09-20, 15:50–16:25 (Europe/Amsterdam), Escher
If there is only one experience shared by anyone who ever wrote code, it is debugging. Then, why is it so often a frustrating experience, abstruse and wasteful?
It does not have to be that way. This talk will focus on methods to help with making debugging a rational, positive experience, and we will explore how debugging can even help with gaining some valuable knowledge about your codebase.
Debugging might seem like dark magic at times, but computers are behaving rationally (unless you are using a quantum computer, at least). The scientific approach used in experimental sciences can help you to understand what is happening in your mysterious codebase and to unravel the secrets of your own bit-based universe.
The focus will be on tips and methodology, not on tools, to help you being more efficient when debugging. Hopefully, I'll show how debugging can be an opportunity for improving your knowledge about your project.
Intended audience: No previous experience required; having already lost your nerves at a particularly irritating bug will help you relate :)
Sarah Diot-Girard has been working on Machine Learning since 2012, and she enjoys using data science tools to find solutions to practical problems. She is particularly interested in issues, both technical and ethical, coming from applying ML into real life. She gave talks at international conferences, about data privacy and algorithmic fairness, and software engineering best practices applied to data science. She is employed by Owkin as a maintainer of the Federated Learning platform Substra since 2023.