Metrics blog

• New from ML? June 11, 2021
  I seldom write about films and events, well maybe actually never, but this year, a lot has happened in the online way. What’s new in Machine Learning | Keynote – YouTube The video above is about the news from Google about their TensorFlow library, which include new ways of training models, compression and performance tuning […]
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• Assessing the maturity of a metric team June 4, 2021
  https://doi.org/10.1016/j.jss.2021.111006 Modern software development organizations work a lot with metrics – they use them to focus their development effort, to understand their products, and, recently, to guide their online experimentation. We’ve studied software measurement programs before, mostly from the perspective of what’s in the program – what is measured, how it is measured, who is […]
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• New programming tools? May 28, 2021
  Glinda: Supporting Data Science with Live Programming, GUIs and a Domain-specific Language (acm.org) I’m not going to add a picture here, because the actual paper contains a great picture, which is copyrighted. But, do we need another tool (I though), and if you think like that… well, think again. Once I looked at the paper, […]
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• Challenges when using ML for SE (article review) May 15, 2021
  104294.pdf (scitepress.org) Machine learning has been used in software engineering for a while now. It used to be called advanced statistics, but with the popularization of artificial intelligence, we use the term machine learning more often. I’m one of those who like to use ML. It’s actually a mesmerizing experience when you train neural networks […]
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• How much does a testing cost and how to estimate it… April 27, 2021
  CSUR5403-53 (acm.org) Testing of software systems is a task which costs a lot. As a former tester, I see this as a neverending story – you’re done with your testing, new code is added, you are not done anymore, you test more, you’re done, new code…. and so on. When I was a tester, there […]
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