Detecting Energy Patterns in Software Development

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. 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. To the best of our knowledge there has been little work on the analysis of energy patterns. In this paper, we present our work 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 describe prediction models to estimate the overall energy consumption based on usage of individual modules. This allows assessing the individual impact of modules on the overall energy consumption and supports overall energy planning. Keywords—power, energy, testing, power traces, power spikes, anomalies, prediction