Reducing Network Usage with Genetic Improvement
Mobile applications can be very network-intensive. Mobile phone users are often on limited data plans, while network infrastructure has limited capacity. There’s little work on optimizing network usage of mobile applications. The most popular approach has been prefetching and caching assets. However, past work has shown that developers can improve the network usage of Android applications by making changes to source code. We built upon this insight and investigated the effectiveness of automated, heuristic application of software patches – a technique known as Genetic Improvement – to improve network usage. Genetic improvement has already shown effective at improving the execution time and memory usage of Android applications. We thus adapt an existing framework with a new mutation operator and develop a new profiler to identify network-intensive methods for improvement. Unfortunately, our approach is unable to find improvements. We conjecture this is due to the fact source code changes affecting network might be rare in the large patch search space. We thus advocate use of more intelligent search strategies in future work.
Tue 16 AprDisplayed time zone: Lisbon change
16:00 - 17:30 | Presentation Session 3 & Discussion & ClosingGI@ICSE at Vianna da Motta Chair(s): Aymeric Blot University of Rennes / IRISA / INRIA, Vesna Nowack Imperial College London | ||
16:00 15mTalk | Human Guidance Approaches for the Genetic Improvement of Software GI@ICSE Benjamin J Craine School of Computing and Communications, Lancaster University, Penny Rainford University of York, Barry Porter Lancaster University | ||
16:15 30mTalk | Reducing Network Usage with Genetic Improvement GI@ICSE William Langdon University College London, James Callan UCL, Justyna Petke University College London | ||
16:45 45mDay closing | Discussion, Awards, and Closing GI@ICSE |