Data-flow analyses usually associate information with control flow regions. Informally, if these regions are too small, like a point between two consecutive statements, we call the analysis dense. On the other hand, if these regions include many such points, then we call it sparse. This paper presents a systematic method to build program representations that support sparse analyses. To pave the way to this framework we clarify the bibliography about well-known intermediate program representations. We show that our approach, up to parameter choice, subsumes many of these representations, such as the SSA, SSI and e-SSA forms. In particular, our algorithms are faster, simpler and more frugal than the previous techniques used to construct SSI - Static Single Information - form programs. We produce intermediate representations isomorphic to Choi et al.'s Sparse Evaluation Graphs (SEG) for the family of data-flow problems that can be partitioned per variables. However, contrary to SEGs, we can handle - sparsely - problems that are not in this family. We have tested our ideas in the LLVM compiler, comparing different program representations in terms of size and construction time. © 2014 Springer-Verlag.
CITATION STYLE
Tavares, A., Boissinot, B., Pereira, F., & Rastello, F. (2014). Parameterized construction of program representations for sparse dataflow analyses. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8409 LNCS, pp. 18–39). Springer Verlag. https://doi.org/10.1007/978-3-642-54807-9_2
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