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Normalize lerped BoxConstraints with overshooting t values - #190971
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This pull request updates BoxConstraints.lerp to normalize the resulting constraints, ensuring that overshooting interpolation values do not produce negative or contradictory constraints. It also adds corresponding regression tests. The feedback suggests asserting the exact expected BoxConstraints values in the tests rather than just checking isNormalized to prevent silent regressions.
justinmc
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LGTM 👍 . Good call. Going negative etc. might make sense for some other values but not for BoxConstraints.
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This was referenced Aug 15, 2026
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BoxConstraints.lerp has the signature
Overshooting curves, such as
Curves.easeOutBack, extrapolate t outside of the range 0.0 to 1.0. Without normalizing, the results can be invalid, causing crashes.This PR normalizes the returned
BoxConstraints.Fixes AnimatedContainer throws Exception when animating height with easeOutBack curve.