no code implementations • 28 Nov 2023 • Luis Fernando Lins, Nathalia Nascimento, Paulo Alencar, Toacy Oliveira, Donald Cowan
Business processes are commonly represented by modelling languages, such as Event-driven Process Chain (EPC), Yet Another Workflow Language (YAWL), and the most popular standard notation for modelling business processes, the Business Process Model and Notation (BPMN).
no code implementations • 23 Nov 2023 • Cristina Tavares, Nathalia Nascimento, Paulo Alencar, Donald Cowan
ML model selection depends on several factors, which include data-related attributes such as sample size, functional requirements such as the prediction algorithm type, and non-functional requirements such as performance and bias.
no code implementations • 20 Nov 2023 • Nathalia Nascimento, Cristina Tavares, Paulo Alencar, Donald Cowan
There is an increasing interest in leveraging Large Language Models (LLMs) for managing structured data and enhancing data science processes.
no code implementations • 21 Aug 2023 • Nathalia Nascimento, Paulo Alencar, Donald Cowan
This paper introduces the "GPT-in-the-loop" approach, a novel method combining the advanced reasoning capabilities of Large Language Models (LLMs) like Generative Pre-trained Transformers (GPT) with multiagent (MAS) systems.
no code implementations • 12 Jul 2023 • Nathalia Nascimento, Paulo Alencar, Donald Cowan
In autonomic computing, self-adaptation has been proposed as a fundamental paradigm to manage the complexity of multiagent systems (MASs).
no code implementations • 19 May 2023 • Nathalia Nascimento, Paulo Alencar, Donald Cowan
The advent of automation in particular Software Engineering (SE) tasks has transitioned from theory to reality.
no code implementations • 15 Feb 2021 • Giuliano Lorenzoni, Paulo Alencar, Nathalia Nascimento, Donald Cowan
Data scientists often develop machine learning models to solve a variety of problems in the industry and academy but not without facing several challenges in terms of Model Development.
no code implementations • 15 Feb 2021 • Nathalia Nascimento, Paulo Alencar, Donald Cowan, Carlos Lucena
In this paper, we propose a reference model based on statecharts that offers abstractions tailored to the development of IoT applications.
no code implementations • 10 Feb 2021 • Glaucia Melo, Paulo Alencar, Donald Cowan
First, as software development is a complex and dynamic activity, these tasks are highly dependent on the characteristics of the software project and its context, and developers need comprehensive support in terms of information and guidance based on the task context.
Recommendation Systems Software Engineering
1 code implementation • 21 Feb 2020 • Shubhankar Mohapatra, Nauman Ahmed, Paulo Alencar
Cryptocurrencies, such as Bitcoin, are becoming increasingly popular, having been widely used as an exchange medium in areas such as financial transaction and asset transfer verification.
no code implementations • 3 Apr 2019 • Nathalia Nascimento, Carlos Lucena, Paulo Alencar, Carlos Juliano Viana
Multiagent Systems (MASs) involve different characteristics, such as autonomy, asynchronous and social features, which make these systems more difficult to understand.
no code implementations • 14 Dec 2018 • Nathalia Nascimento, Paulo Alencar, Carlos Lucena, Donald Cowan
Agent-based Internet of Things (IoT) applications have recently emerged as applications that can involve sensors, wireless devices, machines and software that can exchange data and be accessed remotely.
no code implementations • 12 Feb 2018 • Nathalia Nascimento, Paulo Alencar, Carlos Lucena, Donald Cowan
Agent-based IoT applications have recently been proposed in several domains, such as health care, smart cities and agriculture.
no code implementations • 4 Feb 2018 • Nathalia Nascimento, Carlos Lucena, Paulo Alencar, Donald Cowan
Third, we compared how software engineers fare against machine-learning algorithms when accomplishing the performance and reuse tasks based on criteria such as energy consumption and safety.
no code implementations • 24 Feb 2016 • Ivens Portugal, Paulo Alencar, Donald Cowan
Machine Learning algorithms can be used in Big Data to make better and more accurate inferences.
no code implementations • 17 Nov 2015 • Ivens Portugal, Paulo Alencar, Donald Cowan
This paper presents a systematic review of the literature that analyzes the use of machine learning algorithms in recommender systems and identifies research opportunities for software engineering research.