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Metodologías para optimización de casos de prueba: una prueba práctica

Authors: Solís, Carlos;

Metodologías para optimización de casos de prueba: una prueba práctica

Abstract

Los casos de prueba son vitales para cualquier revisión de calidad de software, pero por su naturaleza suelen requerir de revisiones exhaustivas, lo que causa desgaste al equipo técnico, propensión a omitir fallos, y un importante costo en tiempo y dinero. Para optimizar estos casos de prueba, múltiples metodologías han sido desarrolladas, diseñadas para optimizarlos de tal manera que detecten el máximo de errores con el mínimo de tiempo y esfuerzo; esta área ha tenido un crecimiento importante durante los últimos años. En este artículo se verán y compararán diversas metodologías de reciente desarrollo, que procuran maximizar los errores encontrados, minimizar el tiempo de pruebas, y agrupar inteligentemente pruebas con objetivos similares. Metodologías selectas serán probadas en un ambiente de desarrollo universitario para revisar empíricamente su eficacia.

UCR::Vicerrectoría de Docencia::Ingeniería::Facultad de Ingeniería::Escuela de Ciencias de la Computación e Informática

Country
Costa Rica
Related Organizations
Keywords

Casos de prueba, Optimización, Métodos de prueba, Software

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green