If our app is lagging due to high memory usage, we should start by profiling it using tools like Android Studio Profiler, or Xcode Instruments to pinpoint bottlenecks. We can optimize data structures by replacing HashMap with SparseArray (Android) or using ArrayDeque instead of Stack for better efficiency. Implementing lazy loading and caching will help by loading resources only when needed and using an LRU cache for frequently accessed data. Reducing unnecessary object allocations, tuning garbage collection, and properly managing resources—like closing database cursors and avoiding memory leaks from static Context references—are also key.

I have worked closely with our engineering team to prioritize memory management techniques like implementing lazy loading and optimizing data structures. When explaining these optimizations to stakeholders, I have also learnt to translate memory improvements into tangible user benefits like "40% faster load times on older devices" rather than technical metrics that are difficult to comprehend.

1. Use caching, downscale large images, and load images efficiently 2. Implement Lazy Loading & Pagination 3. Load data in chunks to reduce memory pressure 4. Stream data instead of loading everything at once (Use Memory-Efficient APIs)

You can optimize memory usage by using efficient data structures, implementing lazy loading, reducing memory leaks, and optimizing algorithms to minimize unnecessary object creation.

My number one solution to this issue is optimizing the visuals. You might have to delete some of them and consider hosting it on a dedicated server.

To optimize your app's performance and address high memory usage, start by profiling the app to pinpoint areas consuming excessive memory. Tools like memory profilers can help identify memory leaks and inefficient resource management.

Optimizing app performance requires a strategic approach to memory management. Beyond profiling and data structure optimization, consider leveraging caching mechanisms to reduce redundant data processing and implementing memory-efficient algorithms. Additionally, adopting modular design principles can help isolate and address memory leaks more effectively. Regularly monitoring and testing under real-world conditions ensures sustained performance improvements. Ultimately, a proactive, iterative approach to optimization is key to maintaining a responsive and efficient application.

Use lazy loading to load the required data only, Apply redis cache or clickhouse, Check for web vitals if it is a frontend application, Apply multi threading and fetch the data in chunks

1. Investigate bottleneck by reducing api call as much as you can 2. Refactor code which has I/O by using asynchronous process 3. Apply disposable pattern after processing file/data to clean up memory

To optimize app performance and reduce memory usage, start by using memory profiling tools to identify leaks and excessive allocations. Implement effective garbage collection by managing object lifecycles and disposing of unused resources properly. Opt for efficient data structures to decrease overhead and use lazy loading to fetch resources only when needed. Optimize images through compression and lower resolutions. Consider using object pooling to reuse instances rather than creating new ones constantly. Streamline your code to eliminate redundancies, and evaluate third-party libraries, removing any unnecessary dependencies. These strategies can significantly enhance performance and minimize memory consumption.