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Causal Models for Software Cost Prediction & Control

Poster
This poster provides an update on ongoing research to use causal learning in software cost prediction.
Publisher

Software Engineering Institute

Abstract

To reduce costs, the causes of an outcome (good or bad) need to be considered. Correlations are insufficient due to Simpson’s Paradox. Causal learning identifies when factors such as team membership explain away (or mediate) correlations, and it works for much more complicated datasets too.