GrISE Facultad de Informática - UPM Universidad Politécnica de Madrid
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Using Experiments to Build a Body of Knowledge

Dr. Victor R. Basili

Miércoles 20 de Enero de 1999
Hemiciclo 1005, 17:00 a 18:00 horas

BIOGRAPHY

Dr. Victor R. Basili es Catedrático de Informática en la Universidad de Maryland, Director Ejecutivo del Centro Fraunhofer - Maryland, y uno de los fundadores y directivos del Laboratorio de Ingeniería del Software (SEL) en el NASA/GSFC. Basili es uno de los padres y promotores de la cultura experimental en Ingeniería del Software.

Trabaja principalmente, en medición, evaluación y mejora de los productos y proceso de desarrollo software.

Ha recibido el Group Achievement Award de la NASA y el Productivity Improvement and Quality Enhancement Award del NASA/GSFC. Recibió en 1997 el Award for Outstanding Achievement in Mathematics and Computer Science de la Academia de Ciencias de Washington.

Dr. Basili ha escrito más de 130 artículos en revistas y conferencias, ha sido Editor-in-Chief del IEEE Transactions of Software Engineering, Program Chair y General Chair de las 6th y 15th Conferencias Internacionales en Ingeniería del Software, respectivamente. Es co-editor-in-chief del International Journal of Empirical Software Engineering, publicado por Kluwer. Es Fellow del IEEE y de la ACM.

ABSTRACT

Experimentation in software engineering is difficult. One reason is that there are a large number of context variables, and so, creating a cohesive understanding of experimental results requires a mechanism for motivating studies and integrating results. It requires a community of researchers that can replicate studies, vary context variables, and build abstract models that represent the common observations about the discipline.

This talk offers a high level framework for organizing sets of related studies. With such a framework, experiments can be viewed as part of common families of studies, rather than being isolated events. Common families of studies can contribute to higher level hypotheses that no individual experiment could achieve. Then the replication of experiments within a family of studies can act as the cornerstone for building knowledge in an incremental manner.

A mechanism is suggested that motivates, records, and integrates individual experiments within a family for analysis by the community at large. The framework is based upon the goal template in the Goal/Question/Metric Paradigm. To support the feasibility of the framework, this talk discusses several experiments.

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