2018
Autores
Saraiva, J; Abreu, R; Cunha, J; Fernandes, JP;
Publicação
Impact
Abstract
2018
Autores
SARAIVA, J; HASLab/INESC TEC, University of Minho, Portugal,; COUTO, M; SZABÓ, C; NOVÁK, D; HASLab/INESC TEC, University of Minho, Portugal,; Department of Computers and Informatics, Faculty of Electrical Engineering and Informatics, Technical University of Košice, Letná 9, 042 00 Košice, Slovak Rep,; Department of Computers and Informatics, Faculty of Electrical Engineering and Informatics, Technical University of Košice, Letná 9, 042 00 Košice, Slovak Rep,;
Publicação
Acta Electrotechnica et Informatica
Abstract
2020
Autores
Maia, D; Couto, M; Saraiva, J; Pereira, R;
Publicação
2020 35TH IEEE/ACM INTERNATIONAL CONFERENCE ON AUTOMATED SOFTWARE ENGINEERING WORKSHOPS (ASEW 2020)
Abstract
This paper extends previous work on the concept of a new software energy metric: Energy Debt. This metric is a reflection on the implied cost, in terms of energy consumption over time, of choosing an energy flawed software implementation over a more robust and efficient, yet time consuming, approach. This paper presents the implementation a SonarQube tool called E-Debitum which calculates the energy debt of Android applications throughout their versions. This plugin uses a robust, well defined, and extendable smell catalog based on current green software literature, with each smell defining the potential energy savings. To conclude, an experimental validation of E-Debitum was executed on 3 popular Android applications with various releases, showing how their energy debt fluctuated throughout releases.
2020
Autores
Macedo, Jd; Aloísio, J; Gonçalves, N; Pereira, R; Saraiva, J;
Publicação
35th IEEE/ACM International Conference on Automated Software Engineering Workshops, ASE Workshops 2020, Melbourne, Australia, September 21-25, 2020.
Abstract
2021
Autores
Pereira, R; Couto, M; Ribeiro, F; Rua, R; Cunha, J; Fernandes, JP; Saraiva, J;
Publicação
SCIENCE OF COMPUTER PROGRAMMING
Abstract
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.
2020
Autores
de Mendonça, WLM; Fortes, J; Lopes, FV; Marcilio, D; Bonifácio, R; Canedo, ED; Lima, F; Saraiva, J;
Publicação
J. Softw. Eng. Res. Dev.
Abstract
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