What problems can arise when using Dagger?

Complexity of learning and configuring: Dagger has a steep learning curve, requiring understanding of DI (Dependency Injection) concepts, annotations, and how to work with it. In the initial stages, it can be challenging to correctly set up the dependency graph.
Slow compilation: Dagger's code generation can significantly increase build times, especially in large projects with extensive dependency graphs.
Debugging difficulty: Troubleshooting issues related to Dagger can be difficult. Errors often occur at compile time, and error messages may not always be informative.
Boilerplate code: Although KSP/KAPT help reduce boilerplate, additional code may be necessary for dependency binding and provision in Dagger.
Multi-module project issues: Configuring Dagger in multi-module projects requires careful management of dependencies between modules and proper component linking.
Outdated versions: Using outdated versions of Dagger can lead to compatibility issues and lack of new features or bug fixes.
Implicit dependencies: Dagger encourages explicit declaration of dependencies, but improper use or excessive use of @Inject annotations can lead to implicit dependencies, complicating code understanding.
Migration complexity: Migrating an existing project to Dagger can be labor-intensive and require significant code changes.
Lifecycle issues: Improper management of component and dependency lifecycles can lead to memory leaks or runtime errors.
Testing issues: Setting up Dagger for unit and integration tests may require additional effort to mock dependencies.