Mobile Memory and Resource Management Questions

Covers memory management principles and resource handling for mobile applications across platforms. Candidates should understand platform specific models such as automatic reference counting on iOS and garbage collection on Android, common causes of memory leaks and retain cycles, and how reference ownership and weak versus strong references affect lifetime. Include techniques for releasing resources correctly in lifecycle methods and avoiding long lived references that hold activity or context objects. Expect knowledge of memory profiling and diagnostics including tools and workflows for locating leaks and high memory usage, strategies to prevent out of memory conditions, and trade offs such as requesting a larger heap. Also cover cross platform considerations for frameworks like React Native and Flutter and practical practices for identifying and fixing real memory issues in production, such as analyzing heap dumps, using allocation instrumentation, and applying targeted fixes and regression tests.

MediumTechnical

0 practiced

How would you design background features such as push notification handling and background fetch to be memory-efficient? Discuss short-lived processes, minimal allocations, offloading heavy work to servers, using platform job schedulers (WorkManager for Android, BGTasks for iOS), and avoiding holding UI references. Provide concrete examples for Android and iOS.

EasyTechnical

0 practiced

Write Kotlin code you would include in an Activity's onDestroy to safely release heavy resources such as Bitmaps, adapters that reference Views, database Cursors, sensors, and listeners. Explain why each step helps avoid leaks and what else you might do to ensure resources are freed.

MediumSystem Design

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Design a memory-safe architecture for a mobile photo-editing app that must handle very large images (up to 50MP) for editing and exporting. Requirements: editing pipeline with undo/redo, previews and thumbnails, background processing for filters, no OOMs on mid-range devices, responsive UI. Describe component boundaries, streaming/chunked processing approaches, caching policy (disk vs memory), native vs managed code trade-offs, and how undo/redo should be memory-efficient.

MediumTechnical

0 practiced

Compare approaches to diagnosing memory issues in production for Android and iOS apps. Discuss system-level metrics you would collect (RSS, heap usage, peak memory), platform telemetry options (Android Vitals, Firebase Performance, Xcode metrics), privacy and overhead trade-offs for collecting heap snapshots in production, and sampling or throttling strategies to minimize impact.

MediumTechnical

0 practiced

Implement a SafeHandler pattern in Kotlin that avoids leaking an Activity by using a static-like handler and a WeakReference to the Activity. Provide code showing how to post Runnables safely and how to cancel pending messages in onDestroy. Explain why this pattern prevents leaks.

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