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About

João Saraiva is Professor Auxiliar at the Departmento de Informática, Universidade do Minho, Braga, Portugal, and a researcher member of HASLab/INESC TEC. He obtained a MSc degree from University do Minho in 1993 and a Ph.D. degree in Computer Science from Utrecht University in 1999. His main research contributions have been in the field of program language design and implementation, program analysis and transformation, and functional programming. He supervised 4 (FCT funded) PostDoc projects, 8 PhD projects (5 awarded and 3 running) and over 30 (Pos-Bologna) MSc thesis. He has published over 80 publications (scopus) in conferences and journals. He has served in over 60 program committees of international events, and in the evaluation committees of 5 research agencies: ANII (Uruguay), FRS-FNRS (Belgium), NWO (The Netherlands), FWF (Austria), and FCT (Portugal).

He has experience in participating and coordinating research projects in his research areas, both at national level with projects funded by FCT (projects: PURe, IVY, AMADEUS, CROSS, SSaaPP, AutoSeer, FATBIT, and GreenSwLab) and at international level with projects funded by EPSRC (UK), FLAD/NSF (USA) and by the European Union.

João Saraiva is one of the founders of the successful series of summer schools on Generative and Transformational Techniques in Software Engineering (GTTSE), which he co-organized in 2005, 2007, 2009, 2011, and 2015 (volumes 4143, 5235, 6491, and 7680 of LNCS - Tutorial by Springer-Verlag) in Braga. He was the organizing chair of ETAPS'07, The European Joint Conferences on Theory and Practice of Software, organized in Braga in 2007, and a member of its scientific committee (2007-2012).

Interest
Topics
Details

Details

  • Name

    João Alexandre Saraiva
  • Cluster

    Computer Science
  • Role

    Senior Researcher
  • Since

    01st November 2011
001
Publications

2021

Ranking programming languages by energy efficiency

Authors
Pereira, R; Couto, M; Ribeiro, F; Rua, R; Cunha, J; Fernandes, JP; Saraiva, J;

Publication
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. © 2021 Elsevier B.V.

2020

SPELLing out energy leaks: Aiding developers locate energy inefficient code

Authors
Pereira, R; Carcao, T; Couto, M; Cunha, J; Fernandes, JP; Saraiva, J;

Publication
Journal of Systems and Software

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. © 2019 Elsevier Inc.

2020

Energy Refactorings for Android in the Large and in the Wild

Authors
Couto, M; Saraiva, J; Fernandes, JP;

Publication
2020 IEEE 27th International Conference on Software Analysis, Evolution and Reengineering (SANER)

Abstract

2020

Expressing disambiguation filters as combinators

Authors
Macedo, JN; Saraiva, J;

Publication
SAC '20: The 35th ACM/SIGAPP Symposium on Applied Computing, online event, [Brno, Czech Republic], March 30 - April 3, 2020

Abstract

2020

Unifying Parsing and Reflective Printing for Fully Disambiguated Grammars

Authors
Zhu, ZR; Ko, HS; Zhang, YZ; Martins, P; Saraiva, J; Hu, ZJ;

Publication
NEW GENERATION COMPUTING

Abstract
Language designers usually need to implement parsers and printers. Despite being two closely related programs, in practice they are often designed separately, and then need to be revised and kept consistent as the language evolves. It will be more convenient if the parser and printer can be unified and developed in a single program, with their consistency guaranteed automatically. Furthermore, in certain scenarios (like showing compiler optimisation results to the programmer), it is desirable to have a more powerful reflective printer that, when an abstract syntax tree corresponding to a piece of program text is modified, can propagate the modification to the program text while preserving layouts, comments, and syntactic sugar. To address these needs, we propose a domain-specific language BiYacc, whose programs denote both a parser and a reflective printer for a fully disambiguated context-free grammar. BiYacc is based on the theory of bidirectional transformations, which helps to guarantee by construction that the generated pairs of parsers and reflective printers are consistent. Handling grammatical ambiguity is particularly challenging: we propose an approach based on generalised parsing and disambiguation filters, which produce all the parse results and (try to) select the only correct one in the parsing direction; the filters are carefully bidirectionalised so that they also work in the printing direction and do not break the consistency between the parsers and reflective printers. We show that BiYacc is capable of facilitating many tasks such as Pombrio and Krishnamurthi's 'resugaring', simple refactoring, and language evolution.

Supervised
thesis

2020

Green Software in the Large: Energy-driven Techniques, Tools and Repositories

Author
Rui António Ramada Rua

Institution
UP-FCUP

2020

Explaining Software Faults in Source Code

Author
Francisco José Torres Ribeiro

Institution
UP-FCUP

2020

Automatic generation of program executions

Author
José Nuno Castro de Macedo

Institution
UP-FCUP

2020

Energy-aware Software Product Lines

Author
Marco Rafael Linhares Couto

Institution
UM

2020

Energy Debt - Applying Technical Debt to Energy Consumption

Author
Daniel Fernandes Veiga Maia

Institution
UM