Quantitative Determination of the Relationship between Internal Validity and Bias in Software Engineering Experiments: Consequences for Systematic Literature Reviews

Dieste Tubio, Oscar; Juristo Juzgado, Natalia; Grimán, Anna y Saxena, Himanshu (2011). Quantitative Determination of the Relationship between Internal Validity and Bias in Software Engineering Experiments: Consequences for Systematic Literature Reviews. En: "Fifth International Symposium on Empirical Software Engineering and Measurement, ESEM 2011", 19/09/2011 - 23/09/2011, Banff, Albert, Canada. ISBN 978-1-4577-2203-5. pp. 285-294.

Descripción

Título: Quantitative Determination of the Relationship between Internal Validity and Bias in Software Engineering Experiments: Consequences for Systematic Literature Reviews
Autor/es:
  • Dieste Tubio, Oscar
  • Juristo Juzgado, Natalia
  • Grimán, Anna
  • Saxena, Himanshu
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: Fifth International Symposium on Empirical Software Engineering and Measurement, ESEM 2011
Fechas del Evento: 19/09/2011 - 23/09/2011
Lugar del Evento: Banff, Albert, Canada
Título del Libro: Proceedings of the Fifth International Symposium on Empirical Software Engineering and Measurement, ESEM 2011
Fecha: 2011
ISBN: 978-1-4577-2203-5
Materias:
Palabras Clave Informales: Systematic Literature Review (SLR); Quality Assessment (QA) of experiments; Checklist; Quality Scale
Escuela: Facultad de Informática (UPM) [antigua denominación]
Departamento: Lenguajes y Sistemas Informáticos e Ingeniería del Software
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

Quality assessment is one of the activities performed as part of systematic literature reviews. It is commonly accepted that a good quality experiment is bias free. Bias is considered to be related to internal validity (e.g., how adequately the experiment is planned, executed and analysed). Quality assessment is usually conducted using checklists and quality scales. It has not yet been proven;however, that quality is related to experimental bias. Aim: Identify whether there is a relationship between internal validity and bias in software engineering experiments. Method: We built a quality scale to determine the quality of the studies, which we applied to 28 experiments included in two systematic literature reviews. We proposed an objective indicator of experimental bias, which we applied to the same 28 experiments. Finally, we analysed the correlations between the quality scores and the proposed measure of bias. Results: We failed to find a relationship between the global quality score (resulting from the quality scale) and bias; however, we did identify interesting correlations between bias and some particular aspects of internal validity measured by the instrument. Conclusions: There is an empirically provable relationship between internal validity and bias. It is feasible to apply quality assessment in systematic literature reviews, subject to limits on the internal validity aspects for consideration.

Más información

ID de Registro: 11571
Identificador DC: http://oa.upm.es/11571/
Identificador OAI: oai:oa.upm.es:11571
URL Oficial: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6092577
Depositado por: Memoria Investigacion
Depositado el: 19 Jul 2012 09:23
Ultima Modificación: 20 Abr 2016 19:36
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