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End-to-End Verification for Subgraph Solving

Gocht, Stephan LU ; McCreesh, Ciaran ; Myreen, Magnus O. ; Nordström, Jakob LU ; Oertel, Andy LU orcid and Tan, Yong Kiam (2024) 38th AAAI Conference on Artificial Intelligence, AAAI 2024 In Proceedings of the AAAI Conference on Artificial Intelligence 38. p.8038-8047
Abstract

Modern subgraph-finding algorithm implementations consist of thousands of lines of highly optimized code, and this complexity raises questions about their trustworthiness. Recently, some state-of-the-art subgraph solvers have been enhanced to output machine-verifiable proofs that their results are correct. While this significantly improves reliability, it is not a fully satisfactory solution, since end-users have to trust both the proof checking algorithms and the translation of the high-level graph problem into a low-level 0-1 integer linear program (ILP) used for the proofs. In this work, we present the first formally verified toolchain capable of full end-to-end verification for subgraph solving, which closes both of these trust... (More)

Modern subgraph-finding algorithm implementations consist of thousands of lines of highly optimized code, and this complexity raises questions about their trustworthiness. Recently, some state-of-the-art subgraph solvers have been enhanced to output machine-verifiable proofs that their results are correct. While this significantly improves reliability, it is not a fully satisfactory solution, since end-users have to trust both the proof checking algorithms and the translation of the high-level graph problem into a low-level 0-1 integer linear program (ILP) used for the proofs. In this work, we present the first formally verified toolchain capable of full end-to-end verification for subgraph solving, which closes both of these trust gaps. We have built encoder frontends for various graph problems together with a 0-1 ILP (a.k.a. pseudo-Boolean) proof checker, all implemented and formally verified in the CAKEML ecosystem. This toolchain is flexible and extensible, and we use it to build verified proof checkers for both decision and optimization graph problems, namely, subgraph isomorphism, maximum clique, and maximum common (connected) induced subgraph. Our experimental evaluation shows that end-to-end formal verification is now feasible for a wide range of hard graph problems.

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author
; ; ; ; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
End-to-End Verification for Subgraph Solving
series title
Proceedings of the AAAI Conference on Artificial Intelligence
volume
38
edition
8
pages
10 pages
conference name
38th AAAI Conference on Artificial Intelligence, AAAI 2024
conference location
Vancouver, Canada
conference dates
2024-02-20 - 2024-02-27
external identifiers
  • scopus:85189616389
ISSN
2159-5399
DOI
10.1609/aaai.v38i8.28642
language
English
LU publication?
yes
id
4c0d5226-758f-4e9c-804d-13d5c525ed39
date added to LUP
2024-04-26 14:40:57
date last changed
2024-04-26 14:41:16
@inproceedings{4c0d5226-758f-4e9c-804d-13d5c525ed39,
  abstract     = {{<p>Modern subgraph-finding algorithm implementations consist of thousands of lines of highly optimized code, and this complexity raises questions about their trustworthiness. Recently, some state-of-the-art subgraph solvers have been enhanced to output machine-verifiable proofs that their results are correct. While this significantly improves reliability, it is not a fully satisfactory solution, since end-users have to trust both the proof checking algorithms and the translation of the high-level graph problem into a low-level 0-1 integer linear program (ILP) used for the proofs. In this work, we present the first formally verified toolchain capable of full end-to-end verification for subgraph solving, which closes both of these trust gaps. We have built encoder frontends for various graph problems together with a 0-1 ILP (a.k.a. pseudo-Boolean) proof checker, all implemented and formally verified in the CAKEML ecosystem. This toolchain is flexible and extensible, and we use it to build verified proof checkers for both decision and optimization graph problems, namely, subgraph isomorphism, maximum clique, and maximum common (connected) induced subgraph. Our experimental evaluation shows that end-to-end formal verification is now feasible for a wide range of hard graph problems.</p>}},
  author       = {{Gocht, Stephan and McCreesh, Ciaran and Myreen, Magnus O. and Nordström, Jakob and Oertel, Andy and Tan, Yong Kiam}},
  booktitle    = {{End-to-End Verification for Subgraph Solving}},
  issn         = {{2159-5399}},
  language     = {{eng}},
  month        = {{03}},
  pages        = {{8038--8047}},
  series       = {{Proceedings of the AAAI Conference on Artificial Intelligence}},
  title        = {{End-to-End Verification for Subgraph Solving}},
  url          = {{http://dx.doi.org/10.1609/aaai.v38i8.28642}},
  doi          = {{10.1609/aaai.v38i8.28642}},
  volume       = {{38}},
  year         = {{2024}},
}