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... of a measurement method [12]. The EAL should provide measurement capabilities per application and component. This would be especially helpful for finding energy wasting code patterns in applications =-=[2]-=-. The EAL should provide suitable error handling. As not every device and platform supports every measurement method, the EAL should report, if certain measurement capabilities are not present. The EA...

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...nergy code smells and their restructurings are defined and described similar as the code smells of Fowler [3]. Two such energy code smells are Binding ressources too early and Third party advertising =-=[4]-=-. Binding ressources too early: When applications are binding resources it could be that applications request a resource too early. This means that resources, like GPS and WiFi, are started and consum...

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... implementation choices (at code, design or architectural level) that make the software execution less energy efficient. Combining our experience together with the evidence provided by similar works (=-=[12]-=-, [13], [14] and [15]), we derive a few lessons learned, which represent a set of code-level guidelines for developers aiming at greening their applications. Clean up useless code and data. As softwar...

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...hones and tablets. The battery usage limits the daily device availability and decreases the long term battery quality. Reducing the energy consumption of these devices decreases the number of loading cycles, improves user satisfaction, reduces total operational cost, and eases the carbon footprint of mobile technology [1, 2]. Recent developments in battery technology are mostly defined by larger or brighter displays, faster central processing units (CPU), or an increasing number of sensors [3]. Optimizations on the operating system (OS) level cannot compensate for that increasing power demand [4]. An underestimated optimization potential can be found in applications (apps) [5, 6, 7]. Capra, Formenti et al. [8] showed that, under the same workload, different Enterprise Applications (EA) with similar functionality have significantly different levels of energy consumption [8]. Comparable effects can be discovered in apps on mobile devices [9]. Reducing the power demand of apps can be achieved by exchanging algorithms or resources and limiting the usage of sensors or network traffic [1, 3]. The most common methodology to enable developers to detect energy bugs is energy profiling [10]. Pr...

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... be used to monitor and rate an application’s energy consumption, detect energy code smells, and subsequently remove them. To support the study of different research questions in this area (cf. [28], =-=[29]-=-, [30]), a suitable tool infrastructure has to be built, combining tools for static and dynamic code analysis, metrics evaluation, refactoring, and visualization, as well as “helper” tools, e.g. for p...

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...s of code analysis and transformation is called refactoringsin this work. The approach starts with defining energy-inefficient code parts called energy codessmells. For these, a reengineering process =-=[6]-=- is described and validated by different, softwarebased energy measurement techniques [7]. Aim of this work is the collection and validation ofsenergy code smells and corresponding refactorings which ...

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...서는 실 험 설계와 결과에 대해 다룬다. 4장에서는 실험을 통해 얻 은 데이터를 바탕으로 특이점에 대해 분석한다. 5장에서는s예제 시스템을 통해 전력 효율성에 대한 효과를 확인하고 6 장에서는 결론 및 향후 연구를 기술한다. 2. 관련 연구 코드 리팩토링과 소프트웨어 전력 효율성 사이의 관계를s분석하는 연구들이 진행되고 있다. 대표적으로 Gottschalk=-=[12]-=-,sMarion[13], Silva [14]의 연구가 있다. Gottschalk[12]는 다양한 종류의 Energy Code Smell을s소개하였다. Loop Bug와 Dead Code등의 일반적인 CodesSmell들을 재조명하여 전력 낭비에 어떠한 영향을 미치고s있는지 설명하고, Restructuring을 통해 전력 낭비의 최소화 를 유도하였다. 그러나...