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Mobile Performance and Energy Optimization Questions

Comprehensive engineering and operational practices for diagnosing, profiling, and optimizing mobile application performance and device energy consumption at feature and system scale. Candidates should be able to explain strategies to reduce application startup time, minimize main thread work to keep the user interface responsive, and stabilize rendering at target frames per second such as sixty frames per second and one hundred and twenty frames per second to avoid application not responding situations. Core topics include memory management and leak prevention, allocation analysis, preventing crashes and responsiveness regressions, efficient rendering of large feeds, complex gesture and input handling, and efficient handling of large media such as photos and video. Common techniques include lazy loading, request batching, image resizing and compression, caching and batching strategies, offline first synchronization, and efficient background processing and scheduling to limit energy impact. Energy and battery focused optimizations include minimizing sensor usage and location service use when unnecessary, geofencing best practices, network and radio optimizations to reduce radio wake ups, preferring push driven updates over polling where appropriate, and designing background tasks to be energy aware. Candidates should demonstrate familiarity with profiling and instrumentation tools and workflows for mobile platforms, interpreting profiler output to identify central processing unit and memory bottlenecks, measuring and quantifying latency and energy impact, designing architectural and code changes to prevent regressions, reasoning about trade offs between native and cross platform implementations, and defining user perceived performance and energy metrics with continuous monitoring and tests to quantify improvements.

EasyTechnical
0 practiced
Mobile UI jank often comes from excessive work on the main/UI thread. List common categories of main-thread work that cause jank and describe at least five concrete techniques you would use to minimize main-thread work in a platform-agnostic way. Include examples such as moving I/O off-thread, deferring non-critical work, and chunking long computations.
HardTechnical
0 practiced
You must render a mixed-content feed that includes images, videos, ads and interactive widgets while guaranteeing 60fps on average devices. Propose a scheduling algorithm to prioritize decoding, layout, and network fetching for visible and near-visible items. Include how to handle backpressure when CPU or GPU resources are saturated.
EasyTechnical
0 practiced
List and compare profiling and instrumentation tools you would use to diagnose CPU, memory, rendering, and energy issues on Android and iOS. Include at least one low-level trace tool and one energy-specific tool or workflow, and explain when each is the right choice.
MediumTechnical
0 practiced
Design an image pipeline for a mobile feed that handles source images up to 8MB, must serve 50 images per page, and should minimize memory, CPU, and battery while keeping high visual quality. Describe server-to-client responsibilities, on-device downsampling, decode strategies, caching tiers, preferred image formats, and how progressive rendering or thumbnails could be used.
HardSystem Design
0 practiced
Design an architecture that decides when to perform heavy media processing on-device versus server-side. Consider privacy constraints (sensitive content), latency, battery cost, device capability heterogeneity, and server cost. Propose a hybrid approach that minimizes user-perceived latency and energy impact while respecting privacy.

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