Mining energy traces to aid in software development: an empirical case study

Context: With the advent of increased computing on mobile devices such as phones and tablets, it has become crucial to pay attention to the energy consumption of mobile applications. Goal: The software engineering field is now faced with a whole new spectrum of energy-related challenges, ranging from power budgeting to testing and debugging the energy consumption, for which exists only limited tool support. The goal of this work is to provide techniques to engineers to analyze power consumption and detect anomalies. Method: In this paper, we present our work on analyzing energy patterns for the Windows Phone platform. We first describe the data that is collected for testing (power traces and execution logs). We then present several approaches for describing power consumption and detecting anomalous energy patterns and potential energy defects. Finally we show prediction models based on usage of individual modules that can estimate the overall energy consumption with high accuracy. Results: The techniques in this paper were successful in modeling and estimating power consumption and in detecting anomalies. Conclusions: The techniques presented in the paper allow assessing the individual impact of modules on the overall energy consumption and support overall energy planning.