Elimination algorithms for data flow analysis

Abstract

A unified model of a family of data flow algorithms, called elimination methods, is presented. The algorithms, which gather information about the definition and use of data in a program or a set of programs, are characterized by the manner in which they solve the systems of equations that describe data flow problems of interest. The unified model provides implementation-independent descriptions of the algorithms to facilitate comparisons among them and illustrate the sources of improvement in worst case complexity bounds. This tutorial provides a study in algorithm design, as well as a new view of these algorithms and their interrelationships.

Static Detection of Access Anomalies in Ada95

“…Given a CFG(t) = (N, E, r) of a task body t, the basis for the data flow framework are standard equations [21] of the form S out (n) = Gen(n) ∪ (S in (n) \ Kill(n))…”

“…[21] for a survey of elimination methods). As a preliminary step we need a normal form for our equations.…”

A New Elimination-Based Data Flow Analysis Framework Using Annotated Decomposition Trees

“…For simple data-flow analysis problems the fixpoint operation is quite often the identity function [19].…”

“…Elimination-based approaches [19] are used for data flow analysis problems [17,18,15,5,3,4] that cannot be solved with iterative approaches [12,8]. There exist other applications for elimination methods, which go beyond the area of program analysis [24].…”

A Framework for CFG-Based Static Program Analysis of Ada Programs

“…Many control and data flow analysis approaches [1][2][3][4][5][6] rely on the representation of a program in form of a control flow graph (CFG) [7].…”