The Importance of Using Empirical Evidence in Software Engineering
cic.isFulltext | true | es |
cic.isPeerReviewed | true | es |
cic.lugarDesarrollo | Universidad Nacional de La Plata | es |
dc.date.accessioned | 2016-08-25T14:39:59Z | |
dc.date.available | 2016-08-25T14:39:59Z | |
dc.identifier.uri | https://digital.cic.gba.gob.ar/handle/11746/4016 | |
dc.title | The Importance of Using Empirical Evidence in Software Engineering | en |
dc.type | Parte de libro | es |
dcterms.abstract | Experiments that are run with few experimental subjects are often considered not to be very reliable and deemed, as a result, to be useless with a view to generating new knowledge. This belief is not, however, entirely correct. Today we have tools, such as meta-analysis, that we can use to aggregate small-scale experiments and output results that are equivalent to experiments run on large samples that are therefore reliable. The application of meta-analysis can overcome some of the obstacles that we come up against when running software engineering experiments (such as, for example, the practitioner availability problem). | en |
dcterms.creator.author | Fernández, Enrique | es |
dcterms.creator.author | Dieste, Oscar | es |
dcterms.creator.author | Pesado, Patricia Mabel | es |
dcterms.creator.author | García Martínez, Ramón | es |
dcterms.extent | p. 181-189 | es |
dcterms.identifier.isbn | 978-950-34-0757-8 | es |
dcterms.isPartOf.item | Computer Science and Technology Series, XVI Argentine Congress of Computer Science, Selected papers | es |
dcterms.issued | 2011 | |
dcterms.language | Inglés | es |
dcterms.license | Attribution 4.0 International (BY 4.0) | es |
dcterms.publisher | Editorial de la Universidad de La Plata (EDULP) | es |
dcterms.subject | Meta-analysis | en |
dcterms.subject | statistical power | en |
dcterms.subject | reliability | en |
dcterms.subject | replications | es |
dcterms.subject | sample size | en |
dcterms.subject.materia | Ciencias de la Computación | es |
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