Revisión sistemática sobre el aseguramiento de la calidad de requisitos

La especificación de requisitos es un artefacto software crucial en el desarrollo de software y su calidad puede tener gran influencia sobre el producto software finalmente implementado, y más aún en un entorno de desarrollo global de software (DGS). Por ello es sumamente importante evaluar/asegurar la calidad de las especificaciones de requisitos. El objetivo de este informe es presentar una revisión sistemática de la literatura (RSL) con el fin de conocer las propuestas existentes sobre como evaluar y/o asegurar la calidad de los requisitos de productos software. La búsqueda de artículos se ha hecho en el periodo comprendido entre el 01/01/1990 y el 30/09/2010 en tres fuentes de búsquedas electrónicas (SCOPUS, ACM y Science Direct). Se han obtenido 67 estudios primarios, clasificado según las siguientes dimensiones: tipo de propuesta, característica de calidad, tipo de artefacto, tipo de software, método de validación, tipo de soporte. Como conclusión podemos decir que si bien todas las propuestas coinciden en la necesidad imperiosa de obtener especificaciones software de calidad debido a que tienen gran impacto económico y en la calidad de los productos software, no existen técnicas de evaluación/aseguramiento de la calidad de los requisitos ampliamente difundidas en la industria, y menos aún en entornos de DGS. Para contribuir a subsanar esta carencia creemos conveniente la utilización métodos empíricos que permitan validar la efectividad de las técnicas propuestas en entornos industriales. Lo que sí parece estar más claro es cuales son las características de calidad más relevantes, ellas son: completitud, consistencia, validación, corrección, no-ambigüedad y entendibilidad.Sociedad Argentina de Informática e Investigación Operativ

Using web‐based gamified software to learn Boolean algebra simplification in a blended learning setting

One of the fundamental topics in the education of students enrolled in computer‐related degrees is that of Boolean algebra. This is because it allows the expression of several problems related to digital design, artificial intelligence, databases, compilers, and formal languages, among others, as a sequence of Boolean operations and variables, which can be dealt with by using Boolean algebra methods to optimize algorithms, minimize digital components, and so forth. This study presents a piece of web‐based software, denominated as MiniBool, which has been developed with the objective of supporting the learning of Boolean algebra in a blended learning setting. This educational proposal gives students the opportunity to reinforce learning at any time and in any place. It additionally increases the learners’ motivation by including gamification, through the use of a ranking that shows the students’ level of participation. MiniBool was evaluated by means of a formal experiment, which was carried out with Discrete Mathematics students at a higher education institution in Mexico, where two groups were formed randomly: A control group, whose members attended classes and reinforced their knowledge in a traditional manner with a pencil and paper, and an experimental group, which learned in a blended learning context, receiving the same classes as the control group, but reinforcing what they had learned using MiniBool. The statistical results obtained indicate that the use of MiniBool has a positive and motivating effect on learning and that a greater academic performance is achieved than when the traditional teaching‐learning method is applied

Using an Educational Mobile Application for Learning the Essence 1.2 Kernel Alphas

Essence 1.2 is a standard that facilitates the study of Software Engineering by essentializing the broad empirical knowledge related to this area. The main component of the standard is the kernel, which contains alphas that make it possible to assess the state and progress of a software project through the use of a holistic thinking framework. This paper presents an educational mobile application, denominated as Alphalingo, with which to learn the alphas, and which promotes active and meaningful learning through the inclusion of various learning styles, gamification and spaced learning. The educational proposal was evaluated by means of a formal experiment and a replication, which were carried out with professionals working at two software enterprises in Mexico. The experimentation method consisted of randomly selecting the participants in order to form two groups: a control group, whose members attended classes in order to learn the Essence 1.2 kernel alphas, and an experimental group, which learned using Alphalingo. The statistical results obtained from the meta-analysis carried out indicate that the use of Alphalingo has a greater degree of learning effectiveness and a greater motivating effect than the face-to-face method.Essence 1.2 es un estándar que facilita el estudio de la Ingeniería del Software al esencializar el amplio conocimiento empírico relacionado con esta área. El componente principal del estándar es el núcleo, que contiene alfas que permiten evaluar el estado y el progreso de un proyecto de software mediante el uso de un marco de pensamiento holístico. Este artículo presenta una aplicación móvil educativa, denominada Alphalingo, con la que aprender los alfas, y que promueve el aprendizaje activo y significativo mediante la inclusión de varios estilos de aprendizaje, la gamificación y el aprendizaje espaciado. La propuesta educativa se evaluó mediante un experimento formal y una réplica, los cuales se realizaron con profesionales que laboran en dos empresas de software en México. El método de experimentación consistió en seleccionar aleatoriamente a los participantes para formar dos grupos: un grupo de control, cuyos integrantes asistieron a clases para aprender las alfas del kernel Essence 1.2, y un grupo experimental, que aprendió usando Alphalingo. Los resultados estadísticos obtenidos del metaanálisis realizado indican que el uso de Alphalingo tiene un mayor grado de efectividad en el aprendizaje y un mayor efecto motivador que el método presencial

Considerations about quality in model-driven engineering

The final publication is available at Springer via http://dx.doi.org/10.1007/s11219-016-9350-6The virtue of quality is not itself a subject; it depends on a subject. In the software engineering field, quality means good software products that meet customer expectations, constraints, and requirements. Despite the numerous approaches, methods, descriptive models, and tools, that have been developed, a level of consensus has been reached by software practitioners. However, in the model-driven engineering (MDE) field, which has emerged from software engineering paradigms, quality continues to be a great challenge since the subject is not fully defined. The use of models alone is not enough to manage all of the quality issues at the modeling language level. In this work, we present the current state and some relevant considerations regarding quality in MDE, by identifying current categories in quality conception and by highlighting quality issues in real applications of the model-driven initiatives. We identified 16 categories in the definition of quality in MDE. From this identification, by applying an adaptive sampling approach, we discovered the five most influential authors for the works that propose definitions of quality. These include (in order): the OMG standards (e.g., MDA, UML, MOF, OCL, SysML), the ISO standards for software quality models (e.g., 9126 and 25,000), Krogstie, Lindland, and Moody. We also discovered families of works about quality, i.e., works that belong to the same author or topic. Seventy-three works were found with evidence of the mismatch between the academic/research field of quality evaluation of modeling languages and actual MDE practice in industry. We demonstrate that this field does not currently solve quality issues reported in industrial scenarios. The evidence of the mismatch was grouped in eight categories, four for academic/research evidence and four for industrial reports. These categories were detected based on the scope proposed in each one of the academic/research works and from the questions and issues raised by real practitioners. We then proposed a scenario to illustrate quality issues in a real information system project in which multiple modeling languages were used. For the evaluation of the quality of this MDE scenario, we chose one of the most cited and influential quality frameworks; it was detected from the information obtained in the identification of the categories about quality definition for MDE. We demonstrated that the selected framework falls short in addressing the quality issues. Finally, based on the findings, we derive eight challenges for quality evaluation in MDE projects that current quality initiatives do not address sufficiently.F.G, would like to thank COLCIENCIAS (Colombia) for funding this work through the Colciencias Grant call 512-2010. This work has been supported by the Gene-ralitat Valenciana Project IDEO (PROMETEOII/2014/039), the European Commission FP7 Project CaaS (611351), and ERDF structural funds.Giraldo-Velásquez, FD.; España Cubillo, S.; Pastor López, O.; Giraldo, WJ. (2016). Considerations about quality in model-driven engineering. Software Quality Journal. 1-66. https://doi.org/10.1007/s11219-016-9350-6S166(1985). Iso information processing—documentation symbols and conventions for data, program and system flowcharts, program network charts and system resources charts. ISO 5807:1985(E) (pp. 1–25).(2011). Iso/iec/ieee systems and software engineering – architecture description. 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A systematic literature review of studies on business process modeling quality. Information and Software Technology, 58, 187–205.DenHaan, J. (2009). 8 reasons why model driven development is dangerous @ONLINE.DenHaan, J. (2010). Model driven engineering vs the commando pattern @ONLINE.DenHaan, J. (2011a). Why aren’t we all doing model driven development yet @ONLINE.DenHaan, J. (2011b). Why there is no future model driven development @ONLINE.Di Ruscio, D., Iovino, L., & Pierantonio, A. (2013). Managing the coupled evolution of metamodels and textual concrete syntax specifications. cited By (since 1996)0.Dijkman, R.M., Dumas, M., & Ouyang, C. (2008). Semantics and analysis of business process models in {BPMN}. Information and Software Technology, 50(12), 1281–1294.Domínguez-Mayo, F.J., Escalona, M.J., Mejías, M., Ramos, I., & Fernández, L. (2011). A framework for the quality evaluation of mdwe methodologies and information technology infrastructures. 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Automatic execution of business process models: exploiting the benefits of model-driven engineering approaches. Journal of Systems and Software, 85(3), 607–625. Novel approaches in the design and implementation of systems/software architecture.Falkenberg, E.D., Hesse, W., Lindgreen, P., Nilsson, B.E., Oei, J.L.H., Rolland, C., Stamper, R.K., Assche, F.J.M.V., Verrijn-Stuart, A.A., & Voss, K. (1996). Frisco: a framework of information system concepts. Technical report, The IFIP WG 8. 1 Task Group FRISCO.Fettke, P., Houy, C., Vella, A.-L., & Loos, P. (2012). Towards the Reconstruction and Evaluation of Conceptual Model Quality Discourses – Methodical Framework and Application in the Context of Model Understandability, volume 113 of Lecture Notes in Business Information Processing, chapter 28, pages 406–421, Springer, Berlin, Heidelberg.Finnie, S. (2015). Modeling community: Are we missing something?Fournier, C. (2008). Is uml [email protected], R., & Rumpe, B. (2007). 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Towards a model for managing success factors in software process improvement

Existing software engineering and management literature argue for many different ways of looking at success factors that influence Software Process Improvement (SPI). This study investigates success factors identified in a number of research projects and proposes a model for managing these factors in a structured way during different phases of an SPI program. It also aspires to describe a model that reflects the cyclical influences of factors in a continuously progressing SPI progra

Defining and Validating Metrics for Assessing the Maintainability of Entity-Relationship Diagrams

Database and data model evolution is a significant problem in the highly dynamic business environment that we experience these days. To support the rapidly changing data requirements of agile companies, conceptual data models, which constitute the foundation of database design, should be sufficiently flexible to be able to incorporate changes easily and smoothly. In order to understand what factors drive the maintainability of conceptual data models and to improve conceptual modelling processes, we need to be able to assess conceptual data model properties and qualities in an objective and cost-efficient manner. The scarcity of early available and thoroughly validated maintainability measurement instruments motivated us to define a set of metrics for Entity-Relationship (ER) diagrams, which are a relevant graphical formalism of the conceptual data modelling method. In this paper we show that these objectives and easily calculated metrics, measuring internal properties of ER diagrams related to their structural complexity, can be used as indirect measures (hereafter called indicators) of the maintainability of the diagrams. These metrics may replace more expensive, subjective, and hence potentially unreliable maintainability measurement instruments that are based on expert judgement. Moreover, these metrics are an alternative to direct measurements that can only be obtained during the actual process of data model maintenance. Another result is that the validation of the metrics as early maintainability indicators opens up the way for an in-depth study of structural complexity as a major determinant of conceptual data model maintainability. Apart from the definition of a metrics suite, a contribution of this study is the methodological approach that was followed to theoretically validate the proposed metrics as structural complexity measures and to empirically validate them as maintainability indicators. This approach is based both on Measurement Theory and on an experimental research methodology, stemming mainly from current research in the field of empirical software engineering. In the paper we specifically emphasize the need to conduct a family of related experiments, improving and confirming each other, to produce relevant, empirically supported knowledge on the validity and usefulness of metrics.conceptual data model, entity relationship diagrams, model evolution, model quality, maintainability, structural complexity, metrics, prediction, theoretical validation, empirical validation, experimentation

Quality in conceptual modeling - New research directions

A