Pith Number

pith:XID6Z2NG

pith:2026:XID6Z2NG6QL33CP5CHKEHRGDC7

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Graph Construction and Matching for Imperative Programs using Neural and Structural Methods

Arshad Beg, Diarmuid O'Donoghue, Rosemary Monahan

A pipeline builds consistent typed and attributed graphs from imperative programs across C, Java, and Dafny by combining abstract syntax tree parsing with neural embeddings.

arxiv:2604.26578 v2 · 2026-04-29 · cs.SE · cs.AI

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\pithnumber{XID6Z2NG6QL33CP5CHKEHRGDC7}

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Record completeness

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2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

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The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

Our results show that consistent graph representations can be constructed across different languages and annotation styles. This work provides a practical basis for future steps in semantic enrichment and approximate graph matching for scalable verification artefact reuse.

C2weakest assumption

That combining AST parsing with semantic embeddings from SentenceTransformer and CodeBERT produces graph representations that capture both structural relationships and semantic context sufficiently well to enable future approximate graph matching for verification reuse.

C3one line summary

A pipeline converts programs with annotations into typed attributed graphs using AST parsing and neural embeddings to support verification artefact reuse across languages.

References

15 extracted · 15 resolved · 1 Pith anchors

[1] In: International Conference on Computational Creativity (ICCC) 2021

[2] Ali SJ, Naganathan V, Bork D (2024) Establishing traceability between natural language requirements and software artifacts by combining RAG and llms. In: Maass W, Han H, Yasar H, Multari NJ (eds) Conc 2024 · doi:10.1007/978-3-031-75872-0_16

[3] Beg A, O’Donoghue D, Monahan R (2026) Learning-infused formal reason- ing: From contract synthesis to artifact reuse and formal semantics. URL https://arxiv.org/abs/2602.02881, vERIF AI-2026: The Inte 2026

[4] Short Version of VERIFAI2026 Paper -- Learning Infused Formal Reasoning: Contract Synthesis, Artefact Reuse and Semantic Foundations 2026 · arXiv:2604.12747

[5] In: Kosmatov N, Graph Construction and Matching for Imperative Programs 19 Kovács L (eds) Integrated Formal Methods, Springer Nature Switzerland, Cham, pp 307–325 2025

Receipt and verification

First computed	2026-05-20T00:01:42.159417Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

ba07ece9a6f417bd89fd11d443c4c317edbc0ba348574893bbb412bb37f5aef3

Aliases

arxiv: 2604.26578 · arxiv_version: 2604.26578v2 · doi: 10.48550/arxiv.2604.26578 · pith_short_12: XID6Z2NG6QL3 · pith_short_16: XID6Z2NG6QL33CP5 · pith_short_8: XID6Z2NG

Agent API

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/XID6Z2NG6QL33CP5CHKEHRGDC7 \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: ba07ece9a6f417bd89fd11d443c4c317edbc0ba348574893bbb412bb37f5aef3

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "204ff1f822c31cb1eb602a14020aa05c2c5dfd187d6255339060daf412f03453",
    "cross_cats_sorted": [
      "cs.AI"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.SE",
    "submitted_at": "2026-04-29T11:59:53Z",
    "title_canon_sha256": "725924dfe6c3bca06e12b9cb5a8658b63be033314db1ab4580234fd891c9833f"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2604.26578",
    "kind": "arxiv",
    "version": 2
  }
}