Examinando por Autor "Garzás, Javier"

Mostrando 1 - 9 de 9

A case study of software process improvement with CMMI-DEV and Scrum in Spanish companies
(2013-12-01) Garzás, Javier; Paulk, Mark C
One of the most commonly used agile methods is Scrum. Capability Maturity Model Integration for Development (CMMI-DEV) is currently the de facto framework for process improvement and for determining the organizational maturity of software development companies. CMMI-DEV and Scrum share certain characteristics, and even though they were developed for different purposes, they can be complementary to eachother; and as such, they are not in competition. This paper presents a case study of the relationship between level 2 of CMMI-DEV 1.3 and Scrum. This research has focused on the relationships between Scrum andlevel 2 of CMMI-DEV 1.3. The objective of this research paper is to evaluate how Scrum helps implement a process model such as CMMI-DEV. A detailed case study was conducted among Spanish IT companies. The case study was designed according to established guidelines for cases studies. There were eight principal activities: case study design, case selection, case study procedures and roles, data collection, analysis, plan validity, study limitations, and reporting. The results obtained show that most of the process areas of CMMI-DEV level 2 had been improved by using Scrum. Other issues detected arose during the formal appraisals and illustrated how it is possible toverify with Scrum that the specific goals of CMMI-DEV have been implemented. In addition, it highlight show the use of open-source tools was useful in improving the process in the companies involved. Based on the case study carried out, the addition of Scrum methodologies may improve the increase in quality of software processes
A maturity model for the Spanish software industry based on ISO standards
(2013-11-01) Garzás, Javier; Pino, Francisco J.; Piattini, Mario; Fernández, Carlos Manuel
Many organizations are implementing process improvement models, seeking to increase their organizational maturity for software development. However, implementing traditional maturity models involves a large investment (as regards money, time and resources) which is beyond the reach of vast majority of small organizations. This paper presents the use and adaptation of some ISO models in the creation of an organizational maturity model for the Spanish software industry. This model was used satisfactorily to (i) improve the software processes of several Spanish small firms, and (ii) obtain an organizational maturity certification for software development, granted by the Spanish Association for Standardization and Certification.
A Scrum-based framework for new product development in the non-software industry
(2021-06-18) Cano, Emilio; García-Camús, Juan M; Garzás, Javier; Moguerza, Javier; Sánchez, Noemí
Scrum is an iterative and incremental development framework that, nowadays, is mainly used for software development. In this work, a Scrum-Based New Product Development (SBNPD) approach is introduced. This new framework stems from the basis of Scrum and incorporates tools suitable for being applied to the design and development of physical products. The proposed approach implies that feedback from early adopters is to be gathered throughout the whole project, thereby driving to validated learning within a co-creation process. A case study illustrates how the SBNPD framework is applied for the development of a physical product within the dental industry.
Actas del VII y VIII Congreso Académico Internacional en Gobierno y Gestión del Servicio de Tecnologías de la Información
(Editores: Luis Sánchez, Luis Morán, Esperanza Marcos, Valeria de Castro, Javier Garzás, Maribel Sánchez Segura, 2014) Sánchez, Luis; Morán, Luis; Marcos, Esperanza; Castro, Valeria de; Garzás, Javier; Sánchez Segura, Maribel
Career Success in University Graduates: Evidence from an Ecuadorian Study in Los Ríos Province
(MDPI, 2021-08-20) Pico-Saltos, Roberto; Bravo-Montero , Lady; Montalván-Burbano , Néstor; Garzás, Javier; Redchuk, Andrés
Career success and its evaluation in university graduates generate growing interest in the academy when evaluating the university according to its mission and social mandate. Therefore, monitoring university graduates is essential in measuring career success in the State Technical University of Quevedo (UTEQ, acronym in Spanish). In this sense, this article aims to identify the predictive career success factors through survey application, development of two mathematical functions, and Weka’s classification learning algorithms application for objective career success levels determination in UTEQ university graduates. Researchers established a methodology that considers: (i) sample and data analysis, (ii) career success variables, (iii) variables selection, (iv) mathematical functions construction, and (v) classification models. The methodology shows the integration of the objective and subjective factors by approximating linear functions, which experts validated. Therefore, career success can classify university graduates into three levels: (1) not successful, (2) moderately successful, and (3) successful. Results showed that from 548 university graduates sample, 307 are men and 241 women. In addition, Pearson correlation coefficient between Objective Career Success (OCS) and Subjective Career Success (SCS) was 0.297, reason why construction models were separately using Weka’s classification learning algorithms, which allow OCS and SCS levels classification. Between these algorithms are the following: Logistic Model Tree (LMT), J48 pruned tree, Random Forest Tree (RF), and Random Tree (RT). LMT algorithm is the best suited to the predictive objective career success factors, because it presented 76.09% of instances correctly classified, which means 417 of the 548 UTEQ university graduates correctly classified according to OCS levels. In SCS model, RF algorithm shows the best results, with 94.59% of instances correctly classified (518 university graduates). Finally, 67.1% of UTEQ university graduates are considered successful, showing compliance with the university’s mission.
Kybele Consulting: calidad y valor del software para las organizaciones
(2011) Garzás, Javier; Marcos, Esperanza
Medición del éxito profesional a graduados de la Universidad Técnica Estatal de Quevedo-Ecuador
(2023-04-19) Pico-Saltos, Roberto; Garzás, Javier; Redchuk, Roberto; Jaramillo, Ivan Freddy
Los estudios de seguimiento a graduados de las universidades han contribuido a la medición del éxito de los egresados en los actuales escenarios laborales. El objetivo del presente estudio es analizar el seguimiento a los graduados, su desempeño profesional en el sector empresarial, además, cómo consideran el éxito de su carrera y su satisfacción en la Universidad Técnica Estatal de Quevedo-Ecuador. Se trabajó una investigación exploratoria-descriptiva, con enfoque cuantitativo, y diseño no experimental. Se aplicó un cuestionario con preguntas diseñadas según la escala Likert a 442 egresados de las diferentes carreras, de los cuales 56% corresponde al sexo masculino y 44% representa al sexo femenino. Los resultados indicaron que el 82% de los sujetos califica de excelente la formación profesional recibida. Los empleadores, opinan que el 55% está totalmente de acuerdo con los conocimientos y habilidades de los egresados que se desempeñan en el entorno laboral. Se concluye que es positivo aplicar herramientas para fortalecer el seguimiento a los graduados y su inserción laboral, beneficiando a los empleadores y la universidad, pues permite conocer la actuación de los egresados y su desempeño. Asimismo, revela buena satisfacción por parte de los empleadores en consonancia con las necesidades de la actual sociedad
Numerical Association Rule Mining from a Defined Schema Using the VMO Algorithm
(MDPI, 2021-07-02) Jaramillo, Iván Fredy; Garzás, Javier; Redchuk, Andrés
Association rule mining has been studied from various perspectives, all of which have made valuable contributions to data science. However, there are promising research lines, such as the inclusion of continuous variables and the combination of numerical and categorical attributes for a supervised classification variety. This research presents a new alternative for solving the numerical association rule-mining problem from an optimization perspective by using the VMO (Variable Mesh Optimization) meta-heuristic. This work includes the ability for classification when categorical data are available from a defined rule schema. Our technique implements an optimization process for the intervals of continuous variables, unlike others that discretize these types of variables. Some experiments were carried out with a real dataset to evaluate the quality of the rules obtained; in addition to this, this technique was compared with four population-based algorithms. The results show that this implementation is competitive in classification cases and has more satisfactory results for completely numerical data.
Role of Alumni Program in the Prediction of Career Success in an Ecuadorian Public University
(MDPI, 2022-10-01) Pico-Saltos, Roberto; Garzás, Javier; Redchuk , Andrés; Escandón-Panchana , Paulo; Morante-Carballo , Fernando
Alumni tracking studies at the local, regional and global levels provide quality and efficiency measurement parameters in higher education institutions and project improvements in the quality of professionals. However, there is a gap between alumni tracking and the measurement of career success, influencing the academic offer of careers relevant to labor demands. This article aims to propose a model for predicting career success through the analysis, extraction and evolutionary optimization of objective and subjective variables to determine the role of alumni tracking in a higher education institution. The methodology establishes (i) an analysis of information on the alumni program and career success, (ii) prediction models of career success using genetic algorithms, (iii) validation of prediction models and (iv) the relationship between alumni tracking and career success. The results show models for predicting career success using a genetic algorithm with high certainty percentages, where the objective variables’ weight significantly influences the predictive model. However, subjective variables show importance depending on individual characteristics and their value schemes or goals of graduates. As a recommendation, universities could include a monitoring system for their graduates, which is crucial in adapting to the curriculum, especially in strategic technical and human ethical issues.