Optimizing the performance of your Android app can greatly enhance the user experience. One critical aspect of this is structuring your Android project effectively. Below are some tips to help you achieve better performance through project structure.
Divide your application into smaller, manageable modules. This can help in isolating features, making the codebase cleaner and easier to maintain. It also allows for more effective collaboration between developers.
Organize your resources (like images, layouts, and strings) in separate folders based on their usage. This reduces the APK size and ensures that only relevant resources are loaded in memory.
Define different build types in your Gradle file for production, development, and testing. This allows for optimization specific to each environment and can help in reducing the overall build time.
Using dependency injection frameworks (like Dagger or Hilt) can help in managing dependencies more efficiently. This leads to better testability and reduces the chances of memory leaks.
Applying ProGuard or R8 can obfuscate your code and remove unused methods and classes. This reduces the size of your APK, leading to faster app updates and reduced load times.
Minimize the usage of complex scripts in your Gradle files. Keep them clean and organized to improve build speed and maintainability.
// Project structure example
MyApplication/
├── app/
│ ├── src/
│ │ ├── main/
│ │ │ ├── java/
│ │ │ ├── res/
│ │ │ ├── AndroidManifest.xml
│ ├── build.gradle
├── build.gradle
├── settings.gradle
How do I avoid rehashing overhead with std::set in multithreaded code?
How do I find elements with custom comparators with std::set for embedded targets?
How do I erase elements while iterating with std::set for embedded targets?
How do I provide stable iteration order with std::unordered_map for large datasets?
How do I reserve capacity ahead of time with std::unordered_map for large datasets?
How do I erase elements while iterating with std::unordered_map in multithreaded code?
How do I provide stable iteration order with std::map for embedded targets?
How do I provide stable iteration order with std::map in multithreaded code?
How do I avoid rehashing overhead with std::map in performance-sensitive code?
How do I merge two containers efficiently with std::map for embedded targets?