Analyzing Empirical Data in Requirements Engineering Techniques
dc.contributor.author | Jiang, L. | |
dc.contributor.author | Eberlein, A. | |
dc.contributor.author | Krishna, Aneesh | |
dc.date.accessioned | 2017-07-27T05:21:41Z | |
dc.date.available | 2017-07-27T05:21:41Z | |
dc.date.created | 2017-07-26T11:11:20Z | |
dc.date.issued | 2013 | |
dc.identifier.citation | Jiang, L. and Eberlein, A. and Krishna, A. 2013. Analyzing Empirical Data in Requirements Engineering Techniques. In Information Systems Development, 357-368. New York. | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/54625 | |
dc.identifier.doi | 10.1007/978-1-4614-4951-5 | |
dc.description.abstract |
Getting meaningful information from empirical data is a challenging task in software engineering (SE). It requires an in-depth analysis of the research problem, the data obtained and to select the most suitable data analysis methods, as well as an evaluation of the validity of the analysis result. This chapter reports research with three data analysis methods that were used to analyze a set of empirical requirements techniques data. One of the major findings is that it is possible to get better analysis results if several data analysis methods are combined. The way to examine the validity of the results is also explored. | |
dc.title | Analyzing Empirical Data in Requirements Engineering Techniques | |
dc.type | Book Chapter | |
dcterms.source.startPage | 357 | |
dcterms.source.endPage | 368 | |
dcterms.source.title | Information Systems Development | |
dcterms.source.place | New York | |
dcterms.source.chapter | 55 | |
curtin.department | Department of Computing | |
curtin.accessStatus | Fulltext not available |
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