Obtención y validación de modelos de estimación de software mediante técnicas de minería de datos

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dc.contributor.authorMoreno García, Maríaspa
dc.contributor.authorQuintales, Luis A. Miguelspa
dc.contributor.authorGarcía Peñalvo, Francisco Joséspa
dc.contributor.authorPolo Martín, María Joséspa
dc.contributor.orcidGarcía Peñalvo, Francisco José [https://orcid.org/0000-0001-9987-5584]spa
dc.date.accessioned2020-10-27T00:21:30Z
dc.date.available2020-10-27T00:21:30Z
dc.date.issued2002-06-01
dc.description.abstractLa medición del software está adquiriendo una gran importancia debido a que cada vez se hace más patente la necesidad de obtener datos objetivos que permitan evaluar, predecir y mejorar la calidad del software así como el tiempo y coste de desarrollo del mismo. El valor de las mediciones aumenta cuando se realiza sobre modelos construidos en las primeras fases del proyecto ya que los resultados obtenidos permiten tenerlo bajo control en todo momento y corregir a tiempo posibles desviaciones. La proliferación actual de métricas y el gran volumen de datos que se maneja ha puesto de manifiesto que las técnicas clásicas de análisis de datos son insuficientes para lograr los objetivos perseguidos. En este trabajo se presenta la forma en que pueden aplicarse las nuevas técnicas de minería de datos en la construcción y validación de modelos de ingeniería del software, cambiando el análisis tradicional de datos dirigido a la verificación por un enfoque de análisis de datos dirigido al descubrimiento del conocimiento.spa
dc.description.abstractenglishSoftware measurement is becoming very important due to the fact that it is increasingly makes more evident the need to obtain objective data that allow evaluating, predicting and improve the quality of the software as well as the time and cost of its development. The value of measurements increases when performed on models built in the early stages of the project since the results obtained allow it to be under control at all times and correct possible deviations in time. The current proliferation of metrics and the sheer volume of data that is handled has shown that the classical techniques of data analysis are insufficient to achieve the objectives pursued. This paper presents how that new data mining techniques can be applied in the construction and validation of software engineering models, shifting traditional verification-driven data analysis to a discovery-driven data analysis approach. knowledge.eng
dc.format.mimetypeapplication/pdfspa
dc.identifier.instnameinstname:Universidad Autónoma de Bucaramanga UNABspa
dc.identifier.issn2539-2115
dc.identifier.issn1657-2831
dc.identifier.repourlrepourl:https://repository.unab.edu.co
dc.identifier.urihttp://hdl.handle.net/20.500.12749/9063
dc.language.isospaspa
dc.publisherUniversidad Autónoma de Bucaramanga UNAB
dc.relationhttps://revistas.unab.edu.co/index.php/rcc/article/view/1108/1080
dc.relation.referencesA.J. Albrecht, Measuring application development, Proc. IBM Applications Development Joint SHARE/GUIDE Symposium, Monterey, CA, 83-92, 1979.
dc.relation.referencesJ.D. Arthur y K.T. Stevens, Assessing the adequacy of documentation through document quality indicators, Proc. the IEEE Conference of Software Maintenance, 40-49, 1989.
dc.relation.referencesR. Binder, Testing object-oriented systems, American Programmer, 7(4): 22-29, 1994.
dc.relation.referencesB.W. Boehm; B. Clark; E. Horowitz et al., Cost models for future life cycle processes: COCOMO 2.0, Annals Software Engineering 1(1): 1-24, 1995.
dc.relation.referencesL.C. Briand; J.W. Daly y J.K. Wüst, A unified framework for coupling measurement in objectoriented system, IEEE Transaction on Software Engineering, 25 (1): 91-121, 1999.
dc.relation.referencesB. Brykczynskki, A survey of software inspection checklist, ACM Software Engineering Notes, 24(1): 82-89, 1999.
dc.relation.referencesP. Cabena; P. Hadjinian; R. Stadler; J. Verhees y A. Zanasi, Discovering data mining. from concept to implementation, Prentice Hall, 1998.
dc.relation.referencesS.R. Chidamber y C.F. Kemerer, A Metrics Suite for Object-Oriented Design , IEEE Transactions of Software Engineering, 20(6): 476-493, 1994.
dc.relation.referencesN.I. Churcher y M.J. Shepperd, Towards Conceptual Framework for Object-Oriented Metrics, ACM Software Engineering Notes, 20 (2): 67-76, 1995.
dc.relation.referencesA. Davis et al., Identifying and measuring quality in a software requirements specification Proc. First International Software Metrics Symposium, Baltimore, 141-152, 1993.
dc.relation.referencesT. DeMarco, Controlling software projects, Yourdon Press, 1982.
dc.relation.referencesT. DeMarco, Controlling software projects, Yourdon Press, 1982.
dc.relation.referencesB. Farbey, Software Quality metrics: considerations about requirements and requirements specification, Information and Software Technology, 32 (1): 60-64, 1990.
dc.relation.referencesJ.C. French; J.C. Knight y A.L. Powell, Applying hipertext structures to software documentation, Information Processing and Management, 33 (2): 219-231, 1997.
dc.relation.referencesM. Genero; M.E. Manso; M. Piattini y F.J. García, Assessing the quality and the complexity of OMT models, Proc. 2nd European Software Measurements Conference-FESMA 99, Amsterdam, Netherlands, 99-109, 1999.
dc.relation.referencesM. Genero; M. Piattini, y C. Calero, Una propuesta para medir la calidad de los diagramas de clases en UML, IDEAS´2000, Cancun, México, 373-384, 2000.
dc.relation.referencesT.M. Khoshgoftaar; E.B. Allen; J.P. Hudepohl y S.J. Aud, Neural networks for software quality modeling of a very large telecommunications system, IEEE Trans. on Neural Networks, (8)4: 902-909, 1997.
dc.relation.referencesT.M. Khoshgoftaar y E.B. Allen, Modeling Software Quality with Classification Trees. En: Recent advances in reliability and quality engineering, Hoang Pham Editor.World Scientific, Singapore, 1999.
dc.relation.referencesT.M. Khoshgoftaar y D.L. Lanning, A neural network approach for early detection of program modules having high risk in the maintenance phase. J. Systems Software, 29(1): 85-91, 1995.
dc.relation.referencesU. Krohn y C. Boldyreff, Application of cluster algorithms for batching of proposed software changes, J. Softw. Maint: Res. Pract. 11: 151-165. 1999.
dc.relation.referencesF. Lehner, Quality control in software documentation: Measurement of text comprehensibility, Information and Management, 25: 133-146, 1993.
dc.relation.referencesM. Lorenz y J. Kidd, Object_oriented Software Metrics, Prentice Hall 1994.
dc.relation.referencesM.G. Mendonça y V.R. Basili, Validation of an approach for improving existing measurement frameworks, IEEE Transactions on Software Engineering 26(6): 484-499, 2000.
dc.relation.referencesM.G. Mendonça, y N.L. Sunderhaft, Mining software engineering data: A survey, Technical Report, DoD Data and Analysis Center for Software, DACS-SOAR-99-3, 1999.
dc.relation.referencesM.N. Moreno; F.J. García; M.J. Polo; V. López y A. González, Marco de referencia para la gestión de la calidad de las especificaciones de requisitos, Proc. QUATIC 2001, Lisboa, Portugal, 2001.
dc.relation.referencesA. Podgurski; W. Masri; Y. McCleese y F.G. Wolff, Estimation of software reliability by stratified sampling. ACM Trans.on Soft.Eng.and Methodology, 8 (3): 263-283, 1999.
dc.relation.referencesG. Poels, Towards a size measurement framework for object-oriented especifications, Proc. 1st European Software Measurement Conference - FESMA'98, Antwerp, 379-388, 1998.
dc.relation.referencesG. Poels, On the measurements of event-based object-oriented conceptual models, Proc. 4th International ECOOP Workshop on Quantitative Approaches in Object Oriented Software Engineering, Cannes, France, 2000.
dc.relation.referencesA.A. Porter y R.W. Selby, Empirically guided software development using metric-based classification trees, IEEE Software , 7(2): 46-54, 1990.
dc.relation.referencesT. Roth; P. Aiken y S. Hobbs, Hypermedia support for software developmemt: a retrospective assessment, Hypermedia, 6 (3): 149-173, 1994.
dc.relation.referencesW.B. Samson; D.G. Nevill y P.I. Dugard, Predictive software metrics based on a formal specification, Software Engineering Journal, 5(1), 1990.
dc.relation.referencesK. Srinivasan, y D. Fisher, Machine Learning Approaches to Estimating Software Development Effort, IEEE Transactions on Software Engineering, 21(2): 126-137, 1995.
dc.relation.referencesSymons, C.R. Software Sizing and Estimating MKII FPA. John Wiley and Sons, 1991.
dc.relation.referencesJ. Tian y J. Palma, Analyzing and improving reliability:A Tree-based Approach, IEEE Software, 15(2): 97-104, 1998.
dc.relation.referencesJ. Verner y G. Tate, A software size model, IEEE Transaction of Software Engineering, 18 (4): 265-278, 1992.
dc.relation.referencesS.M. Weiss y N. Indurkhya, Predictive data mining. A Practical Guide, Morgan Kaufmann Publishers, San Francisco, 1998.
dc.relation.urihttps://revistas.unab.edu.co/index.php/rcc/article/view/1108
dc.rightsDerechos de autor 2002 Revista Colombiana de Computación
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.creativecommonsAttribution-NonCommercial-ShareAlike 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.5/co/
dc.sourceRevista Colombiana de Computación; Vol. 3 Núm. 1 (2002): Revista Colombiana de Computación; 53-71
dc.subjectInnovaciones tecnológicas
dc.subjectCiencia de los computadores
dc.subjectDesarrollo de tecnología
dc.subjectIngeniería de sistemas
dc.subjectInvestigaciones
dc.subjectTecnologías de la información y las comunicaciones
dc.subjectTIC´s
dc.subject.keywordsTechnological innovationseng
dc.subject.keywordsComputer scienceeng
dc.subject.keywordsTechnology developmenteng
dc.subject.keywordsSystems engineeringeng
dc.subject.keywordsInvestigationseng
dc.subject.keywordsInformation and communication technologieseng
dc.subject.keywordsICT'seng
dc.subject.keywordsData miningeng
dc.subject.keywordsMetricseng
dc.subject.keywordsSoftware estimationeng
dc.subject.lembInnovaciones tecnológicasspa
dc.subject.lembCiencias de la computaciónspa
dc.subject.lembIngeniería de sistemasspa
dc.subject.lembIngeniería de sistemasspa
dc.subject.lembInvestigacionesspa
dc.subject.lembTecnologías de la información y la comunicaciónspa
dc.subject.proposalMinería de datosspa
dc.subject.proposalMétricasspa
dc.subject.proposalEstimación de softwarespa
dc.subject.proposalDesarrollo tecnológicospa
dc.titleObtención y validación de modelos de estimación de software mediante técnicas de minería de datosspa
dc.title.translatedObtaining and validating software estimation models using data mining techniqueseng
dc.type.coarhttp://purl.org/coar/resource_type/c_7a1f
dc.type.driverinfo:eu-repo/semantics/article
dc.type.hasversionInfo:eu-repo/semantics/publishedVersion
dc.type.hasversioninfo:eu-repo/semantics/acceptedVersionspa
dc.type.localArtículospa
dc.type.redcolhttp://purl.org/redcol/resource_type/CJournalArticle

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