Effect Sizes for Research: A Broad Practical Approach

By K. Goulden. 2006

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When and Why Your Code Starts to Smell Bad (and Whether the Smells Go Away) (2017, unknown): “We follow the guidelines provided by Grissom and Kim [31] to interpret the effect size values: small for d < 0:33 (positive as well as negative values), medium for 0:33 d < 0:474 and large for d 0:474.”
On the diffuseness and the impact on maintainability of code smells: a large scale empirical investigation (2017, methodology): “We estimated the magnitude of the measured differences by using the Cliff’s Delta (or d ), a non-parametric effect size measure (Grissom and Kim 2005) for ordinal data.”