Scientific Papers
ISSI Research PapersPaper information
Title
A Process for Managing Interaction between Experimenters to Get Useful Similar Replications
A Process for Managing Interaction between Experimenters to Get Useful Similar Replications
Natalia Juristo
Published in
Information and Software Technology 55(2): 215-225 (2013), Impact Factor 1.250 (JCR 2011), ISBN: 0950-5849, Elsevier. - 2013
Information and Software Technology 55(2): 215-225 (2013), Impact Factor 1.250 (JCR 2011), ISBN: 0950-5849, Elsevier. - 2013
Abstract
A replication is the repetition of an experiment. Several efforts have been made to adopt replication as a common practice in software engineering. There are different types of replications, depending on their purpose. Similar replications keep the experimental conditions as alike as possible to the original ones. External similar replications, where the replicating experimenters are not the same people as the original experimenters, have been a stumbling block. Several attempts at combining the results of replications have resulted in failure. Software engineering does not appear to be well suited to such replications, because it works with complex experimentally immature contexts. Software engineering settings have a large number of variables, and the role that many of them play is unknown. A successful (or useful) similar replication helps to better understand the phenomenon under study by verifying results and/or identifying contextual variables that could influence (or not) the results, through the combination of experimental results.
A replication is the repetition of an experiment. Several efforts have been made to adopt replication as a common practice in software engineering. There are different types of replications, depending on their purpose. Similar replications keep the experimental conditions as alike as possible to the original ones. External similar replications, where the replicating experimenters are not the same people as the original experimenters, have been a stumbling block. Several attempts at combining the results of replications have resulted in failure. Software engineering does not appear to be well suited to such replications, because it works with complex experimentally immature contexts. Software engineering settings have a large number of variables, and the role that many of them play is unknown. A successful (or useful) similar replication helps to better understand the phenomenon under study by verifying results and/or identifying contextual variables that could influence (or not) the results, through the combination of experimental results.
BibTeX
@misc{issi_web:id:405,
title = "A Process for Managing Interaction between Experimenters to Get Useful Similar Replications",
author = "Natalia Juristo and Sira Vegas and Martín Solari and Silvia Abrahao and Isabel Ramos",
booktitle = "Information and Software Technology 55(2): 215-225 (2013), Impact Factor 1.250 (JCR 2011), ISBN: 0950-5849, Elsevier.",
year = "2013",
eprint = "http://issi.dsic.upv.es/publications/archives/",
url = "http://www.sciencedirect.com/science/article/pii/S0950584912001425",
abstract = "A replication is the repetition of an experiment. Several efforts have been made to adopt replication as a common practice in software engineering. There are different types of replications, depending on their purpose. Similar replications keep the experimental conditions as alike as possible to the original ones. External similar replications, where the replicating experimenters are not the same people as the original experimenters, have been a stumbling block. Several attempts at combining the results of replications have resulted in failure. Software engineering does not appear to be well suited to such replications, because it works with complex experimentally immature contexts. Software engineering settings have a large number of variables, and the role that many of them play is unknown. A successful (or useful) similar replication helps to better understand the phenomenon under study by verifying results and/or identifying contextual variables that could influence (or not) the results, through the combination of experimental results.
"
}