Effectiveness evaluation of a software product oriented web based on fuzzy logic
Keywords:
Fuzzy Logic, Software Metrics, Linguistic Variable, Inference System, Quality SoftwareAbstract
This paper presents a detailed study can be qualifiedas a software product developed by applying a fuzzylogic system, which allows evaluating the responsesthat the system generated from the considerationsthat must be taken into account in the definitionquality, given the parameters that end users look forthese systems.The methodology is quasi-experimental, basedon surveys given to help define the characteristicsand quality standards that each user has andthen translate these parameters into a softwareproduct, which will qualify three websites on thesecharacteristics.From this it was found that the results obtainedby the system, compared to those defined by theuser are similar and therefore have no significantdifferences among them, being able to ensure thatthe software evaluates the quality of web systemseffective.
Downloads
References
2. Gall, C.; Lukins, S; Etzkorn, L; Gholston,S; Farrington, P; Utley, D; Fortune, J; Virani,S.(2008). Semantic software metrics computed fromnatural language design specifications. Software,IET – IEEE. Vol. 2 No. 1. pp. 17 – 26.
3. Akingbehin, Kiumi. (2009). Taguchi Smallerthe-Best Software Quality Metrics.10th ACISInternational Conference on Software Engineering,Artificial Intelligences, Networking and Parallel/Distributed Computing.pp.585-588.
4. Heck, Petra; Klabbers, Martijn; EekelenMarko van. (2010). A software product certificationmodel. Software Quality Journal, vol. 18 No. 1. -Springer Netherlands. pp. 37-55.
5. Hofman, Radoslaw. (2009). Software QualityPerception. Advanced Techniques in ComputingSciences and Software Engineering. Springer. pp.31 – 39.
6. Pressman, Roger. (2008) Ingeniería de Software,Un Enfoque Práctico. 6 Edición. EditorialMcGraw-Hill. Barcelona.
7. López, Daniela; Agüero, Martín. (2007).Aplicación de Métricas Categóricas en sistemas delógica difusa. Revista IEEE América Latina. Vol. 1.No. 5. pp. 55-61.
8. Yang, Bo; Yao, Lan; Huang, Hong-Zhong.(2007). Early Software Quality Prediction Based ona Fuzzy Neural Network Model.Third InternationalConference on Natural Computation (ICNC 2007)– IEEE. pp. 760 – 764.
9. Ruiz, Gustavo; Peña, Alejandro; Castro, Carlos;Alaguna, Ángela; Areiza, Luz y Rincón, Modelode Evaluación de Calidad de Software Basado enLógica Difusa, Aplicada a Métricas de Usabilidadde Acuerdo con la Norma ISO/IEC 9126.Avances en Sistemas e Informática. Vol. 3 No. 2pp. 25–29.
10. Morales Luna Guillermo. (2002). Introducción ala lógica difusa. Centro de Investigación y EstudiosAvanzados del IPN. pp. 1 - 12
11. Fernández, Carlos; Fernández, Ignacio; Moya,David. (2008).Valoración de inmuebles mediantetécnicas de lógica difusa. Universidad Complutensede Madrid. Tésis de Maestría.
12. Chang, Ching-Liang. (2009) Fuzzy-logicbasedprogramming.Editorial World Scientific.Advances in Fuzzy Logic.Applications andTheory.Vol. 15.
