Aplicaciones de la teoría de la información y la inteligencia artificial al testing de software

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Informática, Departamento de Ingeniería de Sistemas lnformáticos y de Computación, leída el 4-05-2022Software Testing is a critical field for the software industry, as it has the main tools used to ensure the reliability of the produced software. Currently, mor then 50% of the time and resources for creating a software product are diverted to testing tasks, from unit testing to system testing. Moreover, there is a huge interest into automatising this field, as software gets bigger and the amount of required testing increases. however, software Testing is not only an industry oriented field; it is also a really interesting field with a noble goal (improving the reliability of software systems) that at the same tieme is full of problems to solve....Es Testing Software es un campo crítico para la industria del software, ya que éste contienen las principales herramientas que se usan para asegurar la fiabilidad del software producido. Hoy en día, más del 50% del tiempo y recursos necesarios para crear un producto software son dirigidos a tareas de testing, desde el testing unitario al testing a nivel de sistema. Más aún, hay un gran interés en automatizar este campo, ya que el software cada vez es más grande y la cantidad de testing requerido crece. Sin embargo, el Testing de Software no es solo un campo orientado a la industria; también es un campo muy interesante con un objetivo noble (mejorar la fiabilidad de los sistemas software) que al mismo tiempo está lleno de problemas por resolver...Fac. de InformáticaTRUEunpu

Using Squeeziness to test from Finite State Machines

Squeeziness is an information theoretic measure designed to quantify the likelihood of a form of fault masking called failed error propagation. It has been shown that Squeeziness correlates strongly with failed error propagation in white-box scenarios. In this thesis, we adapt Squeeziness to a black-box scenario and show how it can be used to estimate the likelihood of failed error propagation

Using mutual information to select test suites in a black-box framework

Mutual Information is an information theoretic measure designed to quantify the amount of similarity between two random variables ranging over two sets. In this paper, we adapt this concept and show how it can be used to select a good test suite, in a black-box scenario and following a maximize diversity approach. We provide experimental evidence to show the usefulness of the measure. We also show that the time needed to compute the measure is negligible when compared to the time needed to apply extra testing. Finally, we compare our measure with current test prioritization measures and show that our proposal outperforms them. As a side result, in this thesis we present a Genetic Programming approach, fully supported by a tool, to generate test suites using Information Theory based measures

SQLab Extension: Laboratorio virtual lenguaje SQL

Extensión de la plataforma SQLab con nuevas funcionalidades que permitan a estudiantes de Bases de Datos evaluar sus conocimientos de diseño de instrucciones DML del lenguaje SQL y a los docentes hacer un seguimiento de la evolucion de sus alumnos

Cluster de Raspberry Pi para prácticas de Programación Paralela y Big Data

Memoria final del proyecto de Innova-Docenci