Software Testing and Test Effectiveness
08/23/15 • 42 min
Each episode we focus on one idea from computer science and try to understand how it fits into our world as professional programmers.
This episode we welcome our guest host, Sergey Astretsov, to discuss the paper “Coverage and Its Discontents” about the use of code coverage as a proxy for test effectiveness. From there we debate when and why to test, discuss the relationship between commenting and testing, and generally digress.
Links:
Each episode we focus on one idea from computer science and try to understand how it fits into our world as professional programmers.
This episode we welcome our guest host, Sergey Astretsov, to discuss the paper “Coverage and Its Discontents” about the use of code coverage as a proxy for test effectiveness. From there we debate when and why to test, discuss the relationship between commenting and testing, and generally digress.
Links:
Previous Episode
Deep Learning with Adam Gibson
In our second episode we interview Adam Gibson, creator of the DeepLearning4J open source project. It turns out that deep learning really is a major breakthrough for machine learning, both conceptually, and as evidenced by the benchmarks.
Links!
- Skymind (Adam’s company)
- Andrew Ng on Deep Learning
- Adam’s Slideshare
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