Generalized Boxings, Congruences and Partial Inlining

. We present a new technique for optimizing programs, based on data-flow analysis. The initial goal was to provide a simple way to improve on Leroy and Peyton-Jones' techniques for optimizing boxings (allocations) and unboxings (field selection) away in strongly-typed functional programs. Our techniques achieve this goal, while not needing types any more (so it applies to Lisp as well as to ML), and providing a finer analysis; moreover, our techniques also improve on classical common subexpression elimination. The methods are twofold: intraprocedurally, we use a data-flow analysis technique that propagates congruences on program variables and terms built on these variables; interprocedurally, we help the intraprocedural analysis by inlining, at least partially, all functions whose definitions are known at call sites. 1 Introduction One of the source of inefficiencies of compiled functional language implementations is the great number of boxings (allocating tuples on the heap) and unbo..