On this page you can find my current main Research Interests and short descriptions of the main Research Projects in which I am currently involved.
Click on each of the Projects below to see its description.
This project aims to: (i) provide a conceptual framework for sequential refactoring as well as related concepts; (ii) develop a theory that explains how developers perform sequential refactoring in practice; (iii) propose heuristics for automated identification of sequential refactoring existing in a program; (iv) assess the quality impact of sequential refactoring; (v) evaluate and classify sequential refactoring as positive or negative based on their impact on structural degradation symptoms and (vi) propose a recommendation system for sequential refactoring.
Brazilian population has not responded well to the prevention programs to combat arboviral diseases, such as Zika and Dengue. Concerns with such diseases has led an overwhelming number of people to increasingly share online strategic information, including the discovery of mosquito breeding sites in public locations. Term social sensors refers to the online population that is motivated to contribute relevant information on social media channels. Recent increasing use of smartphones triggered the growing use of social networks even in poorer communities. Strategic information in these locations are harder to gather for health agents. The health agencies in Northeast should explore the collective knowledge generated by people to improve prevention and combat actions. Although the Brazilian Health System requires that health agents report each Zika case, it takes several days to process and publish this information. The project will develop a platform for promoting virtual communities to prevent and combat Zika. Its core is the VazaZika application. VazaZika will use geolocation and gamification technologies for stimulating citizens to denounce and confirm Aedes breeding sites, and for updating users, in real time, about actions taken by health agents.
The CARECO project aimed to develop: (i) recommendation systems to support collaborative maintenance of software systems; (ii) methods that support the evaluation of the quality of use of recommendation systems; (iii) new collaboration mechanisms integrated with development environments; (iv) application of advanced artificial intelligence and database techniques to develop recommendation systems that support collaborative maintenance of software systems, and (v) design and evaluation of recommendation systems to support the teaching and learning software maintenance.
Dengue is an endemic problem in many areas where public health services assistance is inefficient, and sometimes it is not even there. The Brazilian public health system cannot meet the demands of these areas due to the scarcity of resources available and the number of risk areas that requires monitoring. To make the matters worse, it is very difficult to identify and control dengue outbreaks in their initial stages. Therefore, it needs to notify focus of dengue mosquito in order to make it easier preventing dengue epidemic and to take the best actions. To assist the surveillance and detection of dengue mosquito and outbreaks, we propose an integrated platform for population to act as an etymological surveillance agent. The goal is to collect and transmit geo-referenced data, providing information to assist in entomological surveillance of dengue. To accomplish the aforementioned goal, we will developer (i) mobile applications to collect data, (ii) a web portal for centralizing data and (iii) we will mining social media to extract data and to monitor dengue outbreaks. The computational solution aims at gathering information on the reporting of the mosquito that transmits dengue. Allowing us to organize it and to plot it on maps. The point is to make it available to the government and the population.