Better Code Reviews FTW! - Tess Ferrandez-Norlander - Swetugg Stockholm 2024

  Рет қаралды 477

Swetugg

Swetugg

4 ай бұрын

Code reviews is feedback, but if your friend or partner or colleague would ask you for feedback on some of their work, you would probably not send them a list of 50 things they did wrong. Yet in code reviews, this is perfectly normal.
Could we do better code reviews by just changing the way we give and take feedback? I'll share 10 tips that I try to follow to turn code reviews from a boring exercise or something you dread to a much more pleasant experience.
Tess is a developer/data scientist working at Microsoft. Over the past 20 years she has changed the way we do .net debugging, developed a large number of mobile apps. As of a couple of years ago she moved into the world of data science and machine learning working with a lot of the largest companies in Europe and beyond on really tough ML problems.
She has has spoken at lots and lots of conferences around the world on a wide variety of topics including deep .net debugging, UX, web development and Machine Learning. You can also find her on twitter at @TessFerrandez
This session was recorded at Swetugg Stockholm 2024, Swetugg is run by a group of volunteers with different IT backgrounds with a common denominator: A passion for creating good software and better software developers, no matter if you are just starting your journey or have been writing code since the beginning of unix time.

Пікірлер: 3
@JanekBogucki
@JanekBogucki 3 ай бұрын
Excellent presentation. I will be sharing this with my team.
@JanekBogucki
@JanekBogucki 3 ай бұрын
21:33 Nits should be fixed by the PR author to help reduce the later occurance rate of similar nits. Of course, automate first :) Great talk, thanks for sharing. Packed with useful ideas.
@JanekBogucki
@JanekBogucki 3 ай бұрын
42:17 Love the suggestions features AND the suggestion to use this. My preference is to provide an example but also to link to the relevant documentation or good blog article This turns the review comment into targeted learning.
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