KAIRÓS: Intelligent System for Scenarios Recommendation at the Beginning of Software Process Improvement

Authors

  • Ana Marys Garcia Rodríguez Informatic Science University
  • Yadian Guillermo Pérez Betancourt Informatic Science University
  • Juan Pedro Febles Rodríguez Informatic Science University
  • Yaimí Trujillo Casañola Informatic Science University
  • Alejandro Perdomo Vergara Informatic Science University

DOI:

https://doi.org/10.31449/inf.v42i4.2066

Abstract

Software Process Improvement provides benefits to organizations, however, efforts to improve aren't guided by the combined use of Critical Success Factors and Good Practices to be applied, dedicating resources without a prior analysis to guide the actions intentionally. The research proposes an intelligent system for decision making support in Software Process Improvement, taking as reference the Critical Success Factors and Good Practices that an organization can apply to improve its state. In order to achieve this, an intelligent system is conceived, which, based on Artificial Intelligence techniques, optimizes improvement scenarios through the implementation of a genetic algorithm and the application of rules of association between good practices and critical success factors, predicts the success of scenarios improvement through an evolutionary artificial neural network and offers recommendations to achieve them. The methods used to validate the results corroborated the contribution and usefulness of the proposal.

Author Biographies

Ana Marys Garcia Rodríguez, Informatic Science University

Master in Software QualityEngineer in Computer Science Auxiliary Professor of Software Engineering Department

Yadian Guillermo Pérez Betancourt, Informatic Science University

Engineer in Computer Science Auxiliary Professor of Programming Department

Juan Pedro Febles Rodríguez, Informatic Science University

Doctor in Technical Sciences Titular Professor of Programming Department

Yaimí Trujillo Casañola, Informatic Science University

Doctor in Technical SciencesTitular Professor of Software Engineering Department

Alejandro Perdomo Vergara, Informatic Science University

Engineer in Computer Science Professor of Programming Department

References

Dounos, P. and G. Bohoris (2010). Factors for the Design of CMMI-based Software Process Improvement Initiatives. Conference on Informatics (PCI), 2010 14th Panhellenic, IEEE Xplorer Digital Library, Tripoli, pp. 43 - 47.

Montoni, M. A. and A. R. Rocha (2010). Applying Grounded Theory to Understand Software Process Improvement Implementation. Proceedings of the 2010 Seventh International Conference on the Quality of Information and Communications Technology, IEEE Computer Society. pp. 25-34.

Niazi, M., D. Wilson and D. Zowghi (2006). Critical success factors for software process improvement implementation: an empirical study. Software Process: Improvement and Practice, Vol. 11, num. 2, pp. 193-211. ISSN 1099-1670.

Niazi, M., M. A. Babar and J. M. Verner (2010). Software Process Improvement barriers: A cross-cultural comparison. Information and Software Technology, Vol. 52, num. 11, pp. 1204-1216. ISSN 0950-5849.

Trujillo Casañola, Y (2014). Modelo para Valorar las Organizaciones Desarrolladoras de Software al Iniciar la Mejora de Procesos, Doctorado en Ciencias Técnicas, Tutors A. Febles Estrada and G. León Rodríguez, desarrollada en Diección de Calidad de Software, 2014, Informatics Sciences University, pp. 210.

Fernández Díaz, H., N. Milán Cristo, A. M. Garcia Rodríguez and Y. Trujillo Casañola (2016). Bases teóricas para un procedimiento que evalúe cuantitativamente la influencia de los Factores Críticos de Éxito en la Mejora de Procesos. Informática 2016. VII Taller Internacional de Calidad en las Tecnologías de la Información y las Comunicaciones. La Habana, XVI Convención y Feria Internacional INFORMÁTICA 2016.

Niazi, M., D. Wilson and D. Zowghi (2005). A maturity model for the implementation of software process improvement: an empirical study. J. Syst. Softw., Vol. 74, num. 2, pp. 155-172. ISSN 0164-1212.

Niazi, M., D. Wilson and D. Zowghi (2005). A framework for assisting the design of effective software process improvement implementation strategies. Journal of Systems and Software, Vol. 78, num. 2, pp. 204-222. ISSN 0164-1212.

Clarke, P. and R. O’Connor (2010). Harnessing ISO/IEC 12207 to Examine the Extent of SPI Activity in an Organization. European Conference on Software Process Improvement, Springer, pp. 25-36.

Goldberg, D. E. (1989). Genetic Algorithms in Search, Optimization and Machine Learning, 1st ed., Addison-Wesley Longman Publishing Co., Inc. Boston, MA, pp. 412. ISBN 0201157675.

Pavez-Lazo, B., J. Soto-Cartes, C. Urrutia and M. Curilem (2009). Selección determinística y cruce anular en algoritmos genéticos: aplicación a la planificación de unidades térmicas de generación, Ingeniare. Revista chilena de ingeniería, Vol. 17, num. 2, pp. 175-181. ISSN 0718-3305.

Tallón, B. A. J. (2013). Nuevos modelos de Redes Neuronales Evolutivas para Clasificación. Aplicación a Unidades Producto y Unidades Sigmoide, Doctorado en Ingeniería y Tecnología del Software, Tutors M. C. Hervás and S. J. C. Riquelme, Sevilla.

Tallón Ballesteros, A. J., M. C. Hervás, J. C. Riquelme Santos and R. Ruiz (2013). Feature selection to enhance a two-stage evolutionary algorithm in product unit neural networks for complex classification problems, Neurocomputing, Vol. 114, pp. 107-117. ISSN 0925-2312.

Tostado, S. S. E., R. M. Ornelas, J. A. Espinal and S. H. J. Puga (2016). Implementación de Algoritmos de Inteligencia Artificial para el Entrenamiento de Redes Neuronales de Segunda Generación, Jóvenes en la Ciencia, Vol. 2, num. 1, pp. 5. ISSN 2395-9797.

Martín, D., A. Rosete, J. Alcalá-Fdez and F. Herrera (2014). QAR-CIP-NSGA-II: A new multi-objective evolutionary algorithm to mine quantitative association rules, Information Sciences, Vol. 258, pp. 1-28. ISSN 0020-0255.

Oviedo Carrascal, E. A., A. I. Oviedo Carrascal and G. L. Vélez Saldarriaga (2015). MINERÍA DE DATOS: APORTES Y TENDENCIAS EN EL SERVICIO DE SALUD DE CIUDADES INTELIGENTES, Revista Politécnica, Vol. 11, num. 20. ISSN 1900-2351.

Garcia Rodríguez, A. M., Y. Trujillo Casañola, R. G. Rivero Morales, M. A. Verdera Marcano and O. Santos Acosta (2016). Red Neuronal Artificial para el pronóstico de éxito en la Mejora de Procesos de Software, Congreso INFO 2016, Instituto de Información Científica y Tecnología (IDICT), La Habana.

Garcia Rodríguez, A. M., Y. Trujillo Casañola and A. Perdomo Vergara (2016). Optimización de estados en la mejora de procesos de software. Enl@ce, Vol. 13, num. 2. ISSN 1690-7515.

Torres, M., K. Paz and F. Salazar (2006). Tamaño de una muestra para una investigación de mercado.

Gang, Y., Z. Hong, W. Lei and L. Ying (2009). An implementation of improved apriori algorithm, International Conference on Machine Learning and Cybernetics, pp. 1565-1569. ISBN 2160-133X.

Singh, J., H. Ram and D. J. Sodhi (2013). Improving efficiency of apriori algorithm using transaction reduction, International Journal of Scientific and Research Publications, Vol. 3, num. 1, pp. 1-4.

Yabing, J. (2013). Research of an improved apriori algorithm in data mining association rules, International Journal of Computer and Communication Engineering, Vol. 2, num. 1, pp. 25. ISSN 2010-3743.

Lin, X. (2014). Mr-apriori: Association rules algorithm based on mapreduce, Conference on Software Engineering and Service Science (ICSESS), 2014 5th IEEE International, IEEE. pp. 141-144. ISBN 1479932795.

Pradhan, T., S. R. Mishra and V. K. Jain (2014). An effective way to achieve excellence in research based learning using association rules, International Conference on Data Mining and Intelligent Computing (ICDMIC), pp. 1-4.

Downloads

Published

2018-05-08

How to Cite

Garcia Rodríguez, A. M., Pérez Betancourt, Y. G., Febles Rodríguez, J. P., Trujillo Casañola, Y., & Perdomo Vergara, A. (2018). KAIRÓS: Intelligent System for Scenarios Recommendation at the Beginning of Software Process Improvement. Informatica, 42(4). https://doi.org/10.31449/inf.v42i4.2066

Issue

Vol. 42 No. 4 (2018)

Section

Regular papers

License

I assign to Informatica, An International Journal of Computing and Informatics ("Journal") the copyright in the manuscript identified above and any additional material (figures, tables, illustrations, software or other information intended for publication) submitted as part of or as a supplement to the manuscript ("Paper") in all forms and media throughout the world, in all languages, for the full term of copyright, effective when and if the article is accepted for publication. This transfer includes the right to reproduce and/or to distribute the Paper to other journals or digital libraries in electronic and online forms and systems.

I understand that I retain the rights to use the pre-prints, off-prints, accepted manuscript and published journal Paper for personal use, scholarly purposes and internal institutional use.

In certain cases, I can ask for retaining the publishing rights of the Paper. The Journal can permit or deny the request for publishing rights, to which I fully agree.

I declare that the submitted Paper is original, has been written by the stated authors and has not been published elsewhere nor is currently being considered for publication by any other journal and will not be submitted for such review while under review by this Journal.  The Paper contains no material that violates proprietary rights of any other person or entity. I have obtained written permission from copyright owners for any excerpts from copyrighted works that are included and have credited the sources in my article. I have informed the co-author(s) of the terms of this publishing agreement.


Copyright ©  Slovenian Society Informatika