Software Analytics

"Measure what is measurable, and make measurable what is not so." -- Galileo Galilei. http://en.wikipedia.org/wiki/Galileo_Galilei.

Data is just raw information -- to make that information meaningful, it has to be organized, filtered, and analyzed. Anyone can apply data analysis tools and get results, but without the right approach those results may be useless. This book shows how to effectively approach data analysis problems, and how to extract all of the available information from your data.

One of the clearest, cleanest texts on data mining. While it mentions the WEKA toolkit, its descriptions and explanations of data mining algorithms are insightful for any toolkit.

CUBRID blog - articles about database management systems and software development.

The mission of the Software Analytics Group at Microsoft Research Asia is to advance the state of the art in the software analytics area; and utilize our technologies to help improve the quality of software and services as well as the development productivity for both Microsoft and software industry. They have a large list of publications and presentations on the topic of software analytics.

Revolutions. News about R, statistics, big data analytics, data science, and the world of open source from the staff of Revolution Analytics. (from Revolution Analytics, http://www.revolutionanalytics.com)

"Two Solitudes", Greg Wilson's keynote at the Mining Software Repositories (MSR) Vision 2020 event in Kingston, Ontario. (http://msrcanada.org/msrvision2020/) See also discussion here: http://www.reddit.com/r/programming/comments/yw9ra/greg_wilsons_brilliant_slides_about_the/

Moneyball for software engineering. How metrics-driven decisions can build better software teams (by Jonathan Alexander)

“As complexity rises, precise statements lose meaning and meaningful statements lose precision” ― Lotfi A. Zadeh http://en.wikipedia.org/wiki/Lotfi_A._Zadeh

How can you help your software team improve? This concise book introduces codermetrics, a clear and objective way to identify, analyze, and discuss the successes and failures of software engineers—not as part of a performance review, but as a way to make the team a more cohesive and productive unit. Experienced team builder Jonathan Alexander explains how codermetrics helps teams understand exactly what occurred during a project, and enables each coder to focus on specific improvements.

Four common pitfalls in using software metrics for project management

There is a clear growing interest in the decision processes and data mining. For example, here's a new Springer Journal (that is all open content).

The "R" toolkit lets you generate impressive and informative visualizations of complex data.

Many claims are made about how certain tools, technologies, and practices improve software development. But which claims are verifiable, and which are merely wishful thinking? In... - Selection from Making Software [Book]