NameRui António Rua
Since03rd April 2017
Pereira, R; Couto, M; Ribeiro, F; Rua, R; Cunha, J; Fernandes, JP; Saraiva, J;
SCIENCE OF COMPUTER PROGRAMMING
This paper compares a large set of programming languages regarding their efficiency, including from an energetic point-of-view. Indeed, we seek to establish and analyze different rankings for programming languages based on their energy efficiency. The goal of being able to rank programming languages based on their energy efficiency is both recent, and certainly deserves further studies. We have taken rigorous and strict solutions to 10 well defined programming problems, expressed in (up to) 27 programming languages, from the well known Computer Language Benchmark Game repository. This repository aims to compare programming languages based on a strict set of implementation rules and configurations for each benchmarking problem. We have also built a framework to automatically, and systematically, run, measure and compare the energy, time, and memory efficiency of such solutions. Ultimately, it is based on such comparisons that we propose a series of efficiency rankings, based on single and multiple criteria. Our results show interesting findings, such as how slower/faster languages can consume less/more energy, and how memory usage influences energy consumption. We also present a simple way to use our results to provide software engineers and practitioners support in deciding which language to use when energy efficiency is a concern. In addition, we further validate our results and rankings against implementations from a chrestomathy program repository, Rosetta Code., by reproducing our methodology and benchmarking system. This allows us to understand how the results and conclusions from our rigorously and well defined benchmarked programs compare to those based on more representative and real-world implementations. Indeed our results show that the rankings do not change apart from one programming language. © 2021 Elsevier B.V.
Rua, R; Fraga, T; Couto, M; Saraiva, J;
MOBILESoft '20: IEEE/ACM 7th International Conference on Mobile Software Engineering and Systems, Seoul, Republic of Korea, July 13-15, 2020
Rua, R; Couto, M; Pinto, A; Cunha, J; Saraiva, J;
Proceedings of the XXII Iberoamerican Conference on Software Engineering, CIbSE 2019, La Habana, Cuba, April 22-26, 2019.
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.
Rua, R; Couto, M; Saraiva, J;
Proceedings of the 16th International Conference on Mining Software Repositories, MSR 2019, 26-27 May 2019, Montreal, Canada.
This paper presents the GreenSource infrastructure: a large body of open source code, executable Android applications, and curated dataset containing energy code metrics. The dataset contains energy metrics obtained by both static analysing the applications' source code and by executing them with available test inputs. To automate the execution of the applications we developed the AnaDroid tool which instruments its code, compiles and executes it with test inputs in any Android device, while collecting energy metrics. GreenSource includes all Android applications included in the MUSE Java source code repository, while AnaDroid implements all Android's energy greedy features described in the literature, GreenSource aims at characterizing energy consumption in the Android ecosystem, providing both Android developers and researchers a setting to reason about energy efficient Android software development. © 2019 IEEE.
Pereira, R; Couto, M; Ribeiro, F; Rua, R; Saraiva, J;
Proceedings of the Seventh Workshop on Software Quality Analysis, Monitoring, Improvement, and Applications, SQAMIA 2018, Novi Sad, Serbia, August 27-30, 2018.
This documents introduces \Energyware" as a software engineering discipline aiming at defining, analyzing and optimizing the energy consumption by software systems. In this paper we present energyware analysis in the context of programming languages, software data structures and program's source code. For each of these areas we describe the research work done in the context of the Green Software Laboratory at Minho University: we describe energyaware techniques, tools, libraries, and repositories. © 2018 by the paper's authors.
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