Thu 8 Nov 2018 16:00 - 16:30 at Horizons 6-9F - Energy Chair(s): Diego Garbervetsky

This work considers watch faces for Android Wear devices such
as smartwatches. Watch faces are a popular category of apps that
display current time and relevant contextual information. Our
study of watch faces in an app market indicates that
energy efficiency is a key concern for users and developers.

The first contribution of this work is the definition of several
energy-inefficiency patterns of watch face behavior, focusing on two
energy-intensive resources: sensors and displays. Based on these
patterns, we propose a control-flow model and static analysis
algorithms to identify instances of these patterns. The algorithms
use interprocedural control-flow analysis of callback methods and the
invocation sequences of these methods. Potential energy inefficiencies
are then used for automated test generation and execution, where the
static analysis reports are validated via run-time execution. Our
experimental results and case studies demonstrate that the analysis
achieves high precision and low cost, and provide insights into
potential pitfalls faced by developers of watch faces.

Thu 8 Nov

Displayed time zone: Guadalajara, Mexico City, Monterrey change

15:30 - 17:00
EnergyResearch Papers / Journal-First at Horizons 6-9F
Chair(s): Diego Garbervetsky University of Buenos Aires, Argentina
Approximate Oracles and Synergy in Software Energy Search Spaces
Bobby R. Bruce , Justyna Petke University College London, Mark Harman Facebook and University College London, Earl T. Barr
Detection of Energy Inefficiencies in Android Wear Watch Faces
Research Papers
Hailong Zhang Ohio State University, Haowei Wu , Atanas Rountev Ohio State University
Stochastic Energy Optimization for Mobile GPS Applications
Research Papers
Anthony Canino SUNY Binghamton, Yu David Liu State University of New York (SUNY) Binghamton, Hidehiko Masuhara Tokyo Institute of Technology