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Improving and expanding NASA software cost estimation methods

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dc.contributor.author Hihn, Jairus
dc.contributor.author Juster, Leora
dc.contributor.author Johnson, James
dc.contributor.author Menzies, Tim
dc.contributor.author Michael, George
dc.date.accessioned 2019-05-01T17:28:14Z
dc.date.available 2019-05-01T17:28:14Z
dc.date.issued 2016-03-05
dc.identifier.citation IEEE Aerospace Conference, Big Sky, Montana, March 5-12, 2016 en_US
dc.identifier.clearanceno 16-0298
dc.identifier.uri http://hdl.handle.net/2014/46032
dc.description.abstract Estimators and analysts are increasingly being tasked to develop better models and reliable cost estimates in support of program planning and execution. While there has been extensive work on improving parametric methods for cost estimation, there is very little focus on the use of cost models based on analogy and clustering algorithms. In this paper we summarize the results of our research in developing an analogy method for estimating NASA spacecraft flight software using spectral clustering on system characteristics (symbolic nonnumerical data) and evaluate its performance by comparing it to a number of the most commonly used estimation methods. The strengths and weaknesses of each method based on their performance are also discussed. The paper concludes with an overview of the analogy estimation tool (ASCoT) developed for use within NASA that implements the recommended analogy algorithm. en_US
dc.description.sponsorship NASA/JPL en_US
dc.language.iso en_US en_US
dc.publisher Pasadena, CA: Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2016 en_US
dc.title Improving and expanding NASA software cost estimation methods en_US
dc.type Preprint en_US


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