In recent years, one of the major challenges in education has been to predict students’ performance in a certain and reliable way in order to apply different strategies toimprove their academic deficiencies. In this way, there are many works focused on finding Machine Learning (ML) models individually, but few use the knowledge acquired from student data of a course degree to predict the students’ outcome of other curses’s degree. Therefore, the main goal of this work is to analise the portability of ML models by using Transfer Learning (TL) in students’ logs extracted form the Moodle system, aiming to predict undergraduate students performance in different courses. Through the applied experimental methodology, each of the two types of groupings formed by the disciplines
will be evaluated: those formed according to the undergraduate course and those according to the activities used in Moodle. The data extraction of each group will be performed from the Moodle logs, using the following evaluation methods: cross-validation and hold-out. With this, it will be possible to know whether these evaluations, all performed on the predictive models with the J48 algorithm, tend to show different results in relation to the portability of forecasting models. For evaluation, two scenarios were developed for the execution of experiments, so that each experiment consists of two parts: the choice of models, using the AUC ROC index for Experiment 1 and the F-Measure for Experiment 2; and the validation of the models, using the Precision index for Experiment 1 and the Recall for Experiment 2. The results, even in the evaluation phase, allow us to affirm that it is possible to apply transfer learning between models of the same group in some cases.

This work was conceived from experiences in the Public Ministry of Rio Grande do Norte (MPRN) regarding the creation of a platform to organize products open and closed MPRN data. Thus, firstly, a systematic mapping of the literature, in order to seek the best practices related to data publication, as well as existing processes or  methodologies, such as other initiatives developed by other Public Ministries. The results were then analyzed.
After doing the analysis, it was found that there is a need to improvement of data sharing processes by the Public Ministry. Therefore, we are developing a new process to support sharing open and closed data through the MPRN platform in Data. After that, some case studies were carried out in order to verify the usefulness of the process proposed, as well as to identify the difficulties faced, evaluating its general efficiency and if it can really contribute to improving productivity within the Ministry Public of RN.

Automated machine learning (AutoML) is a field of great interest to both industry and academia. AutoML has allowed developers working on machine learning (ML) applications to achieve satisfactory results with little to no ML expertise. More recently, AutoML tools focused on deep learning (DL) models have proven especially useful to applications where domain-specific algorithms are predominant, as in computer vision (CV) tasks. Still, AutoML tools focused on simpler ML pipelines remain an important alternative, since DL models have high computational resource requirements and offer reduced model interpretability.
Among the main AutoML approaches, AutoML based on an algorithm configurator (AC) is commonly used to produce simpler pipelines, whereas neural architecture search (NAS) is used to produce deep learning models. These two approaches also intersect, since an AC can be used as a NAS algorithm.

In this work, we study the application of the irace AC to both these AutoML methods. The irace configurator has been successfully applied to design effective algorithms for optimization problems, but it has not yet been applied to AutoML. Our assessment is performed in two stages. First, we propose an irace-based AutoML tool to produce simple and effective ML pipelines. The tool is dubbed iSklearn, for which we define a configuration space and setup. We demonstrate that iSklearn is able to produce effective ML pipelines using irace as its AC, with comparable performance to more complex ensembles produced by AutoSklearn, an established configuration-based AutoML tool. Moreover, we show the benefits of the configuration space and setup proposed for iSklearn, even when coupled with another AC. In the second part of our work, we assess irace as a NAS algorithm. To do so, we evaluate irace on NAS-Bench-101, a recent NAS benchmark for the CIFAR-10 CV dataset. We benchmark irace not only as to final-quality assessment, but also as to anytime performance through a bi-objective formulation. Results demonstrate that  irace can be used a NAS algorithm, obtaining comparable results to the best NAS algorithms included in NAS-Bench-101 in terms of final quality. However, further work is required to improve its anytime performance in this context. Finally, we discuss other design choices made in the original benchmark, showing how they affect the relative performance of NAS algorithms, and provide guidelines for improving the assessment of NAS algorithms through the use of NAS-Bench-101.

Domain-Driven Design (DDD) is in creasingly adopted as a particular way of modeling systems. Among DDD’s strategic design patterns is the context map, a powerful tool that helps development teams understand the business domain. Context maps are usually created from the analysis of existing systems, initial requirements or based on the experience of the team, which can lead to the construction of domain models that do not reflect the reality of the organization. In this sense, the analysis of business process models is presented as an alternative to extract domain information and create context maps, since these models capture the logic of organizations’ operations, providing a comprehensive and high-level view of the business. However, approaches for creating context maps from domain knowledge extracted from business process models are lacking. Thus, this research aims to propose the BPM2DDD technique, an approach to support the identification of information domains and the creation of context maps, which can be used in the stages of analysis and modeling of systems, even serving as an alternative for identifying possible software services. The technique allows the identification of domains, subdomains and limited contexts, based on the analysis of BPMN (Business Process Model and Notation) models. The technique was developed and applied in real business processes of the Urban Mobility Secretariat of the city of Natal (STTU), using the action research methodology, during the years 2019 and 2020, in the context of the development of new urban mobility systems. To evaluate the technique, multiple applications were carried out by business and systems analysts, using one of the STTU business processes, in addition to validations by the domain experts of the generated context map. The results indicate that the techniqueis applicable to software processes adopted by the industry, allowing the discovery of information that enables the creation of a context map more aligned to the organization’s domain.

One of the main research fields under Artificial Intelligence, on the context of Digital Games, is the study of Real-Time Strategy Games (RTS), which are commonly considered the successors of classic strategy games such as Checkers, Chess, Backgammon and Go, and impose great challenges to this area’s researchers due to the great complexity involved. Currently, the field aims to study the RTS using StarCraft I and II as stage of experimentation. The main feature sought in artificial agents developed to this kind of game is high performance, having as its main objective to defeat specialist human players. On this context it is inserted the generalization problematic, that is the capacity of an artificial agent of reusing previous experiences, from different contexts, to a new environment. Generalization is a very studied field by the scientific community, but still poorly explored on the context of RTS. By this reason, this work proposes the Beyond Star model, which consists in an architecture to generically represent the state-space of Real-Time Strategy Games, using as base deep reinforcement learning techniques aiming to learn effective strategies to be applied in several RTS environments. As a basis to the architecture, it was developed a platform titled URNAI, a tool that integrates several learning algorithms and environments, such as StarCraft II and DeepRTS. To analyse if the solution is capable of allowing agent generalization, trainings were done in DeepRTS and tests were carried out in StarCraft II. It was verified that the trained agents were capable of generalizing their knowledge from one environment to the other, showing a promising result that allowed to validate this work’s proposal.

The Internet of Things is booming and more and more devices are connected, generating massive amounts of data. Usually this large amount of data is not used to discover additional information. This is also a reality in healthcare, where large amounts of data can already be generated from devices that use open protocols or connected open source hardware sensors, such as environment sensors or human body sensors. This dissertation aims to propose an intelligence module that can, obtaining data from IoT sensors in health, return categorization and prognostic information of medical complications, thus bringing direct benefits to the patient's health as well as streamlining the patient's health. hospital care and cost reduction.

The food and restaurant sector are segments that are facing challenges to adapt to a new reality that requires less food waste, quality food and efficient management. Consumers in rich countries are estimated to waste around 222 million tonnes of food products and most of them are from restaurants. In Brazil, ANVISA requires restaurants to be monitored by nutritionists, one of whose tasks is to control the temperature of food preservation to verify compliance with its resolutions. In order for restaurants to avoid both food waste and working within these regulatory standards, efficient management is needed to optimize internal processes and make more accurate decisions. Therefore, the objective of this work is to create a smart platform for monitoring the quantity and temperature of a self-service restaurant buffet in order to minimize food waste, improve the handling of nutritional information and optimize its management. The system will be able to check the temperature consumption of food exposed in tanks of a buffet and that the data will be sent to restaurant sectors like cooking, nutrition and management in real time. The system will be created using the concepts and features of the Internet of Things (IoT), Big Data and Web Programming in JavaScript. Finally, software like Node-red, ThingSpeak, Arduino IDE among other tools will compose the framework of technologies used to develop this platform.

Software quality has become a key factor in the software development process today. To be able to measure the quality of different types of tests is today an important challenge to be met. The research conducted in this study considered the evaluation of the effectiveness of systems tests performed by MOPA Embedded Systems in the use of Ginga middleware for Digital TV. To perform the system test suite evaluation performed by the company, it was proposed a methodology to evaluate it through the code coverage criterion, followed by an exploratory study to investigate possible reasons for the results obtained from the coverage. Finally, exploratory tests were conducted to confirm the findings from the exploratory study phase. Through these steps, it was possible to establish an opinion on the quality of the tests performed, as well as the automation performed by the company.

This work will present an interface for non-invasive adaptation of Virtual Reality input
devices, for use with desktop platform games incompatible with such devices, with a focus
on games for rehabilitation, since the Universidade Federal do Rio Grande do Norte has a
ongoing research on application and development of new controller devices for therapeutic
games. In addition to being a tool for adapting joysticks, it will also contain a module for
therapy, this module besides collecting information can help the patient to correct the
movements performed, artifice useful when therapy is performed at home, away from the
therapist’s supervision.

For a variety of reasons, when there is a monitoring system that allows analyzing and correlating data so that relevant information can be extracted, even the smallest problem can be detected and corrected efficiently, reducing downtime.Thus, effective monitoring helps applications and services be available as long as possible. This work specifies the design and development of a monitoring system for software and hardware components for IoT based platforms.The hypothesis describes the proposed monitoring system will help to maintain the guarantee of the availability and reliability of IoT based platform components.

Increasingly, companies have cherished well-being, motivation and satisfaction of their employees since they are the most valuable resource of organization. Motivated employees tend to produce with more quality and productivity, helping to solve problems with better performance. When companies acts successfully to positively influence motivation and better work environment, receives in exchange not just greater engagement but also makes a good external marketing to attract new talents, being seen by external community as a company where “many others want to work”. To make this possible, it is necessary recognize and provide a feedback to employees on their performance. Depending on hierarchical complexity and quantity of employees and diversity of company positions, evaluate their performance may represent a big challenge, being necessary the use of many resources to make it happens in acceptable time. This work presents software that provide a performance feedback to the teams of a company by use of performance indicators, in addition to implement a public recognition model of employees in a view of good attitudes. To measure the impact of the software utilization, a study will be conducted before and after use this software, to measure their influence on the motivation of members of development teams and what the variation of satisfaction of them within the work environment.

Information systems have become increasingly robust, working with high volumes of data, objects and data processes. In the context of the Federal Institute of Rio Grande do Norte (IFRN), a system was developed to attend all the administrative and academic activities of the institution: SUAP, Unified System of Public Administration. Over the course of 11 years, the application has evolved from just one module to over 40, in addition to the dizzying growth of users -- which today permeates the number of 35 thousand. These aspects often impact directly and negatively on systems performance, leading software architects to seek alternatives to better scale their applications. In the case of the IFRN, even after high investments in infrastructure, SUAP performance problems persist. In order to make better use of the available hardware structure, it is necessary to understand the reasons for these performance problems, so that these computational resources are used dynamically and incrementally, managed more efficiently and able to withstand surplus loads without prejudice to application stability. Thus, the need to evaluate more comprehensive aspects of the current architecture of the application is presented, so that elements that impair its performance can be known. This work aims to perform a systematized analysis of the SUAP performance through the application of the Architecture Trade-off Analysis Method (ATAM). Based on the analysis performed, a set of load tests were identified that allow the identification of its main points of slowness. With this, it is hoped to contribute to the definition of a strategy for tests of performance in the SUAP that can be incorporated by the development team. 

The software architecture represents a set of design decisions, often taken before implementing the system, with the goal of achieving desired levels of software quality attributes. An architectural pattern provides a set of specific design decisions applicable to recurrent design problems. Violating these decisions may not only hinder quality attributes, but it may also lead to architectural degradation. The Model-Template-View (MTV) pattern implemented by the Django framework has a set of decisions that promote low coupling and rigorous separation between the parts of an application. However, during the evoution of an applicatoin, design decision may be violated. This way, we investiigate the detection of design problems related to the MTV pattern with the goal of aiding the prevention of architectural degradation in MTV applications. The main contributions of this work are the elaboration of a catalogue of MTV-specific design problems e the implementation of tool for statically detecting these violations. The catalogue and the tool were validated in the context of the Sistema Unificado de Administração Pública (SUAP) developed and maintained by the Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Norte – IFRN.

Since the dawn of civilization, humans beings had always been fascinated by games, because they are fun and a great way to pass time. In recent decades, digital games became popular among young people in school age. Among the digital game styles available on the market today, the RPG (Role-playing game) has attracted attention, since its titles are several years in the bestseller list. This is due various features available, such as character customization and progression, interaction with the new and fictional world and problem solving in this world. In this scenario, we find the concept of quest, which are missions given to the player that must be accomplished for the conclusion of the game or to evolute the narrative. In an effort to facilitate the quest produce process, this work propose a methodology called Quest Design Canvas, which allows for faster production, with well defined creative process steps, with the purpose of, finally, obtain a  narrative line inserted within a set of missions within a mental map. So, it is intended to reach all the goals to be achieved with a digital game, even being educational, introspective or promotional. As validation, This methodology will be used to produce quests for the massive and multiplayer online RPG game (MMORPG) UFRN - The Video game.

The methodology based on competence aims at training of workers with a focus on skills to perform tasks related to their occupation in the labor market. But this new proposal brought challenges pedagogical and teaching teams, the act of planning has been an arduous task, considering so many processes and information that teachers need to understand and develop. Because of this, this paper proposes a solution through a software tool that minimizes the problems faced and provide resources to facilitate the understanding of the methodology. For it was developed an exploratory research with the goal of finding difficulties patterns through online forms and focus group were collected, with teachers from schools of SENAI-DR / RN, relevant data to formulate a proposed solution. The proposed application is currently under development.

The Learning Objects (LO) are importants modular and reusable resources to Distance Education thatt composes the Learning Management Systems (LMS), building a tool kit that can be used for teachers in their learning project and a course’s activity fluxs.The LOs can ber hosted directly into LMS or stored into Learning Objects Repositories (LOR), that are suitable to host them in centered form, describing their details using metadata and with eficient search engine for find the requested object. The stored objects in the LOR can be accessed and used in severals LMSs that include them, increasing the resource available variety to mount a course whith their evaluative activities. This dissertation aproachs the proposal of architecture for integration of the Distance Education Secretary’s (DES) LOR of Federal University of Rio Grande do Norte with LMS Moodle using tha LTI especification developed by IMS Global Leaning Consortion.

The border firewall exercises a fundamental role for corporate network security, acting as the first defense barrier delimiting a secure perimeter. However, the culture of Bring Your Own Device weakens the notion of secure domain, contributing to the creation of attack vectors inside the secure perimeter. Distributed firewall systems emerged with the proposal of protecting individual hosts against attacks originating from inside the network. In such systems, firewall rules are created centrally, then distributed and enforced on all servers that compose the firewall, restricting which services should be available. Meanwhile, software vulnerabilities can make network services vulnerable to attacks, since firewalls usually do not scan application protocols. In this sense, from the discovery of a vulnerability until the publication and application of patches there is an exposure window that must be reduced. Given this scenario, the present work presents a proposal of a self-adaptive distributed firewall system. This proposal is based on monitoring hosts and using a vulnerability assessment system to detect vulnerable services, integrated with components capable of deciding and applying firewall rules on affected hosts. In this way, our approach is able to respond to vulnerabilities discovered in these hosts, helping to mitigate the risk of exploiting the vulnerability. Our system was evaluated in the context of a case study that simulates a corporate network environment, where the results achieved demonstrate its viability.

A software product line (SPL) represents a family of related systems that share commonalities and variabilities to meet the needs of a specific market or mission. The adoption of SPL has been applied in several areas in the software industry due to the benefits achieved, such as reduction of development costs, quality improvement and reduction of time to market. However, distinct scenarios can be found when developing a SPL, which lead to 3 approaches for adopting a SPL: (1) proactive approach: there areno software being developed and a SPLis developed from scratch; (2) reactive approach: there is a SPL which is evolved to address new features and products; (3) extractive approach: SPL is developed from the assets of a system or a set of related systems that are already in production. In the context of the extractive and reactive approaches, this dissertation aims to define a method to develop a SPL from existing systems implemented in the Java language. A practical study that extracts and evolves a SPL of the domain of space allocation management is used as a background to define the method.  

The necessity of software evolution for those which solve daily problems became even more frequent and the software engineering had to be adapted in order to be able to delivery products with good quality in tight dead lines. In order to the software continues being useful during its life cycle, to the main purpose whose was developed, its necessary to apply changes or include new features due to changes which happens in the business.

Rewrite the same block of code is not a recommended approach on software development, because it spreads code in a distributed and disordered way. Applying the code reuse, the same block of code already wrote is referenced by different use cases through the dependency chain and method calls, where different parts of the code, which are being relate to differents funcionalitys, going to depend to the same component. Changes applyed to a block of code which has direct or indirect relation with differents use cases may lead to umpredictable fails, depending on the number of different artifacts related and the extension of dependency chain related to the artifact which was modified, this change may cause a impact on another use case which, by a first look, does not have any relation which the modified block of code. Predict impacts from in a specific artifact is a task which demands time to analysis, deep knowledge of the source-code and test effort.

This paper presents an approach to automatize the identification of possible indirect conflicts using the developed tool, whose can determinate which use cases are more defect prone by source-code changes, providing a more effective direction to the test's efforts. A Study Case was elaborated, assessing a real project of extensive dimension whose doesn't have a automatized test case suite, and the developed tool was able to identify the indirect conflicts on differents cenarios and besides, the tool was able to proof in a empiric experiment which the major failures, caused by indirect conflicts could be avoided if the tool were be used during the development fase.

Para alunos que ingressam no primeiro ano de um curso técnico integrado, a matemática é uma das disciplinas de difícil entendimento. Fatores como falta de atenção, problemas com interpretação de texto e problemas no aprendizado no ensino fundamental, colaboram com as reprovações na disciplina, gerando um aumento no desestímulo do aluno no curso. Com base em relatos dos professores da disciplina de matemática feitos ao setor pedagógico da escola sobre as dificuldades desses alunos em resolver as atividades trabalhadas em sala de aula e após a realização de entrevistas com um grupo de alunos, os referidos fatores de dificuldade foram identificados e possíveis soluções foram traçadas. Uma delas é a implementação de um jogo digital, a ser trabalhado no ambiente escolar, que proporcione o exercício da matemática fundamental, como forma de trabalhar aspectos cognitivos e o conhecimento dos conteúdos da disciplina, gerando dados sobre o desempenho do jogador, proporcionando um feedback ao professor sobre dificuldades e/ou facilidades na resolução das questões. Este trabalho apresenta a proposta de jogo concebida.

In general, laboratories or labs are workplaces that provide controlled conditions for experiments and measurements to be performed. For this reason, controlling temperature and humidity is an important requirement that needs to be achieved in order to guarantee the reproducibility of processes carried out in labs.

Aiming to propose efficient environmental controlling mechanisms, specifically for chemical analysis laboratories, we present in this work an intelligent environmental control system based on sensors network and pattern recognition. Our prototype uses its own data generated by sensors distributed in the environment to identify a pattern of behavior. Through the use of machine learning algorithms, the system identifies the classes within the data (clustering), does the training and testing procedures (classification), so that it can generalize what was learned. Finally, the rules are created in association with previously identified classes in order to control air conditioners, both the main and the spare ones, plus the dehumidifier. In this sense, the prototype keeps temperature and humidity stable and in an effective way.

Quality and time are important factors in software development process, because  we  expect  to  deliver  a  high  quality  product  with  acceptable  cost  and deadline. These factors are even more relevant to innovative environments and small businesses, like a startup. Many companies still don’t carry out activities to improve quality of use of software they had developed. Lack of knowledge of HCI evaluation  methods  and  expectation  of  large  increase  in  coast  and  deadlines have been arguments to maintain the current culture in some companies. This work compares three HCI  evaluation methods well known in literature: heuristic evaluation, communicability evaluation and usability testing. We investigate how they  contribute  to  designer’s  work  during  conception  of  their  interaction  and user interface solution. We compared the activities, time of execution, used materials, profile and number of involved evaluators and users, results and difficulties of evaluators during the execution of methods. This comparison was made by a designer as part of SoftUrbano’s juridical system for smartphone. The results can better inform professionals about the HCI evaluation practice and contribute to changing the software development culture in many companies, especially small businesses and startups.

Regardless of the area of operation and due to business needs, given
the pace of innovation, public and private organizations are
constantly adapting to technological changes, either with the best
market practices or upgrading their technologies. These frequent
changes often end up creating in the company a very heterogeneous
environment, where the systems involved in the business were developed
using various platforms (for example, programming language and / or
database) operate in an isolated way. In situations like this, the
company needs to adopt strategies to provide interoperability between
their systems and thus ensure a good communication, aiming to promote
the exchange of information between departments and the integration of
business rules. The main objective of this work was to propose and
develop strategies enabling the integration of systems in these
heterogeneous environments, regardless of platform and development
language of the systems. In order to solve the current communication
problems and performance between different information systems in the
Department of Distance Education (SEDIS) of the Federal University of
Rio Grande do Norte (UFRN), it was developed a so-called middleware
INTEGRA designed on a service-oriented architecture. The proposal It
was created for the SEDIS, but can be extended to other public
institutions of higher education. One of the advantages of the
architecture proposed is to provide the addition of new systems
without causing a severe impacts of adjustments and changes, ensuring
general maintainability of the software. The middleware creates
communication between different help desk systems and issue tracking
offering a range of services through a communication protocol that
standardizes the exchange and routing of messages. Through the
proposed strategy as showed in the poc, it was possible to get a
balance between the principle of decoupling and the principle of
uniformly distributing responsibility, thus guaranteeing a low
coupling and high cohesion, desirable principles in Software
Engineering.

Usually, the software architect responsible for the software architecture definition and evaluation cannot rank which non-functional requirements must be prioritized during the development of their systems. Because of that, failures may happen during the system execution requiring more time and resources to fix it. In many cases, due to the inexperience of architects or the need for rapid deployment of a system, the non-functional requirements are not considered in the software architecture definition phase and the its documentation is absent or incomplete, making the software architecture difficult to be accessed and understood by others team members and also more difficult the maintenance of its components/modules and relationships. This work raises with public and private software companies which are their main strategies used to define software architecture in terms of its documentation and to ensure it is suitable for non-functional requirements of interest. Our study had the participation of 17 software architects to answer the survey. With the completion of the survey we identified that the non-functional requirements for performance and reliability are the most important to be addressed by the architecture and even with the existence of some approaches to evaluation architectures, they do not seem to be well disseminated and / or used among architects. Besides that, we propose a guide to help software architects in the task of achieving such non-functional requirements during the evolution of software systems. The proposed guide prioritizes the non-functional requirement of performance.

This work presents a tool composed by a domain-specific language used to describe textually performance tests, and by a component that uses those described tests to generate projects in different performance test execution platforms. The purpose is to use concepts defined in the language to abstract the concepts of each platform, which are often modeled differently (regarding nomenclature and/or structure) and even dependent on the tool rather than just the domain. The proposed tool supports SOAP, REST and web applications performance tests to JMeter and Silk Performer. It also allows extension to new test types and target platforms. Studies has been made to evaluate the tool’s usage: tests from a company were rewritten with the DSL and then projects were generated on the target platforms, to be executed. This study also served to help in the development of the tool. It was possible to observe the feasibility of using the DSL to different application types, customizing it according to concepts and characterists of platforms and organizations.