SEOct 20, 2018

Leveraging Program Analysis to Reduce User-Perceived Latency in Mobile Applications

arXiv:1810.08862v131 citations
Originality Incremental advance
AI Analysis

This work addresses user-perceived latency for mobile app users, representing an incremental improvement through automated instrumentation.

The paper tackles the problem of network latency in mobile applications by introducing PALOMA, a client-centric technique that prefetches HTTP requests in Android apps, resulting in runtime savings of several hundred milliseconds per prefetchable HTTP request.

Reducing network latency in mobile applications is an effective way of improving the mobile user experience and has tangible economic benefits. This paper presents PALOMA, a novel client-centric technique for reducing the network latency by prefetching HTTP requests in Android apps. Our work leverages string analysis and callback control-flow analysis to automatically instrument apps using PALOMA's rigorous formulation of scenarios that address "what" and "when" to prefetch. PALOMA has been shown to incur significant runtime savings (several hundred milliseconds per prefetchable HTTP request), both when applied on a reusable evaluation benchmark we have developed and on real applications

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