Risk Assessment in Code
The discussion highlights the integration of machine learning in code reviews, emphasizing the importance of human oversight. By analyzing both code properties and the social context of contributors, the system can better assess risk levels associated with pull requests. Experience and familiarity with the codebase play a crucial role in determining the likelihood of defects, suggesting a nuanced approach to automated reviews.In this clip
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SE Radio 554: Adam Tornhill on Behavioral Code Analysis
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