Results 1 
3 of
3
Optimal Code Motion: Theory and Practice
, 1993
"... An implementation oriented algorithm for lazy code motion is presented that minimizes the number of computations in programs while suppressing any unnecessary code motion in order to avoid superfluous register pressure. In particular, this variant of the original algorithm for lazy code motion works ..."
Abstract

Cited by 112 (18 self)
 Add to MetaCart
An implementation oriented algorithm for lazy code motion is presented that minimizes the number of computations in programs while suppressing any unnecessary code motion in order to avoid superfluous register pressure. In particular, this variant of the original algorithm for lazy code motion works on flowgraphs whose nodes are basic blocks rather than single statements, as this format is standard in optimizing compilers. The theoretical foundations of the modified algorithm are given in the first part, where trefined flowgraphs are introduced for simplifying the treatment of flowgraphs whose nodes are basic blocks. The second part presents the `basic block' algorithm in standard notation, and gives directions for its implementation in standard compiler environments. Keywords Elimination of partial redundancies, code motion, data flow analysis (bitvector, unidirectional, bidirectional), nondeterministic flowgraphs, trefined flow graphs, critical edges, lifetimes of registers, com...
The Interprocedural Coincidence Theorem
 In Int. Conf. on Comp. Construct
, 1992
"... We present an interprocedural generalization of the wellknown (intraprocedural) Coincidence Theorem of Kam and Ullman, which provides a sufficient condition for the equivalence of the meet over all paths (MOP ) solution and the maximal fixed point (MFP ) solution to a data flow analysis problem. Th ..."
Abstract

Cited by 85 (11 self)
 Add to MetaCart
We present an interprocedural generalization of the wellknown (intraprocedural) Coincidence Theorem of Kam and Ullman, which provides a sufficient condition for the equivalence of the meet over all paths (MOP ) solution and the maximal fixed point (MFP ) solution to a data flow analysis problem. This generalization covers arbitrary imperative programs with recursive procedures, global and local variables, and formal value parameters. In the absence of procedures, it reduces to the classical intraprocedural version. In particular, our stackbased approach generalizes the coincidence theorems of Barth and Sharir/Pnueli for the same setup, which do not properly deal with local variables of recursive procedures. 1 Motivation Data flow analysis is a classical method for the static analysis of programs that supports the generation of efficient object code by "optimizing" compilers (cf. [He, MJ]). For imperative languages, it provides information about the program states that may occur at s...
Lazy Strength Reduction
 Journal of Programming Languages
"... We present a bitvector algorithm that uniformly combines code motion and strength reduction, avoids superfluous register pressure due to unnecessary code motion, and is as efficient as standard unidirectional analyses. The point of this algorithm is to combine the concept of lazy code motion of [1] ..."
Abstract

Cited by 23 (8 self)
 Add to MetaCart
We present a bitvector algorithm that uniformly combines code motion and strength reduction, avoids superfluous register pressure due to unnecessary code motion, and is as efficient as standard unidirectional analyses. The point of this algorithm is to combine the concept of lazy code motion of [1] with the concept of unifying code motion and strength reduction of [2, 3, 4, 5]. This results in an algorithm for lazy strength reduction, which consists of a sequence of unidirectional analyses, and is unique in its transformational power. Keywords: Data flow analysis, program optimization, partial redundancy elimination, code motion, strength reduction, bitvector data flow analyses. 1 Motivation Code motion improves the runtime efficiency of a program by avoiding unnecessary recomputations of a value at runtime. Strength reduction improves runtime efficiency by reducing "expensive" recomputations to less expensive ones, e.g., by reducing computations involving multiplication to computat...