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 t-refined 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 (bit-vector, unidirectional, bidirectional), nondeterministic flowgraphs, t-refined flow graphs, critical edges, lifetimes of registers, com...

This paper addresses the problem of how to apply pointer analysis to a wide variety of compiler applications. We are not presenting a new pointer analysis. Rather, we focus on putting two existing pointer analyses, points-to analysis and connection analysis, to work. We demonstrate that the fundamental problem is that one must be able to compare the memory locations read/written via pointer indirections, at different program points, and one must also be able to summarize the effect of pointer references over regions in the program. It is straightforward to compute read/write sets for indirections involving stack-directed pointers using points-to information. However, for heap-directed pointers we show that one needs to introduce the notion of anchor handles into the connection analysis and then express read/write sets to the heap with respect to these anchor handles. Based on the read/write sets we show how to extend traditional optimizations like common subexpression elimination, loop...

Explanation-Based Learning (EBL) is a widely-used technique for acquiring searchcontrol knowledge. Recently, Prieditis, van Harmelen, and Bundy pointed to the similarity between Partial Evaluation (PE) and EBL. However, EBL utilizes training examples whereas PE does not. It is natural to inquire, therefore, whether PE can be used to acquire searchcontrol knowledge, and if so at what cost? This paper answers these questions by means of a case study comparing prodigy/ebl, a state-of-the-art EBL system, and static, a PEbased analyzer of problem-space definitions. When tested in prodigy/ebl's benchmark problem spaces, static generated search-control knowledge that was up to three times as effective as the knowledge learned by prodigy/ebl, and did so from twenty-six to seventyseven times faster. The paper describes static's algorithms, compares its performance to prodigy/ebl's, noting when static's superior performance will scale up and when it will not. The paper concludes with several le...

Even though impressive progress has been made...

We present an interprocedural generalization of the well-known (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 stack-based 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...

This paper presents a practical heap analysis technique, connection analysis, that can be used to disambiguate heap accesses in C programs. The technique is designed for analyzing programs that allocate many disjoint objects in the heap such as dynamically-allocated arrays in scientific programs. The method statically estimates connection matrices which encode the connection relationships between all heap-directed pointers at each program point. The results of the analysis can be used by parallelizing compilers to determine when two heapallocated objects are guaranteed to be disjoint, and thus can be used to improve array dependence and interference analysis. The method has been implemented as a context-sensitive interprocedural analysis in the McCAT optimizing/parallelizing C compiler. Experimental results are given to compare the accuracy of connection analysis versus a conservative estimate based on points-to analysis. This work supported by NSERC, FCAR, and the EPPP project (fin...

A maintainer's understanding cangoawry when it is based on purely local clues. How can we spell out the intentions behindapiece ofcode?

We apply linear algebra techniques to precise interprocedural dataflow analysis. Specifically, we describe analyses that determine for each program point identities that are valid among the program variables whenever control reaches that program point. Our analyses fully interpret assignment statements with affine expressions on the right hand side while considering other assignments as non-deterministic and ignoring conditions at branches. Under this abstraction, the analysis computes the set of all affine relations and, more generally, all polynomial relations of bounded degree precisely. The running time of our algorithms is linear in the program size and polynomial in the number of occurring variables. We also show how to deal with affine preconditions and local variables and indicate how to handle parameters and return values of procedures.

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