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Mental Models of Software Forecasting

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dc.contributor.author Hihn, J. en_US
dc.contributor.author Griesel, A. en_US
dc.contributor.author Bruno, K. en_US
dc.contributor.author Fouser, T. en_US
dc.contributor.author Tausworthe, R. en_US
dc.date.accessioned 2004-10-06T02:22:51Z
dc.date.available 2004-10-06T02:22:51Z
dc.date.issued 1993-06-01 en_US
dc.identifier.citation San Francisco, California, USA en_US
dc.identifier.clearanceno 93-0799 en_US
dc.identifier.uri http://hdl.handle.net/2014/35223
dc.description.abstract The majority of software engineers resist the use of the currently available cost models. One problem is that the mathematical and statistical models that are currently available do not correspond with the mental models of the software engineers. In an earlier JPL funded study (Hihn and Habib-agahi, 1991) it was found that software engineers prefer to use analogical or analogy-like techniques to derive size and cost estimates, whereas curren CER's hide any analogy in the regression equations. In addition, the currently available models depend upon information which is not available during early planning when the most important forecasts must be made. en_US
dc.format.extent 795193 bytes
dc.format.mimetype application/pdf
dc.language.iso en_US
dc.subject.other Cost Models en_US
dc.title Mental Models of Software Forecasting en_US


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