Publications

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 microservice-based applications. The dramatic growth in popularity of microservice-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 a Java monolithic application into a microservice-based one. Our methodology receives the Java code and a proposition of microservices and refactors the original classes to make each microservice independent. 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 initial evaluation shows that our tool can successfully refactor 80% of the applications tested.

Data science has started to become one of the most important skills one can have in the modern world, due to data taking an increasingly meaningful role in our lives. The accessibility of data science is however limited, requiring complicated software or programming knowledge. Both can be challenging and hard to master, even for the simple tasks.

Although hardware is generally seen as the main culprit for a computer's energy usage, software too has a tremendous impact on the energy spent. Unfortunately, there is still not enough support for software developers so they can make their code more energy-aware. This paper proposes a technique to detect energy inefficient fragments in the source code of a software system. Test cases are executed to obtain energy consumption measurements, and a statistical method, based on spectrum-based fault localization, is introduced to relate energy consumption to the source code. The result of our technique is an energy ranking of source code fragments pointing developers to possible energy leaks in their code. This technique was implemented in the SPELL toolkit. Finally, in order to evaluate our technique, we conducted an empirical study where we asked participants to optimize the energy efficiency of a software system using our tool, while also having two other groups using no tool assistance and a profiler, respectively. We showed statistical evidence that developers using our technique were able to improve the energy efficiency by 43% on average, and even out performing a profiler for energy optimization.

Portugal is one of the European countries that implemented early protective measures in the context of the COVID-19 pandemic. Portugal declared a state of emergency on 18 March, and a set of regional and national preventive public health measures was progressively implemented. Studies on the psychological impact of pandemics show evidence of the negative impact on mental health. Of particular concern are individuals with previous fragility (e.g. personal, family or occupational) and those undergoing life transitions. In this paper, we present a telephone-based psychological crisis intervention that was implemented to provide brief, appropriate, and timely psychological help. This intervention follows standard models of crisis intervention and is structured in five phases and five different intervention modules to take into account the impact of the pandemic on the mental health of specific risk groups. With these support services, we hope to help our community better cope with the immediate impact of the pandemic and to contribute to preventing serious mental health problems in the medium and long term.

Functional programmers are strong enthusiasts of modular solutions to programming problems. Since software characteristics such as readability or maintainability are often directly proportional to modularity, this programming style naturally contributes to the beauty of functional programs. Unfortunately, in return of this beauty we often sacrifice efficiency: modular programs rely, at runtime, on the creation, use and elimination of intermediate data structures to connect its components. In this tutorial paper, we study an advanced technique that attempts to retain the best of this two worlds: (i) it allows programmers to implement beautiful, modular programs (ii) it shows how to transform such programs, in a way that can be incorporated in a compiler, into programs that do not construct any intermediate structure.

Energy consumption is becoming an evident concern to software developers. This is even more notorious due to the propagation of mobile devices. Such propagation of devices is also influencing software development: a software system is now developed has a set of similar products sharing common features. In this short paper, we describe our methodology aim at static and accurately predict the energy consumption of software products in such variability systems, typically called software product lines.

This technical report describes the research goals and results of the SpreadSheet as a Programming Paradigm research project. This was a project funded by Funda{\c c}ão para a Ciencia e Tecnologia - FCT: the Portuguese research foundation, under reference FCOMP-01-0124-FEDER-010048, that ran from May 2010 till July 2013. This report includes the complete document reporting the results achieved during the project execution, which was submitted to FCT for evaluation on October 2013. It describes the goals of the project, and the different research tasks presenting the deliver- ables of each of them. It also presents the management and result dissemination work performed during the project{\textquoteright}s execution. The document includes also a self assess- ment of the achieved results, and a complete list of scientific publications describing the contributions of the project. Finally, this document includes the FCT evaluation report.

This paper showcases MDSheet, a framework aimed at improving the engineering of spreadsheets. This framework is model-driven, and has been fully integrated under a spreadsheet system. Also, its practical interest has been demonstrated by several empirical studies.

Spreadsheets can be viewed as programming languages for non-professional programmers. These so-called ``end-user'' programmers vastly outnumber professional programmers creating millions of new spreadsheets every year. As a programming language, spreadsheets lack support for abstraction, testing, encapsulation, or structured programming. As a result, and as numerous studies have shown, the high rate of production is accompanied by an alarming high rate of errors. Some studies report that up to 90% of real-world spreadsheets contain errors. After their initial creation, many spreadsheets turn out to be used for storing and processing increasing amounts of data and supporting increasing numbers of users over long periods of time, making them complicated systems. An emerging solution to handle the complex and evolving software systems is Model-driven Engineering (MDE). To consider models as first class entities and any software artifact as a model or a model element is one of the basic principles of MDE. We adopted some techniques from MDE to solve spreadsheet problems. Most spreadsheets (if not all) lack a proper specification or a model. Using reverse engineering techniques we are able to derive various models from legacy spreadsheets. We use functional dependencies (a formalism that allow us to define how some column values depend on other column values) as building blocks for these models. Models can be used for several spreadsheet improvements, namely refactoring, safe evolution, migration or even generation of edit assistance. The techniques presented in this work are available under the framework HAEXCEL that we developed. It is composed of online and batch tools, reusable HASKELL libraries and OpenOffice.org extensions. A study with several end-users was organized to survey the impact of the techniques we designed. The results of this study indicate that the models can bring great benefits to spreadsheet engineering helping users to commit fewer errors and to work faster.

Spreadsheets can be viewed as programming languages for non-professional programmers. These so-called ``end-user'' programmers vastly outnumber professional programmers creating millions of new spreadsheets every year. As a programming language, spreadsheets lack support for abstraction, testing, encapsulation, or structured programming. As a result, and as numerous studies have shown, the high rate of production is accompanied by an alarming high rate of errors. Some studies report that up to 90% of real-world spreadsheets contain errors. After their initial creation, many spreadsheets turn out to be used for storing and processing increasing amounts of data and supporting increasing numbers of users over long periods of time, making them complicated systems. An emerging solution to handle the complex and evolving software systems is Model-driven Engineering (MDE). To consider models as first class entities and any software artifact as a model or a model element is one of the basic principles of MDE. We adopted some techniques from MDE to solve spreadsheet problems. Most spreadsheets (if not all) lack a proper specification or a model. Using reverse engineering techniques we are able to derive various models from legacy spreadsheets. We use functional dependencies (a formalism that allow us to define how some column values depend on other column values) as building blocks for these models. Models can be used for several spreadsheet improvements, namely refactoring, safe evolution, migration or even generation of edit assistance. The techniques presented in this work are available under the framework HAEXCEL that we developed. It is composed of online and batch tools, reusable HASKELL libraries and OpenOffice.org extensions. A study with several end-users was organized to survey the impact of the techniques we designed. The results of this study indicate that the models can bring great benefits to spreadsheet engineering helping users to commit less errors and to work faster.