The program dependence graph and its use in optimization

Abstract

In this paper we present an intermediate program representation, called the program dependence graph (PDG), that makes explicit both the data and control dependence5 for each operation in a program. Data dependences have been used to represent only the relevant data flow relationships of a program. Control dependence5 are introduced to analogously represent only the essential control flow relationships of a program. Control dependences are derived from the usual control flow graph. Many traditional optimizations operate more efficiently on the PDG. Since dependences in the PDG connect computationally related parts of the program, a single walk of these dependences is sufficient to perform many optimizations. The PDG allows transformations such as vectorization, that previously required special treatment of control dependence, to be performed in a manner that is uniform for both control and data dependences. Program transformations that require interaction of the two dependence types can also be easily handled with our representation. As an example, an incremental approach to modifying data dependences resulting from branch deletion or loop unrolling is introduced. The PDG supports incremental optimization, permitting transformations to be triggered by one another and applied only to affected dependences.

Framework for the Formal Specification and Verification of Security Guidelines

“…The starting key element for this step is the standard PDG that we generate from the Java program bytecode using the JOANA tool [14]. In this PDG, control and (explicit/implicit) data dependencies are captured, which constitutes a strong basis to perform a precise analysis.…”

“…• Augmented Program Dependence Graph: this component first builds the program dependence graph (PDG) from the Java bytecode (.class) using the JOANA IFC tool [14]. We have chosen the Program Dependence Graph (PDG) as the abstraction model for its ability to represent both control and (explicit/implicit) data dependencies.…”

Comparison of methods of program cycle transformation with using of the symbolic notation

“…Необходимо отме-тить, что на сегодняшний день методологический аппарат, который является неформальным и во многом зависит от людей, которые его используют, спо-собствует раннему обнаружению ошибок в программном продукте и его стабилизации, но не о гарантии отсутствия ошибок в нем. Формальные ме-тоды разделились на несколько групп: 1) инструменты, построенные на принципах абстрактной интерпретации [7] и статического анализа [5,[8][9][10]; 2) инструменты, основанные на проверке моделей [3,4]; 3) инструменты, в основе которых лежит принцип доказательства теорем [11]. Среди всех вы-шеперечисленных на практике используются только статический анализ, который позволяет выявить заранее известные паттерны ошибок в коде, но при этом не гарантирует их полное выявление и появление ложных сраба-тываний.…”

A practice-driven systematic review of dependency analysis solutions

“…Although the identified approaches are very different, these approaches share two main underlying characteristics. First, the identification and description of dependencies is bases on the Program Dependency Graph (PDG) (Ferrante et al 1987;Podgurski and Clarke 1990). PDG is a classic dependency model to identify data and control dependencies between program statement elements (variables, operators, and operands).…”