The lack of citations is concerning. I could read his book but it worries me when numbers like these are thrown around without some way to verify the analysis.

The lack of citations is concerning. I could read his book but it worries me when numbers like these are thrown around without some way to verify the analysis. The "28x productivity" (or 10x or Xx ...) claim always triggers warning bells for me. http://morendil.github.io/folklore.html http://morendil.github.io/folklore.html does a pretty good job explaining how the research backing that widely accepted "fact" may be questionable. I also really like Dan Luu's review of the research behind static typing at http://danluu.com/empirical-pl/ http://danluu.com/empirical-pl/ as an example of how a "well studied" claim can still be questionable due to the massive difficulty in evaluating software engineering empirically. Software engineering is a very human activity and that makes it very hard to measure and quantify. A book that does a better job is Making Software (http://www.amazon.com/Making-Software-ebook/dp/B004D4YI6G/ref=la_B001H6PNGM_1_3?ie=UTF8&qid=1370219697&sr=1-3 http://www.amazon.com/Making-Software-ebook/dp/B004D4YI6G/re...) but as my first link points out, it still has some issues. At least its goal is to get more rigorous in our scientific analysis of software engineering.