Avaliação da contribuição de desenvolvedores para projetos de software usando mineração de repositórios de software e mineração de processos

Software Repository Mining (MSR) is a research area that analyses software repositories in order to derive relevant information for the research and practice of software engineering. The main goal of repository mining is to extract static information from repositories (e.g. code repository or change requisition system) into valuable information providing a way to support the decision making of software projects. On the other hand, another research area called Process Mining (PM) aims to find the characteristics of the underlying process of business organizations, supporting the process improvement and documentation. Recent works have been doing several analyses through MSR and PM techniques: (i) to investigate the evolution of software projects; (ii) to understand the real underlying process of a project; and (iii) create defect prediction models. However, few research works have been focusing on analyzing the contributions of software developers by means of MSR and PM techniques. In this context, this dissertation proposes the development of two empirical studies of assessment of the contribution of software developers to an open-source and a commercial project using those techniques. The contributions of developers are assessed through three different perspectives: (i) buggy commits; (ii) the size of commits; and (iii) the most important bugs. For the opensource project 12.827 commits and 8.410 bugs have been analyzed while 4.663 commits and 1.898 bugs have been analyzed for the commercial project. Our results indicate that, for the open source project, the developers classified as core developers have contributed with more buggy commits (although they have contributed with the majority of commits), more code to the project (commit size) and more important bugs solved while the results could not indicate differences with statistical significance between developer groups for the commercial project

Uma ferramenta de análise automatizada de técnicas de seleção de testes de regressão baseada em mineração de repositórios de software

The main goal of Regression Test (RT) is to reuse the test suite of the latest version of a software in its current version, in order to maximize the value of the tests already developed and ensure that old features continue working after the new changes. Even with reuse, it is common that not all tests need to be executed again. Because of that, it is encouraged to use Regression Tests Selection (RTS) techniques, which aims to select from all tests, only those that reveal faults, this reduces costs and makes this an interesting practice for the testing teams. Several recent research works evaluate the quality of the selections performed by RTS techniques, identifying which one presents the best results, measured by metrics such as inclusion and precision. The RTS techniques should seek in the System Under Test (SUT) for tests that reveal faults. However, because this is a problem without a viable solution, they alternatively seek for tests that reveal changes, where faults may occur. Nevertheless, these changes may modify the execution flow of the algorithm itself, leading some tests no longer exercise the same stretch. In this context, this dissertation investigates whether changes performed in a SUT would affect the quality of the selection of tests performed by an RTS, if so, which features the changes present which cause errors, leading the RTS to include or exclude tests wrongly. For this purpose, a tool was developed using the Java language to automate the measurement of inclusion and precision averages achieved by a regression test selection technique for a particular feature of change. In order to validate this tool, an empirical study was conducted to evaluate the RTS technique Pythia, based on textual differencing, on a large web information system, analyzing the feature of types of tasks performed to evolve the SUT

Uma abordagem para evolução e reconciliação de linhas de produtos de software clonadas

Software product line engineering promotes large software reuse by developing a system family that shares a set of developed core features, and enables the selection and customization of a set of variabilities that distinguish each software product family from the others. In order to address the time-to-market, the software industry has been using the clone-and-own technique to create and manage new software products or product lines. Despite its advantages, the clone-and-own approach brings several difficulties for the evolution and reconciliation of the software product lines, especially because of the code conflicts generated by the simultaneous evolution of the original software product line, called Source, and its cloned products, called Target. This thesis proposes an approach to evolve and reconcile cloned products based on mining software repositories and code conflict analysis techniques. The approach provides support to the identification of different kinds of code conflicts – lexical, structural and semantics – that can occur during development task integration – bug correction, enhancements and new use cases – from the original evolved software product line to the cloned product line. We have also conducted an empirical study of characterization of the code conflicts produced during the evolution and merging of two large-scale web information system product lines. The results of our study demonstrate the approach potential to automatically or semi-automatically solve several existing code conflicts thus contributing to reduce the complexity and costs of the reconciliation of cloned software product lines.

Uma proposta de indicadores para o acompanhamento de alunos em projetos de desenvolvimento colaborativo de software com foco no desenvolvimento de habilidades transversais

Soft skills and teamwork practices were identi ed as the main de ciencies of recent graduates in computer courses. This issue led to a realization of a qualitative research aimed at investigating the challenges faced by professors of those courses in conducting, monitoring and assessing collaborative software development projects. Di erent challenges were reported by teachers, including di culties in the assessment of students both in the collective and individual levels. In this context, a quantitative research was conducted with the aim to map soft skill of students to a set of indicators that can be extracted from software repositories using data mining techniques. These indicators are aimed at measuring soft skills, such as teamwork, leadership, problem solving and the pace of communication. Then, a peer assessment approach was applied in a collaborative software development course of the software engineering major at the Federal University of Rio Grande do Norte (UFRN). This research presents a correlation study between the students' soft skills scores and indicators based on mining software repositories. This study contributes: (i) in the presentation of professors' perception of the di culties and opportunities for improving management and monitoring practices in collaborative software development projects; (ii) in investigating relationships between soft skills and activities performed by students using software repositories; (iii) in encouraging the development of soft skills and the use of software repositories among software engineering students; (iv) in contributing to the state of the art of three important areas of software engineering, namely software engineering education, educational data mining and human aspects of software engineering.

Uma proposta de indicadores para o acompanhamento de alunos em projetos de desenvolvimento colaborativo de software com foco no desenvolvimento de habilidades transversais

Soft skills and teamwork practices were identi ed as the main de ciencies of recent graduates in computer courses. This issue led to a realization of a qualitative research aimed at investigating the challenges faced by professors of those courses in conducting, monitoring and assessing collaborative software development projects. Di erent challenges were reported by teachers, including di culties in the assessment of students both in the collective and individual levels. In this context, a quantitative research was conducted with the aim to map soft skill of students to a set of indicators that can be extracted from software repositories using data mining techniques. These indicators are aimed at measuring soft skills, such as teamwork, leadership, problem solving and the pace of communication. Then, a peer assessment approach was applied in a collaborative software development course of the software engineering major at the Federal University of Rio Grande do Norte (UFRN). This research presents a correlation study between the students' soft skills scores and indicators based on mining software repositories. This study contributes: (i) in the presentation of professors' perception of the di culties and opportunities for improving management and monitoring practices in collaborative software development projects; (ii) in investigating relationships between soft skills and activities performed by students using software repositories; (iii) in encouraging the development of soft skills and the use of software repositories among software engineering students; (iv) in contributing to the state of the art of three important areas of software engineering, namely software engineering education, educational data mining and human aspects of software engineering.

X-ARM: um modelo de representação de artefatos de software

A great challenge of the Component Based Development is the creation of mechanisms to facilitate the finding of reusable assets that fulfill the requirements of a particular system under development. In this sense, some component repositories have been proposed in order to answer such a need. However, repositories need to represent the asset characteristics that can be taken into account by the consumers when choosing the more adequate assets for their needs. In such a context, the literature presents some models proposed to describe the asset characteristics, such as identification, classification, non-functional requirements, usage and deployment information and component interfaces. Nevertheless, the set of characteristics represented by those models is insufficient to describe information used before, during and after the asset acquisition. This information refers to negotiation, certification, change history, adopted development process, events, exceptions and so on. In order to overcome this gap, this work proposes an XML-based model to represent several characteristics, of different asset types, that may be employed in the component-based development. Besides representing metadata used by consumers, useful for asset discovering, acquisition and usage, this model, called X-ARM, also focus on helping asset developers activities. Since the proposed model represents an expressive amount of information, this work also presents a tool called X-Packager, developed with the goal of helping asset description with X-ARM