Change impact analysis techniques that underestimate impact may cause important financial losses from the point of view of an IT services company. Thus, reducing falsenegatives in these techniques is a goal with strong practical relevance. This work presents a technique that uses both static and dynamic analysis of object-oriented source code to improve resulting impact estimates in terms of recall. The technique consists of three steps: static analysis to identify structural dependencies between code entities, dynamic analysis to identify dependencies based on a succession relation derived from execution traces, and a ranking of results from both analyses that takes into account the relevance of dynamic dependencies. Evaluation was performed through prototype development and a multiple-case quantitative case study that compared our solution against a static technique and a dynamic one. Results showed that our hybrid technique improved recall between 90 and 115% compared to the static technique, and between 21.2 and 39% compared to the dynamic one.

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Student engagement is a key indicator of student academic success, especially in the online environment, where students can study anywhere, anytime. In this paper, we analyze track records of the novice programmers' interaction with an online learning environment. The results show indicators of poor and good engagement and can guide teachers in choosing the most appropriate teaching strategy according to the needs of each individual.Resumo. O envolvimento do aluno é um indicador fundamental para o sucesso acadêmico do aluno, principalmente no ambiente on-line, onde os alunos podem estudar em qualquer lugar e a qualquer momento. Neste trabalho, analisamos registros da interação do aluno iniciante em programação com um ambiente de aprendizado on-line. Os resultados apresentam indicadores de fraco e bom engajamento, e podem guiar os professores na escolha de estratégia de ensino mais adequadas de acordo com a necessidade de cada indíviduo.

Contributing Student Pedagogy is an active method that encourages students to contribute to community learning and to value the contributions of others. Activities based on contribution guide students to produce study material and create new exercises for community usage and discuss and evaluate the contribution of others. The creation of new learning exercises can positively influence students' academic performance. This article presents an experimental study to assess how new exercises' creation influences student engagement in programming learning activities. Considering student engagement involves behavior, cognition, and emotion dimensions, this study examined which of these are affected when the student contributes to the community's learning through the production of new programming exercises. Results indicate that the development of this activity improves emotional and cognitive engagement and does not influence behavior. Contributing students reported developing more difficult learning exercises and felt more stimulated, satisfied, and happy. In contrast, those who did not contribute to the community said that their contributions were easier and felt more ashamed and proud.