Browsing by Autor "Rubby Casallas"

Now showing 1 - 13 of 13

A High-Level Domain-Specific Language for Business Processes Monitoring and Measurement
(Vrije Universiteit Brussel, 2007) Oscar González-Rojas; Rubby Casallas; Dirk Deridder; Viviane Jonckers
A practical approach to multi-modeling views composition
(2024) Andrés Yie; Rubby Casallas; Dirk Deridder; Dennis Wagelaar
The use of several view models to specify a complex system is a common practice to provide the most appropriate abstractions to model its diverse concerns. When several view models are used to specify a system, it is necessary to compose them to generate the application. When the view models are expressed in different Domain Specific Modeling Languages a problem arises because a heterogeneous composition is required. A possible approach to avoid a heterogeneous composition is to transform the diverse models into low-level models using a common low-level modeling language as target. Therefore, when all the view models are transformed in low-level models specified with a common language, it is possible to apply a ho- mogeneous composition to obtain the final application. However, it is necessary to identify the elements to compose in the low-level. In this paper, we present an auto- matic mechanism to identify which elements will be composed. This mechanism is based on defining correspondence relationships between the high-level view mod- els and automatically deriving new correspondence between the generated low-level models.
Automatic Schema Generation for Document-Oriented Systems
(Springer Science+Business Media, 2020) Paola Gómez; Rubby Casallas; Claudia Roncancio
Changing a Generation’s Way of Thinking: Teaching Computational Thinking Through Programming
(SAGE Publishing, 2017) Francisco Buitrago Flórez; Rubby Casallas; Marcela Hernández; Alejandro Reyes; Silvia Restrepo; Giovanna Danies
Computational thinking (CT) uses concepts that are essential to computing and information science to solve problems, design and evaluate complex systems, and understand human reasoning and behavior. This way of thinking has important implications in computer sciences as well as in almost every other field. Therefore, we contend that CT should be taught in elementary schools and included in every university’s educational curriculum. Several studies that measure the impact of teaching programming, analytical thinking, and CT have been conducted. In this review, we analyze and discuss findings from these studies and highlight the importance of learning programming with a focus on the development of CT skills at a young age. We also describe the tools that are available to improve the teaching of CT and provide a state-of-the-art overview of how programming is being taught at schools and universities in Colombia and around the world.
Detecting Architectural Issues During the Continuous Integration Pipeline
(2019) Camilo Mendoza; Kelly Garcés; Rubby Casallas; José Bocanegra
The use of a software reference architecture limits possible deviations and errors in the implementation of software projects, as the code must follow predefined rules that developers must respect to guarantee quality. However, when introducing new code to projects these rules can be violated. As a result, architectural erosion, bad smells, or even bugs that can be difficult to find are introduced to the projects. This paper proposes an approach for reviewing compliance to predefined rules that map architectural decisions to code. During the continuous integration process, the automatic analysis raises an issue for each rule violation. Developers can analyze and correct issues, and trace/visualize improvements, or lack thereof, through time. We present a validation experiment carried out in the context of a Software Development course, and we show how the approach helps developers to write better code.
Implementación de un asistente de IA generativa en la enseñanza de fenómenos de transporte biológico: estrategias, resultados y perspectivas
(2025) A. Barreras; Santiago Serrano; José Bestier Padilla Bejarano; Rubby Casallas; Luis H. Reyes; Juan C. Cruz
La inteligencia artificial generativa (IAGen) está transformando la enseñanza en ingeniería al facilitar la comprensión de conceptos complejos y fomentar el aprendizaje personalizado. Este trabajo presenta BioFlow, un asistente inteligente diseñado para apoyar a los estudiantes del curso de Fenómenos de Transporte Biológico mediante preguntas de práctica, retroalimentación guiada y repasos temáticos. Desarrollado como parte de la estrategia institucional de IAGen de la Universidad de los Andes, BioFlow integra modelos de lenguaje natural en una arquitectura modular con tres casos de uso. Ha sido probado en plataformas como OpenAI y Copilot Studio, y actualmente se proyecta su migración a n8n. Encuestas aplicadas en cuatro periodos académicos revelan una alta valoración por parte de los estudiantes, quienes destacaron su utilidad, facilidad de uso y pertinencia conceptual. A pesar de algunas limitaciones técnicas, los resultados confirman su potencial como herramienta educativa flexible, replicable y alineada con principios pedagógicos y éticos.
Implementing Operations to Combine Feature Models: The Conditional Intersection Case
(2017) Jaime Chavarriaga; Rubby Casallas; Viviane Jonckers
In order to reduce the complexity of modeling product lines, many authors propose modeling product concerns separately by using multiple feature models. These proposals use well-known operations such as merge, union and slice to compose the models for analysis and engineering. Such operations produce new models that represent sets of products that comply with the semantics of the operations. We use different feature models, which were independently created by various experts, to represent: (1) domain concerns and (2) standards and regulations. When experts want to analyze the interactions among the models, they need to work collaboratively and compose their own models. This paper (1) introduces the Conditional Intersection Merge - an operation to combine a feature model for a domain with a feature model for a standard, in which the resulting model includes an optional feature that represents the standard and a set of constraints that enforce the rules of the standard whenever that feature is selected - (2) presents a review of different techniques that can be applied to implement the aforementioned operation, and (3) describes a new approach to implement operations by combining feature models, which only adds constraints to one of the input models.
MMC-BPM: A Domain-Specific Language for Business Processes Analysis
(Springer Science+Business Media, 2009) Oscar González-Rojas; Rubby Casallas; Dirk Deridder
MMC-BPM: A Domain-Specific Language for Business Processes Analysis
(Vrije Universiteit Brussel, 2009) Oscar González-Rojas; Rubby Casallas; Dirk Deridder; Witold Abramowicz
Monitoring and Control of an Event-based Middleware.
(2008) Oscar González-Rojas; Nicolás López; Rubby Casallas
Multi-step Concern Refinement
(Vrije Universiteit Brussel, 2008) Andrés Yie; Rubby Casallas; Dirk Deridder; Ragnhild Van Der Straeten
A Model-Driven Software Product Line (MD-SPL) uses metamodels, models, and transformations to create a family of products using a Model Refinement Line (MRL). However, an MD-SPL must evolve and provide mechanisms to add new crosscutting concerns, such as security or logging, to the applications. Our problem is that we want to preserve and reuse the original MRL. In this paper, we present the challenges associated with this problem. We illustrate them by evaluating different model-driven approaches to add crosscutting concerns into an application using high-level aspects. Furthermore, we propose an approach to add crosscutting concerns as early aspects and to preserve the original MRL. This approach adds a new MRL that refines a high-level model of the concern. This high-level model is related with the high-level application model in the original MRL. The refinement of the application model and the concern model proceeds in parallel. The presented approach is a work in progress and requires us to tackle several challenges in order to implement and validate the proposal.
Supporting Multi-level Configuration with Feature-Solution Graphs -- Formal Semantics and Alloy Implementation
(Vrije Universiteit Brussel, 2013) Jaime Alberto Chavarriaga Lozano; Carlos Francisco Noguera Garcia; Viviane Jonckers; Rubby Casallas
Using multiple feature models to specify configuration options for electrical transformers
(2015) Jaime Chavarriaga; Carlos Rangel; Carlos Noguera; Rubby Casallas; Viviane Jonckers
Electrical Transformers are complex devices that exhibit an enormous variability depending on the intended power transformation, environmental conditions, standards imposed and customer particularities. Incomplete information or inconsistencies in the specifications can lead to re-processes and higher bid times. This paper presents our experience on using multiple feature models to specify custom Electrical Transformer as a Configuration Process. This process facilitates the elicitation of knowledge from multidisciplinary experts using several feature models, one per domain and per standard and defining relationships among them. This separation of domains eases the analysis and validation of the models. To support the process, we have developed some tools to separate, merge and analyze these models. The final feature models are tested configuring and comparing products from existing company catalogs. We consider that the same strategy can be used in other contexts where experts on multiple disciplines participate.