Computing and Proving Well-founded Orderings through Finite Abstractions

Rob Sumners
(Centaur Technology)

A common technique for checking properties of complex state machines is to build a finite abstraction then check the property on the abstract system — where a passing check on the abstract system is only transferred to the original system if the abstraction is proven to be representative. This approach does require the derivation or definition of the finite abstraction, but can avoid the need for complex invariant definition. For our work in checking progress of memory transactions in microprocessors, we need to prove that transactions in complex state machines always make progress to completion. As a part of this effort, we developed a process for computing a finite abstract graph of the target state machine along with annotations on whether certain measures decrease or not on arcs in the abstract graph. We then iteratively divide the abstract graph by splitting into strongly connected components and then building a measure for every node in the abstract graph which is ensured to be reducing on every transition of the original system guaranteeing progress. For finite state target systems (e.g. hardware designs), we present approaches for extracting the abstract graph efficiently using incremental SAT through GL and then the application of our process to check for progress. We present an implementation of the Bakery algorithm as an example application.

In Grant Passmore and Ruben Gamboa: Proceedings of the Sixteenth International Workshop on the ACL2 Theorem Prover and its Applications (ACL2 2020), Worldwide, Planet Earth, May 28-29, 2020, Electronic Proceedings in Theoretical Computer Science 327, pp. 47–60.
Published: 29th September 2020.

ArXived at: http://dx.doi.org/10.4204/EPTCS.327.4 bibtex PDF
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