line Code Quality Improvement Techniques Part 27 (opens in new tab)
Over-engineering through excessive Dependency Injection (DI) can introduce unnecessary complexity and obscure a system's logic. While DI is a powerful tool for modularity, applying it to simple utility functions or data models often creates a maintenance burden without providing tangible benefits. Developers should aim to balance flexibility with simplicity by only injecting dependencies that serve a specific architectural purpose. ### The Risks of Excessive Dependency Injection Injecting every component, including simple formatters and model factories, can lead to several technical issues that degrade code maintainability: * **Obscured Logic Flow:** When utilities are hidden behind interfaces and injected via constructors, tracing the actual execution path requires navigating through multiple callers and implementation files, making the code harder to read. * **Increased Caller Responsibility:** Requiring dependencies for every small component forces the calling class to manage a "bloated" set of objects, often leading to a chain reaction where high-level classes must resolve dozens of unrelated dependencies. * **Data Inconsistency:** Injecting multiple utilities that rely on a shared state (like a `Locale`) creates a risk where a caller might accidentally pass mismatched configurations to different components, breaking the expected association between values. ### Valid Use Cases for Dependency Injection DI should be reserved for scenarios where the benefits of abstraction outweigh the cost of complexity. Proper use cases include: * **Lifecycle and Scope Management:** Sharing objects with specific lifecycles, such as those managing global state or cross-cutting concerns. * **Dependency Inversion:** Breaking circular dependencies between modules or ensuring the code adheres to specific architectural boundaries (e.g., Clean Architecture). * **Implementation Switching:** Enabling the replacement of components for different environments, such as swapping a real network repository for a mock implementation during unit testing or debugging. * **Decoupling for Build Performance:** Separating implementations into different modules to improve incremental build speeds or to isolate proprietary third-party libraries. ### Strategies for Refactoring and Simplification To improve code quality, developers should identify "transparent" dependencies that can be internalized or simplified: * **Direct Instantiation:** For simple data models like `NewsSnippet`, replace factory functions with direct constructor calls to clarify the intent and reduce boilerplate. * **Internalize Simple Utilities:** Classes like `TimeTextFormatter` or `StringTruncator` that perform basic logic can be maintained as private properties within the class or as stateless `object` singletons rather than being injected. * **Selective Injection:** Reserve constructor parameters for complex objects (e.g., repositories that handle network or database access) and environment-dependent values (e.g., a user's `Locale`). The core principle for maintaining a clean codebase is to ensure every injected dependency has a clear, documented purpose. By avoiding the trap of "injecting everything by default," developers can create systems that are easier to trace, test, and maintain.