ing with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Publications Dept, ACM Inc., fax + 1 (212) 869-0481, or permissions@acm.org. Context-Insensitive Alias Analysis Reconsidered Erik Ruf erikruf@microsoft.com Abstract Recent work on alias analysis in the presence of pointers has concentrated on context-sensitive interprocedural analyses, which treat multiple calls to a single procedure independently rather than constructing a single approximation to a procedure's effect on all of its callers. While contextsensitive modeling offers the potential for greater precision by considering only realizable call-return paths, its empirical benefits have yet to be measured. This paper compares the precision of a simple, efficient, context-insensitive points-to analysis for the C programming language with that of a maximally context-sensitive version of the same...

Relevant context inference (RCI) is a modular technique for flow- and context-sensitive data-flow analysis of statically typed object-oriented programming languages such as C ++ and Java. RCI can be used to analyze complete programs as well as incomplete programs such as libraries; this approach does not require that the entire program be memoryresident during the analysis. RCI is presented in the context of points-to analysis for a realistic subset of C ++ . The empirical evidence obtained from a prototype implementation argues the effectiveness of RCI. 1 Introduction Points-to analysis [EGH94] for statically typed objectoriented programming languages (e.g., Java, C ++ ) determines, at each program point, the objects to which a pointer may point during execution. This information is crucial to many applications, including static resolution of dynamically dispatched calls, side-effect analysis, data-flow-based testing, program slicing and aggressive compiler optimizations. The s...

This paper presents an overview of automatic program parallelization techniques. It covers dependence analysis techniques, followed by a discussion of program transformations, including straight-line code parallelization, do loop transformations, and parallelization of recursive routines. The last section of the paper surveys several experimental studies on the effectiveness of parallelizing compilers.

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...

In this paper we present a modular interprocedural pointer analysis algorithm based on access-paths for C programs. We argue that access paths can reduce the overhead of representing context-sensitive transfer functions and effectively distinguish non-recursive heap objects. And when the modular analysis paradigm is used together with other techniques to handle type casts and function pointers, we are able to handle significant programs like those in the SPECcint92 and SPECcint95 suites. We have implemented the algorithm and tested it on a Pentium II 450 PC running Linux. The observed resource consumption and performance improvement are very encouraging.

This paper presents an extensive empirical evaluation of an interprocedural parallelizing compiler, developed as part of the Stanford SUIF compiler system. The system incorporates a comprehensive and integrated collection of analyses, including privatization and reduction recognition for both array and scalar variables, and symbolic analysis of array subscripts. The interprocedural analysis framework is designed to provide analysis results nearly as precise as full inlining but without its associated costs. Experimentation with this system shows that it is capable of detecting coarser granularity of parallelism than previously possible. Specifically, it can parallelize loops that span numerous procedures and hundreds of lines of codes, frequently requiring modifications to array data structures such as privatization and reduction transformations. Measurements from several standard benchmark suites demonstrate that an integrated combination of interprocedural analyses can substantially ...

To exploit instruction level parallelism, compilers for VLIW and superscalar processors often employ static code scheduling. However, the available code reordering may be severely restricted due to ambiguous dependences between memory instructions. This paper introduces a simple hardware mechanism, referred to as the memory con ict bu er, which facilitates static code scheduling in the presence of memory store/load dependences. Correct program execution is ensured by the memory con ict bu er and repair code provided by the compiler. With this addition, signi cant speedup over an aggressivecodescheduling model can be achieved for both non-numerical and numerical programs. 1

To function on programs written in languages such as C that make extensive use of pointers, automated software engineering tools require safe alias information. Existing alias-analysis techniques that are sufficiently efficient for analysis on large software systems may provide alias information that is too imprecise for tools that use it: the imprecision of the alias information may (1) reduce the precision of the information provided by the tools and (2) increase the cost of the tools. This paper presents a flow-insensitive, context-sensitive points-to analysis algorithm that computes alias information that is almost as precise as that computed by Andersen's algorithm -- the most precise flow- and contextinsensitive algorithm -- and almost as efficient as Steensgaard's algorithm -- the most efficient flow- and context-insensitive algorithm. Our empirical studies show that our algorithm scales to large programs better than Andersen's algorithm and show that flow-insensitive alias an...

This article presents a testing methodology that adapts data flow adequacy criteria and coverage monitoring to the task of testing spreadsheets. To accommodate the evaluation model used with spreadsheets, and the interactive process by which they are created, our methodology is incremental. To accommodate the users of spreadsheet languages, we provide an interface to our methodology that does not require an understanding of testing theory. We have implemented our testing methodology in the context of the Forms/3 visual spreadsheet language. We report on the methodology, its time and space costs, and the mapping from the testing strategy to the user interface. In an empirical study, we found that test suites created according to our methodology detected, on average, 81% of the faults in a set of faulty spreadsheets, significantly outperforming randomly generated test suites

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