On multiphase-linear ranking functions

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Abstract

Multiphase ranking functions (MΦRFs) were proposed as a means to prove the termination of a loop in which the computation progresses through a number of “phases”, and the progress of each phase is described by a different linear ranking function. Our work provides new insights regarding such functions for loops described by a conjunction of linear constraints (single-path loops). We provide a complete polynomial-time solution to the problem of existence and of synthesis of MΦRF of bounded depth (number of phases), when variables range over rational or real numbers; a complete solution for the (harder) case that variables are integer, with a matching lower-bound proof, showing that the problem is coNP-complete; and a new theorem which bounds the number of iterations for loops with MΦRFs. Surprisingly, the bound is linear, even when the variables involved change in non-linear way. We also consider a type of lexicographic ranking functions more expressive than types of lexicographic functions for which complete solutions have been given so far. We prove that for the above type of loops, lexicographic functions can be reduced to MΦRFs, and thus the questions of complexity of detection, synthesis, and iteration bounds are also answered for this class.

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Ben-Amram, A. M., & Genaim, S. (2017). On multiphase-linear ranking functions. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10427 LNCS, pp. 601–620). Springer Verlag. https://doi.org/10.1007/978-3-319-63390-9_32

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