Suggesting Fixes during Code Review with ML
- Track: ML on Code devroom
- Room: H.2213
- Day: Sunday
- Start: 09:50
- End: 10:30
![](/2019/schedule/event/ml_on_code_code_review_suggestions/ml_on_code_code_review_suggestions-84018897cdf7f5c7bd79bb1959b22a8901ece8266e0833d91650e291a3ddd264.png)
Many developers hate doing code reviews. Reading foreign code is hard, and suggesting improvements is even harder. Yet a dramatic portion of code review time goes to figuring out the boring details: formatting, naming, microoptimizations and best practices. We believe that all of those can be automated with ML on Code, either learning from a particular project or from all the open source code in the world which is relevant. This talk will be about open source "analyzers" - ML-driven code review agents which deal with the boring but important details.
Speakers
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Vadim Markovtsev |