TY - GEN
T1 - Detecting anomalous energy consumption in android applications
AU - Couto, Marco
AU - Carção, Tiago
AU - Cunha, Jácome
AU - Fernandes, João Paulo
AU - Saraiva, João
PY - 2014
Y1 - 2014
N2 - The use of powerful mobile devices, like smartphones, tablets and laptops, is changing the way programmers develop software. While in the past the primary goal to optimize software was the run time optimization, nowadays there is a growing awareness of the need to reduce energy consumption. This paper presents a technique and a tool to detect anomalous energy consumption in Android applications, and to relate it directly with the source code of the application. We propose a dynamically calibrated model for energy consumption for the Android ecosystem that supports different devices. The model is used as an API to monitor the application execution: first, we instrument the application source code so that we can relate energy consumption to the application source code; second, we use a statistical approach, based on fault-localization techniques, to localize abnormal energy consumption in the source code.
AB - The use of powerful mobile devices, like smartphones, tablets and laptops, is changing the way programmers develop software. While in the past the primary goal to optimize software was the run time optimization, nowadays there is a growing awareness of the need to reduce energy consumption. This paper presents a technique and a tool to detect anomalous energy consumption in Android applications, and to relate it directly with the source code of the application. We propose a dynamically calibrated model for energy consumption for the Android ecosystem that supports different devices. The model is used as an API to monitor the application execution: first, we instrument the application source code so that we can relate energy consumption to the application source code; second, we use a statistical approach, based on fault-localization techniques, to localize abnormal energy consumption in the source code.
KW - Energy-aware Software
KW - Green Computing
KW - Source Code Analysis
UR - http://www.scopus.com/inward/record.url?scp=84907319512&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84907319512&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-11863-5_6
DO - 10.1007/978-3-319-11863-5_6
M3 - Conference contribution
AN - SCOPUS:84907319512
SN - 9783319118628
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 77
EP - 91
BT - Programming Languages - 18th Brazilian Symposium, SBLP 2014, Proceedings
PB - Springer Verlag
T2 - 18th Brazilian Symposium on Programming Languages, SBLP 2014
Y2 - 2 October 2014 through 3 October 2014
ER -