2019 · 12 citations · 5 references
ComputingComputer EngineeringComputer ScienceMobile ComputingMobile SystemsSoftware EngineeringAlgorithm AnalysisEnergy-efficient Mobile ComputingMobile Application DevelopmentPower EstimationPower ManagementSorting AlgorithmsApplication-specific Power EstimationEmpirical EvaluationEnergy ConsumptionEnergy ProfilingEnergy-efficient AlgorithmsMobile Device Energy ProfilingSoftware Quality AttributesSoftware Quality Measurement
With the advent of mobile application development a new software quality concern - energy consumption - was introduced. For mobile software developers knowledge about software and algorithm design choices and their implications on energy consumption is crucial. However, software developers either lack this knowledge or tools to support them in estimating the energy consumption of their applications and therefore are unable to reflect on their design choices. In this empirical study we examine the energy consumption of 12 sorting algorithms and the resulting energy impact when used with different data types. We propose a methodology to obtain energy readings and relate them to application execution traces. Our results show that the choice of data type together with algorithm design can have significant impact on the energy profile of an application.
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Calculating source line level energy information for Android applications
Ding Li, Shuai Hao, William G. J. Halfond et al. · 2013 · 199 citations
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