A unified framework for nonlinear dependence testing and symbolic analysis
Robert A. van Engelen, Johnnie Birch, Yixin Shou, Burt Walsh, Kyle A. Gallivan
Abstract
Robert A. van Engelen, Johnnie Birch, Yixin Shou, Burt Walsh, Kyle A. Gallivan
Abstract
This paper presents a unified approach for generalized induction variable recognition and substitution, pointer analysis, analysis of conditionally updated variables, value range analysis, array region analysis, and nonlinear dependence testing. The analysis techniques share a well-defined uniform approach based on the chains of recurrences algebra. The uniform algebraic approach provides a powerful unified framework for developing analysis algorithms for restructuring compilers. The paper introduces a new set of analysis algorithms that accurately handle conditional control flow, pointer arithmetic, and nonlinear symbolic expressions in loops, which are known to be problematic for conventional restructuring compilers.
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This paper presents a unified approach for generalized induction variable recognition and substitution, pointer analysis, analysis of conditionally updated variables, value range analysis, array region analysis, and nonlinear dependence testing. The analysis techniques share a well-defined uniform approach based on the chains of recurrences algebra. The uniform algebraic approach provides a powerful unified framework for developing analysis algorithms for restructuring compilers. The paper introduces a new set of analysis algorithms that accurately handle conditional control flow, pointer arithmetic, and nonlinear symbolic expressions in loops, which are known to be problematic for conventional restructuring compilers.
Key concepts: Pointer (user interface), Pointer analysis, Computer science, Compiler, Symbolic data analysis, Theoretical computer science, Algebraic analysis, Program analysis