This paper presents an educational intervention designed to promote students' engagement, interest, and active involvement, while enriching their learning experience, in a required undergraduate course on database programming. The intervention uses a framework that integrates three active learning strategies: (1) think-pair-share to address theoretical concepts, while enhancing conceptual understanding, critical thinking, and participation; (2) gamification with program-building cards, to address algorithmic aspects, while boosting group collaboration and peer-interaction; and (3) peer-assessment to evaluate final programs, while encouraging students' reflection and critical analysis of their learning. The framework's effectiveness was assessed through a comparative analysis of student performance between experimental and control groups, feedback from the experimental group, and instructor's perceptions. Results showed that students in the experimental group significantly outperformed their peers on examination averages. They also reported higher motivation and engagement while performing the framework's activities. The instructor observed that these students felt more motivated and actively involved in the framework. Given its potential applicability to other courses, the paper concludes with lessons learned for educators and researchers to consider.

Database evolution and data provenance are two closely related research fields. On the one hand, the registry (via provenance) of the schema evolution allows the maintenance of its version record. On the other hand, the origin of the data (i.e., its provenance) will always be affected by modifications (i.e., the evolution) in the schema on which they are based. Despite these interrelationships, there are few works in the literature that have proposed advances in that direction. In particular, to the best of our knowledge, there is no research that has resulted in a general and interoperable solution to the problem of managing database evolution using provenance. In this article, we present PROV-IDEA: a PROV-Interoperable Database Evolution Approach. This is a proposal that allows the simultaneous management of the provenance of schemas (of relational databases) and data, using the PROV standard as a way to guarantee interoperability. Furthermore, it is an adaptable and expandable approach (by using PROV templates), which allows a non-intrusive and seamless integration with existing applications, as well as different aspects of provenance information generation. These properties are demonstrated in the article by presenting a proof of concept built on top of a third-party relational database evolution tool.

In response to the increasing calls for algorithmic accountability, UML2PROV is a novel approach to address the existing gap between application design, where models are described by UML diagrams, and provenance design, where generated provenance is meant to describe an application's flows of data, processes and responsibility, enabling greater accountability of this application. The originality of UML2PROV is that designers are allowed to follow their preferred software engineering methodology to create the UML Diagrams for their application, while UML2PROV takes the UML diagrams as a starting point to automatically generate: (1) the design of the provenance to be generated (expressed asPROV templates); and (2) the software library for collecting runtime values of interest (encoded as variable-value associations known asbindings), which can be deployed in the application without developer intervention. At runtime, the PROV templates combined with the bindings are used to generate high-quality provenance suitable for subsequent consumption. UML2PROV is rigorously defined by an extensive set of 17 patterns mapping UML diagrams to provenance templates, and is accompanied by a reference implementation based on Model Driven Development techniques. A systematic evaluation of UML2PROV uses quantitative data and qualitative arguments to show the benefits and trade-offs of applying UML2PROV for software engineers seeking to make applications provenance-aware. In particular, as the UML design drives both the design and capture of provenance, we discuss how the levels of detail in UML designs affect aspects such as provenance design generation, application instrumentation, provenance capability maintenance, storage and run-time overhead, and quality of the generated provenance. Some key lessons are learned such as: starting from a non-tailored UML design leads to the capture of more provenance than required to satisfy provenance requirements and therefore, increases the overhead unnecessarily; alternatively, if the UML design is tailored to focus on addressing provenance requirements, only relevant provenance gets to be collected, resulting in lower overheads.

Key Performance Indicators (KPIs) are becoming essential elements for measuring business performance. In recent years, KPIs management has been the subject to sustained interests for researchers and practitioners alike, deriving into a large research corpus of approaches addressing aspects in matters as varied as modelling, maintenance or expressiveness of KPIs. In particular, since both businesses and processes have to be adapted to ever-changing requirements, the KPIs that measure their performance must evolve accordingly. However, based on a previous review of the literature, we found that little attention has been paid to the provision of mechanisms to manage KPIs evolution. Our long-term research goal is to provide a fully proposal for supporting KPIs evolution management. In this position paper, we present the first ideas of a conceptual framework for addressing this issue, proposing a pattern-driven KPI evolution specification and a KPI evolution metamodel made up of two interconnected views. Our proposal is general enough to be applied regardless of the specific KPIs management approach being used.

Software engineers must be able to manage complex projects, so that skills such as teamwork, leadership or initiative are critical to their successful development. Because of this, it is fundamental that the learning of software engineering as an academic discipline provides solid links between theory and practice. Educational frameworks such as those derived from the European Higher Education Area state that student-centered approaches are a useful tool for achieving these objectives. In this context, we present a project-based learning (PBL) experience report in a software engineering program of a Spanish university. The experience is based on the formation of small heterogeneous teams, which face the initial phases of a software methodology during the development of a project close to a real one. Through a strategy of role rotation and documentation transfer, all students perform different tasks and face different challenges throughout the project. Summative assessment is also adopted, considering not only teacher ratings but also students' peer assessment. The results prove the positive effect of using PBL to improve the training of students in acquiring different skills as future software engineers.

In a competitive market, business process improvement is a requirement for any organization. This improvement can only be achieved with the support of comprehensive systems that fully monitor business processes. We propose an occurrence - based approach to business process monitoring that provides a holistic perspective of system dynamics, lending support to evolution aspects. More specifically, we present a three-dimensional artifact, called Occurrence, in which structure, behavior, and guidance are considered simultaneously. Based on this, we define more complex structures, namely Occurrence Base and Occurrence Management System, which serve as scaffolding to develop business process monitoring systems. We also present a specific occurrence-based design strategy that, using an MDE approach, has been applied by our research group for the development of successful monitoring applications.

System monitoring is typically performed by means of log files storing the sequential trace of the system events. However, these files constitute a poor solution when improved auditing features are required. For this reason, we advocate defining specific persistence structures for registering a more complete system trace. In particular, when the system behaviour is specified by means of a UML statechart, we propose to automatically generate a stereotyped UML class diagram containing information for tracing the system behaviour without loosing the statechart dynamic semantics. To do this, we have formally defined a Statechart Execution Persistence (SEP) UML profile which (1) eases audit and process improvement, (2) ensures accuracy and consistency of data, and (3) guides during the automatic generation of the system's storage mechanisms, following a MDD approach.

Clinical guidelines systematically assist practitioners with providing appropriate health care for specific clinical circumstances. However, a significant number of guidelines are lacking in quality. In this paper, we use the UML modeling language to capture guidelines and model checking techniques for their verification. We have established a classification of possible properties to be verified in a guideline and we present an automated approach based on a translation from UML to PROMELA, the input language of the SPIN model checker. Our approach is illustrated with a guideline based on a guideline published by the National Guideline Clearing House (NGC).