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Hyperparameter Optimization for AST Differencing
Computing the differences between two versions of the same program is an
essential task for software development and software evolution research. AST
differencing is the most advanced way of doing so, and an active research area.
Yet, AST differencing still relies on default configurations or manual
tweaking. In this paper we present a novel approach named DAT for
hyperparameter optimization of AST differencing. We thoroughly state the
problem of hyper configuration for AST differencing. We show that our
data-driven approach to hyperoptimize AST differencing systems increases the
edit-script quality in up to 53% of cases