Abstract

Abstract
Over the last few years, the interest in the analysis of the energy consumption of Android applications has been increasing significantly. Indeed, there are a considerable number of studies which aim at analyzing the energy consumption in the Android ecosystem, such as measuring/estimating the energy consumed by an application or block of code, or even detecting energy expensive coding patterns or APIs. In this paper, we present an initial study of the impact of memoization in the energy consumption of Android applications. We compare implementations of 18 methods from different applications, with and without using memoization, and measure the energy consumption of both of them. The results show that using memoization can be a good approach for saving energy, since 13 of those methods decreased their energy consumption.

Abstract
Although hardware is generally seen as the main culprit for a computer's energy usage, software too has a tremendous impact on the energy spent. Unfortunately, there is still not enough support for software developers so they can make their code more energy-aware. This paper proposes a technique to detect energy inefficient fragments in the source code of a software system. Test cases are executed to obtain energy consumption measurements, and a statistical method, based on spectrum-based fault localization, is introduced to relate energy consumption to the source code. The result of our technique is an energy ranking of source code fragments pointing developers to possible energy leaks in their code. This technique was implemented in the SPELL toolkit. Finally, in order to evaluate our technique, we conducted an empirical study where we asked participants to optimize the energy efficiency of a software system using our tool, while also having two other groups using no tool assistance and a profiler, respectively. We showed statistical evidence that developers using our technique were able to improve the energy efficiency by 43% on average, and even out performing a profiler for energy optimization.

Abstract

Abstract

Abstract
Smart buildings will play a fundamental role in ensuring comfort while reducing the energy required. However, due to the lack of knowledge about the operation of the smart controllers, the occupants can unintentionally increase the energy spent. Nevertheless, there is evidence that the informed and motivated user will actually cooperate with the system. Some of the issues associated with researching control systems in the context of building automation are difficult to address, because of the chronic lack of effective laboratory settings for experimentation. In this paper, we describe a system representative of the usual complexity found in cyber-physical systems, whose purpose is to address the needs for experimenting with building automation, with a focus on control systems and gamification. Designed with pragmatic concerns, this system presents a unique set of challenges and opportunities to research a new generation of software control systems, and supporting interfaces, that leverage the occupants' behaviour.