Abstract

Data flow analysis algorithms for imperative programming languages can be split into two groups: first, into the semantic algorithms that determine semantic equivalence between terms, and second, into the syntactic algorithms that compute complex program properties based on syntactic term identity, which support powerful optimization techniques like for example partial redundancy elimination. Value Flow Graphs represent semantic equivalence of terms syntactically. This allows us to feed the knowledge of semantic equivalence into syntactic algorithms. The power of this technique, which leads to modularly extendable algorithms, is demonstrated by developing a two stage algorithm for the optimal placement of computations within a program wrt the Herbrand interpretation. 1 Introduction There are two kinds of data flow analysis algorithms for imperative programming languages. First, the semantic algorithms that determine semantic equivalence between terms, e.g. the classical algorithm of ...

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