<ul><li>Code review is crucial in software engineering for maintaining quality and collaboration.</li><li>Many industrial Merge Request (MR) workflows deviate from standard review processes, with a significant percentage serving non-review purposes.</li><li>Identified seven categories of deviations in MRs, occurring in 37.02% of cases, and proposed a few-shot learning detection method with 91% accuracy.</li><li>Excluding deviations improves ML models predicting review completion time, enhancing performance and shifting feature importance significantly.</li></ul>

On The Impact of Merge Request Deviations on Code Review Practices

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