July/August 2015

Data Mining and Measurements

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Table of Contents
(click below to download individual articles from the July/August 2015 issue)

From the Sponsor
by Karl G. Rogers
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Big Data and Deep Learning for Understanding DoD Data
by Ying Zhao, Ph.D., Douglas J. MacKinnon, Ph.D., and Shelley P. Gallup, Ph.D.
Today, Big Data infrastructure and analytics intervene with traditional data sciences. We are compelled to ask - What is new?
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Rapid Deployment of Data Mining for Engineering Applications
by Nikhil Dakwala
The fundamentals of data mining: structured vs. unstructured data, supervised vs. unsupervised learning, cluster analysis, association learning, and decision trees.
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Not All Time Matters: Be Sure To Count What Does
by Timothy A. Chick, Lana Cagle, and Gene Miluk
If you have difficulty bringing projects in on schedule with the promised functionality, you might want to rethink the “time” you are using.
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Hybrid-Agile Software Development: Anti-Patterns, Risks, and Recommendations
by Paul E. McMahon
Using a hybrid-agile development approach requires that organizations think carefully about process tailoring and metrics decisions to ensure they stay aligned with their performance goals.
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Using Hubs and Cyclicality to Relate Software Architecture and Quality
by Tyson R. Browning, Jürgen Mihm, and Manuel Sosa
Recent studies of 17 open source applications have shown two salient characteristics of software architecture, hubs and cycles, to have strong relationships with software
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Testing Earned Schedule Forecasting Reliability
by Walt Lipke
Real data for the examination, providing a compelling argument for the reliability of ES duration forecasting.
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by David A. Cook,
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