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Detalhes

Detalhes

  • Nome

    Jácome Costa Cunha
  • Cluster

    Informática
  • Cargo

    Investigador
  • Desde

    01 novembro 2011
Publicações

2023

A methodology for refactoring ORM-based monolithic web applications into microservices

Autores
Freitas, F; Ferreira, A; Cunha, J;

Publicação
JOURNAL OF COMPUTER LANGUAGES

Abstract
In the last few years we have been seeing a drastic change in the way software is developed. Large-scale software projects are being assembled by a flexible composition of many (small) components possibly written in different programming languages and deployed anywhere in the cloud - the so-called microservices-based applications. The dramatic growth in popularity of microservices-based applications has pushed several companies to apply major refactorings to their software systems. However, this is a challenging task that may take several months or even years. We propose a methodology to automatically evolve monolithic web applications that use object-relational mapping into microservices-based ones. Our methodology receives the source code and a microservices proposal and refactors the original code to create each microservice. Our methodology creates an API for each method call to classes that are in other services. The database entities are also refactored to be included in the corresponding service. The evaluation performed in 120 applications shows that our tool can successfully refactor about 72% of them. The execution of the unit tests in both versions of the applications yield exactly the same results.

2022

Which Technologies are Most Frequently Used by Data Scientists?

Autores
Pereira, P; Fernandes, JP; Cunha, J;

Publicação
Proceedings of IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC

Abstract
Data collection is pervasively bound to our digital lifestyle. A recent study reports that the growth of the data created and replicated in 2020 was even higher than in the previous years to an astonishing global amount of 64.2 zettabytes of data. There are numerous companies whose services/products rely heavily on data analysis, and mining the produced data has already revealed great value for businesses in different sectors. In order to be able to support the professionals that do this job, typically known as data scientists, we first need to characterize them. To contribute towards this characterization, we conducted a public survey and in this work we present the results about a particular aspects of their life: the tools they use and need. © 2022 IEEE Computer Society. All rights reserved.

2022

Energy Efficiency of Web Browsers in the Android Ecosystem

Autores
Gonçalves, N; Rua, R; Cunha, J; Pereira, R; Saraiva, J;

Publicação
CoRR

Abstract

2021

Ranking programming languages by energy efficiency

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.

2021

Identification of microservices from monolithic applications through topic modelling

Autores
Brito, M; Cunha, J; Saraiva, J;

Publicação
SAC '21: The 36th ACM/SIGAPP Symposium on Applied Computing, Virtual Event, Republic of Korea, March 22-26, 2021

Abstract
Microservices emerged as one of the most popular architectural patterns in the recent years given the increased need to scale, grow and flexibilize software projects accompanied by the growth in cloud computing and DevOps. Many software applications are being submitted to a process of migration from its monolithic architecture to a more modular, scalable and flexible architecture of microservices. This process is slow and, depending on the project's complexity, it may take months or even years to complete. This paper proposes a new approach on microservice identification by resorting to topic modelling in order to identify services according to domain terms. This approach in combination with clustering techniques produces a set of services based on the original software. The proposed methodology is implemented as an open-source tool for exploration of monolithic architectures and identification of microservices. A quantitative analysis using the state of the art metrics on independence of functionality and modularity of services was conducted on 200 open-source projects collected from GitHub. Cohesion at message and domain level metrics' showed medians of roughly 0.6. Interfaces per service exhibited a median of 1.5 with a compact interquartile range. Structural and conceptual modularity revealed medians of 0.2 and 0.4 respectively. Our first results are positive demonstrating beneficial identification of services due to overall metrics' results. © 2021 ACM.

Teses
supervisionadas

2022

Model-Driven Engineering for DevOps

Autor
Hugo Afonso da Gião

Instituição
UM

2022

Spectrum-Based Fault Localization for Microservices via Log Analysis

Autor
João Miguel Ribeiro de Castro Silva Martins

Instituição
UP-FEUP

2022

Designing and Building A Microservices-Based Time Series Forecasting System

Autor
João Ruano Neto Veiga de Macedo

Instituição
UP-FEUP

2022

A Generic Scalable Web Platform For XAI Algorithms

Autor
Luís Pedro Viana Ramos

Instituição
UP-FEUP

2022

LPBlocks - A Block-based Language for Linear Programming

Autor
Hugo Afonso da Gião

Instituição
UM