Cache behavior prediction by abstract interpretation

Abstract interpretation is a technique for the static detection of dynamic properties of programs. It is semantics-based, that is, it computes approximative properties of the semantics of programs. On this basis, it allows for correctness proofs of analyses. It replaces commonly used ad hoc techniques by systematic, provable ones, and it allows the automatic generation of analyzers from specifications as in the Program Analyzer Generator (PAG). In this paper, abstract interpretation is applied to the problem of predicting the cache behavior of programs. Abstract semantics of machine programs are defined which determine the contents of caches. For interprocedural analysis, existing methods are examined and a new approach that is especially tailored for the cache analysis is presented. This allows for a static classification of the cache behavior of memory references of programs. The calculated information can be used to sharpen worst-case execution time estimations. It is possible to analyze instruction, data, and combined instruction/data caches for common (re)placement and write strategies. Experimental results are presented that demonstrate the applicability of the analysis.