Engineers and scientists love to measure. We measure complexity of software, its performance, size and maintainability (just to name a few). We need these measurements in order to construct software, manager organizations or release high quality, high reliable products. However, there is a difference between measuring software aspects and using the measures in decision processes. In this talk, we present the concept of measurement program, measurement system, information quality and indicator-triggered decisions. We show what to consider when setting up measurement programs and provide a hints about the costs and benefits of having the program. We end the talk with presenting recent research results from Software Center, where we combine measurements and machine learning to speed-up software development.
Another version of this webinar can be found on the ACM website, where we focused mostly on the factors related to infrastructure and assessment of the measurement programs.
And finally, here is a 2018 video about using ML in measurement programs, presented at Microsoft Research.