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Many developers have reason to be concerned with with power consumption. For example, mobile app developers want to minimize how much power their applications draw, while still providing useful functionality. However, developers have few tools to get feedback about changes to their application's power consumption behavior as they implement an application and make changes to it over time. We present a tool that, using a team's existing test cases, performs repeated measurements of energy consumption based on instructions executed, objects generated, and blocking latency, generating a distribution of energy use estimates for each test run, recording these distributions in a time series of distributions over time. Then, when these distributions change substantially, we inform the developer of this change, and offer them diagnostic information about the elements of their code potentially responsible for the change and the inputs responsible. Through this information, we believe that developers will be better enabled to relate recent changes in their code to changes in energy consumption, enabling them to better incorporate changes in software energy consumption into their software evolution decisions. |
