We provide a uniform framework for the analysis of programs with procedures and explicit, unbounded, fork/join parallelism covering not only bitvector problems like reaching definitions or live variables but also non-bitvector problems like strong copy constant propagation. Due to their structural similarity to the sequential case, the resulting algorithms are as efficient as their widely accepted sequential counterparts, and they can easily be integrated in existing program analysis environments like e.g. MetaFrame or PAG. We are therefore convinced that our method will soon find its way into industrial-scale computer systems.

We exhibit an interprocedural framework for the analysis of multi-threaded programs based on partial invariants of a new kind of constraint systems which we call side-e#ecting.

This article presents a novel generic technique for solving dataflow equations in interprocedural dataflow analysis. The technique is obtained by generalizing Newton’s method for computing a zero of a differentiable function to ω-continuous semirings. Complete semilattices, the common program analysis framework, are a special class of ω-continuous semirings. We show that our generalized method always converges to the solution, and requires at most as many iterations as current methods based on Kleene’s fixed-point theorem. We also show that, contrary to Kleene’s method, Newton’s method always terminates for arbitrary idempotent and commutative semirings. More precisely, in the latter setting the number of iterations required to solve a system of n equations is at most n.