I enjoyed Robert Musson’s recent Qasig.org presentation How Data Science is Changing Software Testing and recommend you watch it or at least read Robert’s Presentation Slides which don’t do it full justice, but should tease you.
As the abstract stated: It will describe the new skills required of test organizations and the ways individuals can begin to make the transition.
I worked with Bob a few times while at Microsoft, and he truly was one of the original Data Science testers for the past decade doing Data Analytics. He says (37:50 into video) the tide has turned recently and he has “seen more progress in last 6 months than seen in past 10 years.”
So now I need to learn
- Statistics, e.g., r-value, p-value, Poisson and Gamma distributions
Homogenous (non-changing) or Non-homogenous (changing) Poisson for reliability measurements to get me used to time analysis.
- R language (open source version of S).
Object oriented with many packages to do exploratory data analysis and quick linear models.
- Python for easier data manipulation including building dictionaries and packages for linear algebra
So I can prepare for the mindset change.
Mindset change is to one of information discovery vs. bug discovery
An audience member asked how to learn, and Bob recommended Coursera.org for many courses, including statistic courses.. He called out specifically,
Model Thinking – Scott Page – U. of Michigan.
I love models, but I might also start with