review process at work. This has been helpful in breaking down certain silos, distributing knowledge across the organization, and building skills and experience in more junior engineers. A recent tech spec caught my eye, and resulted in a really valuable learning opportunity. The specifics of the spec aren't terribly important, but at a high level the proposal was to introduce a single Composable to represent lists of files anywhere in the app. Due to the multitude of sources that can provide lists of files this was accomplished with a relatively complex set of generic data source factories that were registered via our dependency injection system to later be looked up and constructed. ## How To Refactor Legacy Code DevFeed: [How To Refactor Legacy Code]() Original publisher: [Read original article]() Author: Daniel Moka Published: 2025-04-12T05:01:26Z Content type: tutorial Language: en Sources: [Craft Better Software]() Topics: [Refactoring](), [Testing](), [Dependency injection](), [Test coverage](), [Mocking]() Tags: [dependency-injection](), [how-to](), [legacy-code](), [refactor](), [refactoring](), [testing](), [tests]() ### AI overview A six-step strategy for refactoring legacy code by breaking dependencies, using characterization and other testing techniques, achieving test coverage, and then changing the code. ### Source excerpt The art of making your code testable, testing it effectively, and refactoring it like a pro ## Introducing Metro, a Kotlin compiler-plugin dependency injection framework DevFeed: [Introducing Metro, a Kotlin compiler-plugin dependency injection framework]() Original publisher: [Read original article]() Author: Zac Sweers Published: 2025-04-03T16:14:23Z Content type: article Language: en Sources: [Zac Sweers]() Topics: [Dependency injection](), [Compiler](), [Kotlin](), [multiplatform](), [build performance](), [benchmarking]() Tags: [anvil](), [benchmarking](), [build-performance](), [compilation](), [compiler](), [dagger](), [dependency-injection](), [error-messages](), [kotlin](), [metro](), [multiplatform]() ### AI overview The article introduces Metro, a Kotlin compiler-plugin framework for compile-time dependency injection. It combines ideas from Dagger, Anvil, and Kotlin-Inject, and describes features including dependency graph validation, code generation, multiplatform support, IDE integration, and diagnostics. The author reports benchmarked build-time improvements in a CatchUp app and notes that Metro 0.1.1 is in active development. ### Source excerpt I'm excited to share something new I've been working on the past few months! ## Bridging Compose and View: Seamless Interop Communication with CompositionLocal DevFeed: [Bridging Compose and View: Seamless Interop Communication with CompositionLocal]() Original publisher: [Read original article]() Author: Julien Salvi Published: 2025-03-05T13:42:13Z Content type: tutorial Language: en Sources: [Stories by Julien Salvi on Medium]() Topics: [Compose](), [interoperability](), [Dependency injection](), [ui]() Tags: [android](), [android-development](), [androiddev](), [bridge](), [compose](), [dependency-injection](), [interface-implementation](), [interoperability](), [jetpack-compose](), [sharedflow](), [stateflow](), [ui](), [viewmodel]() ### AI overview This tutorial explains how to bridge Jetpack Compose and traditional Android Views using CompositionLocal. It shows how to provide a FeedbackMessageInterop implementation so composables can trigger View-based feedback, and describes the reverse direction through an interface and reactive streams such as StateFlow or SharedFlow. ### Source excerpt Migrating to Compose exposed the team to several interoperability challenges as we integrated new Composables into our existing codebase. One key hurdle was figuring out how to trigger events from Compose and dispatch them to the main View holder, such as a Fragment or Activity. After some exploration, we found an efficient solution using CompositionLocal. Here's how we made it work! 🚀 What is a CompositionLocal? Think of CompositionLocal as a localized dependency injection system built directly into Compose's composition model. You create a CompositionLocal instance, which acts as a key for a specific type of data. Then, using the CompositionLocalProvider, you define a scope within your UI tree and associate a value with that CompositionLocal key. Any composable within that scope can then access the provided value using the CompositionLocal.current property, without needing to know where the value originated. This not only simplifies code but also makes it more maintainable and reusable. Furthermore, CompositionLocal values can be dynamic, triggering recomposition when they change, and they are thread-safe, making them a powerful tool for managing shared state within your Compose UI. Interop Communication with CompositionLocal In the following code, LocalFeedbackInterop is a staticCompositionLocalOf that will hold an implementation of the FeedbackMessageInterop interface. This interface defines the methods for showing feedback alerts, and the staticCompositionLocalOf ensures that the implementation is unlikely to change as it cannot be re-provided. This allows any composable within the scope to access the FeedbackMessageInterop implementation and trigger feedback messages without explicit dependencies. import androidx.compose.runtime.ProvidableCompositionLocal import androidx.compose.runtime.staticCompositionLocalOf val LocalFeedbackInterop: ProvidableCompositionLocal = staticCompositionLocalOf { null } interface FeedbackMessageInterop { fu ## GameChanger and Anvil DevFeed: [GameChanger and Anvil]() Original publisher: [Read original article]() Author: GameChanger Published: 2024-09-18T04:00:00Z Content type: article Language: en Sources: [GameChanger]() Topics: [Dagger](), [Dependency injection](), [Android](), [Architecture & Design](), [Code quality]() Tags: [android](), [code-quality](), [dagger](), [dependency-injection](), [development-tools](), [workflows]() ### AI overview GameChanger describes how its App Platform team integrates Anvil with an existing Dagger setup in an Android codebase. The effort streamlines dependency injection and supports modularization, consistent architecture, reduced cognitive load, faster onboarding, and improved code quality. ### Source excerpt At GameChanger, we have a dedicated App Platform team that focuses on scaling our engineering organization and supporting development teams across the company. Our mission is to make building things the right way the easy way for all developers at GameChanger. This involves: Implementing and maintaining core infrastructure like dependency injection systems Creating and improving development tools and workflows Establishing best practices and architectural patterns Providing support and guidance to feature teams By having a dedicated team focus on these foundational aspects, we achieve several benefits: Consistency across the codebase, making it easier for developers to switch between projects Reduced cognitive load for feature teams, allowing them to focus on business logic Faster onboarding for new team members Improved code quality and maintainability The work on integrating Anvil with our existing Dagger setup is a prime example of how the App Platform team contributes to these goals. By streamlining our dependency injection process, we're making it easier for all teams to build features efficiently and correctly. With this context in mind, let's explore the technical details of our setup and why we chose to augment Dagger with Anvil. What's the setup? The Android codebase has the following Dagger components: a longstanding Application Component, a User Component that lives for as long as the user is logged in, and Game Components that last for as long as any live game. Features usually involve a fragment to render UI and a view model to manage business logic and state. Said view model is supplied by a factory in either the Application Component or User Component and pulls in dependencies from the rest of the Dagger graph that may come from any of the mentioned components. So Why Anvil? 1. Anvil makes modularization easy: We're following, as shown in the diagram above, a format for modules across the codebase to follow that involve the inversion of control princi ## Essential Components of an Android Developer GitHub Showcase Project DevFeed: [Essential Components of an Android Developer GitHub Showcase Project]() Original publisher: [Read original article]() Author: Ban Markovic Published: 2024-02-05T11:00:04Z Content type: tutorial Language: en Sources: [Stories by Ban Markovic on Medium]() Topics: [Android](), [android-development](), [Mobile](), [Kotlin](), [REST API](), [Coroutines](), [Dependency injection]() Tags: [android](), [android-development](), [androiddev](), [coroutines](), [dependency-injection](), [github](), [jetpack-compose](), [kotlin](), [mvi](), [mvvm](), [portfolio](), [rest-api](), [screen](), [unit-tests]() ### AI overview The article recommends building a concise Android showcase project for a GitHub portfolio. The project should use two screens to fetch and display a list from a REST API, support navigation to item details, demonstrate MVI or MVVM architecture, organize files clearly, handle asynchronous work, include unit tests, and use dependency injection. ### Source excerpt In the competitive world of Android development, having a strong GitHub portfolio is crucial for showcasing your skills to potential employers. One effective way to demonstrate your expertise is by creating a concise yet comprehensive project that highlights key aspects of Android development. In this article, we'll explore the essential components that every Android developer should have in their GitHub, focusing on a project that encapsulates fundamental skills. The Project Overview A successful showcase project should include two screens and cover the following key functionalities: Fetching and Displaying Data - Utilize a REST API to fetch a list of items. - Display this list on the first screen of the app. Navigation and Detailed Information - Enable users to navigate to a second screen by clicking on a specific item. - On the second screen, display more detailed information about the selected item. Key Considerations for the Showcase ProjectArchitecture -- MVI or MVVM Clearly implement and showcase your understanding of the chosen architecture (MVI or MVVM). Organize code files in a logical and easily understandable structure. File Organization Demonstrate a well-organized project structure, separating concerns and making codebase easily maintainable (feature-based or type-based folders structure). Asynchronous Communication Showcase your proficiency in handling asynchronous tasks by using an appropriate library (e.g., Kotlin Coroutines, LiveData, RxJava). Unit Tests Impress potential employers by including unit tests to validate the functionality of critical components (cover your ViewModel, UseCase, Repository classes with unit tests). Dependency Injection (DI): Implement and demonstrate your use of dependency injection for managing component dependencies (Hilt, Dagger, Koin). Why This Project Matters This concise project effectively showcases your abilities in: Displaying a list of items Fetching data from the internet Implementing navigation between screens [Next page]()