12 citations · 44 across the 14 of their papers we have counts for
11 papers · 1 filter
Machine Learning Model Development from a Software Engineering Perspective: A Systematic Literature Review
Giuliano Lorenzoni, Paulo Alencar, Nathalia Nascimento +1
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 Develop…
A Cognitive and Machine Learning-Based Software Development Paradigm Supported by Context
Glaucia Melo, Paulo Alencar, Donald Cowan
Advances in the use of cognitive and machine learning (ML) enabled systems fuel the quest for novel approaches and tools to support software developers in executing their tasks. Fi…
Exploring Context-Aware Conversational Agents in Software Development
Glaucia Melo, Edith Law, Paulo Alencar +1
Software development is a complex endeavor that depends on a wide variety of contextual factors involving a large amount of distributed information. This knowledge could include: t…
Context-Augmented Software Development Projects: Literature Review and Preliminary Framework
Glaucia Melo, Paulo Alencar, Don Cowan
Software development is a complex activity which depends on diverse technologies and people's expertise. The approaches to developing software highly depend on these different char…
The Next Generation of Metadata-Oriented Testing of Research Software
Doug Mulholland, Paulo Alencar, Donald Cowan
Research software refers to software development tools that accelerate discovery and simplifies access to digital infrastructures. However, although research software platforms can…
A Variability-Aware Design Approach to the Data Analysis Modeling Process
Maria Cristina Vale Tavares, Paulo Alencar, Donald Cowan
The massive amount of current data has led to many different forms of data analysis processes that aim to explore this data to uncover valuable insights. Methodologies to guide the…
The iEnvironment Platform: Developing an Open Science Software Platform for Integrated Environmental Monitoring and Modeling of Surface Water
Paulo Alencar, Donald Cowan, Doug Mulholland
This paper describes the development of iEnvironment, an open science software platform that supports monitoring and modeling of aspects of surface water. The platform supports sci…
Software Engineers vs. Machine Learning Algorithms: An Empirical Study Assessing Performance and Reuse Tasks
Nathalia Nascimento, Carlos Lucena, Paulo Alencar +1
Several papers have recently contained reports on applying machine learning (ML) to the automation of software engineering (SE) tasks, such as project management, modeling and deve…
A Survey on Domain-Specific Languages for Machine Learning in Big Data
Ivens Portugal, Paulo Alencar, Donald Cowan
The amount of data generated in the modern society is increasing rapidly. New problems and novel approaches of data capture, storage, analysis and visualization are responsible for…
The Use of Machine Learning Algorithms in Recommender Systems: A Systematic Review
Ivens Portugal, Paulo Alencar, Donald Cowan
Recommender systems use algorithms to provide users with product or service recommendations. Recently, these systems have been using machine learning algorithms from the field of a…
Requirements Engineering for General Recommender Systems
Ivens Portugal, Paulo Alencar, Donald Cowan
In requirements engineering for recommender systems, software engineers must identify the data that drives the recommendations. This is a labor-intensive task, which is error-prone…