A Clean & Practical Code Review Checklist for Android Projects

In Android projects — especially large-scale, multi-module, production apps — having a consistent review checklist reduces technical debt and keeps standards aligned across the team.
They are about maintainability, scalability, performance, and team trust.
Here’s a practical checklist I use for Android projects.

1. Architecture & Design

Good architecture makes the project survivable after years.

✔ Architecture Consistency

• Follows Clean Architecture / MVVM / MVI consistently
• Uni-directional data flow maintained
• Clear separation of UI / Domain / Data layers

✔ Business Logic Placement

• No business logic inside Activities or Fragments (or compose)
• ViewModels only handle UI-related logic
• Domain logic lives inside UseCases

✔ UseCases

• Single responsibility
• Small and focused
• No multi-purpose “God” use cases

✔ Dependency Injection

• Hilt / Dagger properly configured
• No manual dependency wiring
• No service locators hidden inside code

✔ Design Principles

• SOLID principles followed, along with others(DRY, KISS, GRASP, CQRS)
• Reuse of existing utility functions where appropriate
• No duplicated logic
• No broken unit tests

2. Kotlin & Language Usage

Kotlin gives powerful tools. Use them wisely.

✔ Immutability First

• Prefer val over var
• Immutable state where possible ### ✔ Kotlin Types
• Use data class for models
• sealed class for state representation
• enum when appropriate ### ✔ Null Safety
• Avoid nullable chains like ?.?.?.
• No use of !!
• Handle nulls explicitly and safely ### ✔ Extension & Scope Functions
• Extension functions improve readability (not dumping business logic)
• Scope functions (let, apply, run, also, with) used meaningfully
• No nested scope-function pyramids ### ✔ Data Structures
• Correct usage of List, MutableList, Map, Set
• Avoid unnecessary list copying
• Efficient transformations (map, filter, associate, etc.)

3. UI Layer (Compose / XML)

UI should be predictable and state-driven.

Jetpack Compose

• State hoisted properly
• UI is stateless where possible
• No side effects inside composables
• Use LaunchedEffect, SideEffect, remember, derivedStateOf correctly
• Awareness of recomposition behavior (use of key in list generate)
• Avoid unnecessary recompositions

XML / View System

• No heavy logic inside views
• Avoid deeply nested layouts
• ViewBinding enabled (no findViewById)
• No memory leaks from view references

4. State & Async Handling

Async mistakes are expensive in production.

✔ Coroutines & Flow

• Proper use of Flow, StateFlow, or LiveData
• No GlobalScope
• Cold vs hot stream usage is correct ### ✔ Dispatcher Usage
• IO for network/database
• Default for CPU work
• Main for UI ### ✔ Cancellation
• Jobs cancelled properly
• ViewModelScope used correctly ### ✔ Avoid Blocking
• No runBlocking in production
• No Thread.sleep()
• No heavy work on Main thread

5. Error Handling

Error handling defines production quality.

• Errors modeled explicitly (Result, Either, sealed classes)
• No silent catch {} blocks
• User-friendly error states exposed to UI
• Logs added meaningfully (no spam logging) 

6. Performance

Performance issues hide in small mistakes.

• No heavy work on Main thread
• Avoid unnecessary recompositions
• Efficient list rendering (LazyColumn, DiffUtil)
• Pagination or lazy loading where needed
• No memory leaks (Context misuse, observers not cleared)

7. Testing

If it’s not tested, it’s fragile.

• Unit tests for UseCases
• Unit tests for ViewModels
• UI logic is state-driven and testable
• Mocks/Fakes used properly
• Descriptive test names
• Minimum coverage target followed (e.g., 80%)
• Test functions are maintainable and readable

8. Code Quality & Readability

Code should read like documentation.

• Small and focused functions
• Meaningful naming (no data, temp, obj)
• No commented-out dead code
• Consistent formatting (ktlint, detekt)
• No magic numbers — use constants

9. Security & Configuration

Small mistakes here can be costly.

• No API keys or secrets inside source code
• Tokens loaded from secure config
• Proguard / R8 rules reviewed
• Debug-only tools not leaking into release builds
• Do not pass secret user-data every layer or keep in memory
• Follow Security team guideline to avoid pentest defects/review comments

10. Git & PR Hygiene

Good PR hygiene reduces team friction.

• PR is small and focused
• Large tasks split into smaller subtasks
• Clear description of what and why
• Screenshots for UI changes
• Screen recording for flow (even with mock data)
• For defect fixes: include reproduction path and screen record
• Linked ticket/task for feature or bug
• No unrelated changes in the same PR

Final Thoughts

A good code review is not about nitpicking syntax.
It’s about protecting the future of the codebase.
When teams follow a structured checklist:

• Bugs decrease
• Performance improves
• Onboarding becomes easier
• Refactoring becomes safer (layer by layer)
• Trust increases

Code quality is not accidental. It is enforced — consistently.