Background: Software project management activities help to introducing software process models in Software Engineering courses. However, these activities should be adequately aligned with the learning outcomes and support student's progression. 

Objective: Present and evaluate an approach to help students acquire theoretical and practical knowledge and experience real-world software projects' challenges. The approach combines a serious game and a design-implement task in which students develop a controlled-scale software system.

Methods: To evaluate our approach, we analyzed the students' perceptions collected through an online survey, their project plans, and their final reports using thematic analysis.

Results: Results suggest that the approach promotes knowledge acquisition, enables students' progression, reinforces theoretical concepts, and is properly aligned with the course's learning outcomes.

Conclusion: The approach seems to help introducing software process models in Software Engineering courses. Our experience can also be inspiring for educators willing to apply our approach in similar courses.

Context: Interest in global software development (GSD) has led to the publication of numerous studies. Over time, these studies should be updated to verify if their findings and conclusions remain valid. 
Objective: To update a tertiary study, published in 2014, focused on investigating risks and risk mitigation advice in the context of GSD. 
Method: We conducted a systematic literature study based on forward snowballing, out of which we identified and selected 25 unique studies.
Results: We extracted: a) 122 risks (75 of which already identified in the original work), and b) 123 mitigation advice (44 of which were identified in the original work). The evidence supporting these risks and mitigation were extracted from 619 and 389 primary sources, respectively. Given the amount of evidence found, we have reported only those with higher empirical support. The raw data, including all the values obtained, are available online as complementary material.
Conclusions: Interest in GSD, its potential risks, and possible mitigation strategies, remains high. This update has allowed increasing the level of empirical support provided by the findings of the original work.

Evaluation of cost estimates should be fair and give incentives for accuracy. These goals, we argue, are challenged by a lack of precision in what is meant by a cost estimate and the use of evaluation measures that do not reward the most accurate cost estimates. To improve the situation, we suggest the use of probabilistic cost estimates and propose guidelines on how to evaluate such estimates. The guidelines emphasize the importance of a match between the type of cost estimate provided by the estimators and the chosen cost evaluation measure, and the need for an evaluation of both the calibration and the informativeness of probabilistic cost estimates. The feasibility of the guidelines is exemplified in an analysis of a set of 69 large Norwegian governmental projects. The evaluation indicated that the projects had quite accurate and unbiased P50 estimates and that the prediction intervals were reasonably well calibrated. It also showed that the cost prediction intervals were non-informative with respect to differences in cost uncertainty and, consequently, not useful to identify projects with higher cost uncertainty. The results demonstrate the usefulness of applying the proposed cost estimation evaluation guidelines.