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ResearchSpace@Auckland

Formal verification of biologically inspired computing models

Abstract

dc:description.abstract

As a recently proposed biologically inspired computing model, cP systems can solve computationally hard problems in polynomial - often linear or sublinear - time. Similar to other membrane computing models, cP systems work in an ideal way, having unlimited space and computing power. This thesis discusses the formal verification of cP systems. cP systems support labelled multiset-based terms and generic rewriting rules. To apply a rule, variable terms in its lhs (left-hand-side) and promoters need to be unified against system terms. Although several first-order unification algorithms were proposed in previous work, none of them can be readily applied to cP systems due to the use of labelled and nested multisets. In order to solve the issue, we formally defined the unification problem for labelled multisets and proposed a corresponding algorithm, namely LNMU. This can solve well-formed labelled multiset unification problems in linear time. To verify cP systems, both model checking and interactive theorem proving are considered in this thesis. By using formal tools including PAT3, ProB, and Coq, several cP systems were verified including two NPC solutions proposed in this study. These are: ΠSSP - a cP system that solves the subset sum problem in linear time, and Π Sudoku - a cP system that solves Sudoku (m * m) in sublinear time. In order to automate the verification process, we proposed several mapping guidelines, which can be used to transform cP system notation into modelling languages including CSP#, B, and Gallina automatically. Using existing general purpose formal tools to verify cP systems often requires human intervention. Furthermore, it is extremely hard to completely model cP systems with complex generic rules in third-party verifiers. In order to overcome these limitations, we designed and implemented a domain-specific formal framework for cP system simulation and verification, namely cPV. By implementing LNMU in an optimised way, cPV can efficiently simulate and verify cP systems. System properties including deadlockfreeness, confluence, termination, determinism, and goal reachability can be automatically verified in cPV. We also presented a new research direction: using cP systems as a theorem proving tool. A cP system that can efficiently perform equational deduction was proposed. Using certain cP system friendly encodings and the power of maximal parallelism, the cP system can be exponentially faster than traditional rewrite systems when proving equational theories.

Degree

thesis:*
Name thesis:degree_name
PhD
Level thesis:degree_level
Doctoral
Discipline thesis:degree_discipline
Computer Science
Grantor dc:publisher
ResearchSpace@Auckland
Year dc:date.issued
2022

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Liu, Yezhou
Advisors dc:contributor.advisor
  • Sun, Jing
  • Nicolescu, Radu

Rights

dc:rights
Statement dc:rights
  • Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/2292/63353
OAI identifier oai:identifier
oai:researchspace.auckland.ac.nz:2292/63353

Chain of custody

source
Harvested from
University of Auckland
Base URL
researchspace.auckland.ac.nz/server/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
related terms
citation

Liu, Yezhou. Formal verification of biologically inspired computing models. Doctoral thesis, ResearchSpace@Auckland, 2022. https://hdl.handle.net/2292/63353