The window is closing, and the idea that a Kolmogorov-Smirnov test alone embodies a methodology is an imprudent consumption of our limited resources.
This test only measures a distributional similarity, not proof of robust performance, especially if the input data are biased by unaddressed biases.
For example, unadjusted venture capital fund returns in Hong Kong for cross-border liquidity effects will only give an illusion of validity.
Interpreting it as proof of robustness is a costly distraction, forcing us to ration our attention on more fundamental analyses.