2011
Using Predictive Modeling in Software Development: Results from the Field
Measurement & Analysis , SEI Research No Comments »By Dennis R. Goldenson
Senior Member of the Technical Staff
Software Engineering Measurement and Analysis
As
with any new initiative or tool requiring significant investment, the
business value of statistically-based predictive models must be
demonstrated before they will see widespread adoption. The SEI Software Engineering Measurement and Analysis (SEMA)
initiative has been leading research to better understand how existing
analytical and statistical methods can be used successfully and how to
determine the value of these methods once they have been applied to the
engineering of large-scale software-reliant systems. As part of this
effort, the SEI hosted a series of workshops that brought together
leaders in the application of measurement and analytical methods in many
areas of software and systems engineering. The workshops help identify
the technical barriers organizations face when they use advanced
measurement and analytical techniques, such as computer modeling and
simulation. This post focuses on the technical characteristics and
quantified results of models used by organizations at the workshops.
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