On Singleton Self-Loop Removal for Termination of LCTRSs with Bit-Vector Arithmetic

07/26/2023
by   Ayuka Matsumi, et al.
0

As for term rewrite systems, the dependency pair (DP, for short) framework with several kinds of DP processors is useful for proving termination of logically constrained term rewrite systems (LCTRSs, for short). However, the polynomial interpretation processor is not so effective against LCTRSs with bit-vector arithmetic (BV-LCTRSs, for short). In this paper, we propose a novel DP processor for BV-LCTRSs to solve a singleton DP problem consisting of a dependency pair forming a self-loop. The processor is based on an acyclic directed graph such that the nodes are bit-vectors and any dependency chain of the problem is projected to a path of the graph. We show a sufficient condition for the existence of such an acyclic graph, and simplify it for a specific case.

READ FULL TEXT
research
09/01/2023

Improving Dependency Tuples for Almost-Sure Innermost Termination of Probabilistic Term Rewriting

Recently, we adapted the well-known dependency pair (DP) framework to a ...
research
07/19/2023

Dependency Tuples for Almost-Sure Innermost Termination of Probabilistic Term Rewriting (Short WST Version)

Dependency pairs are one of the most powerful techniques to analyze term...
research
02/19/2018

Transforming Dependency Chains of Constrained TRSs into Bounded Monotone Sequences of Integers

In the dependency pair framework for proving termination of rewriting sy...
research
10/30/2019

Formalizing the Dependency Pair Criterion for Innermost Termination

Rewriting is a framework for reasoning about functional programming. The...
research
06/02/2019

Ara: A 1 GHz+ Scalable and Energy-Efficient RISC-V Vector Processor with Multi-Precision Floating Point Support in 22 nm FD-SOI

In this paper, we present Ara, a 64-bit vector processor based on the ve...
research
07/19/2023

Proving Non-Termination by Acceleration Driven Clause Learning (Short WST Version)

We recently proposed Acceleration Driven Clause Learning (ADCL), a novel...

Please sign up or login with your details

Forgot password? Click here to reset