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capture promoted Tier 1 2026-11-05

Does any independent source corroborate Nogueira, Pattabiraman, Vieira & Campos's (arXiv:2607.02808) LLM-code failure-independence numbers?

software-reliabilityn-version-programmingcorrelated-errorsalgorithmic-monoculturesource-corroborationsingle-source-caparxiv

A dedicated search for citations, replications, or independent tests of Nogueira, Pattabiraman, Vieira & Campos's "A Systematic Methodology for Evaluating Failure Independence in LLM-Generated Code" (arXiv:2607.02808, submitted 2 Jul 2026) found one genuinely independent preprint that corroborates the paper's qualitative conclusion using its own distinct statistical machinery, but no source — independent or otherwise — that reproduces the paper's specific 0.43/0.44 reliability-gain figures.

Claim: The specific 0.43/0.44 reliability-gain figures remain single-sourced; no independent source reports or tests those exact numbers

verifies: question-corroborate-nogueira-2026-arxiv-2607-02808-single-source-cap

A citation search (web search for the paper's title, its arXiv ID, and its author names, cross-checked against the arXiv page's own "References & Citations" links to Google Scholar and Semantic Scholar) located exactly one paper that cites arXiv:2607.02808 directly: Mohamed Chahine Ghanem's "Builder, Defender, Breaker: Measurable Independence and Bounded Autonomy When Generative Models Build, Defend and Test Software" (arXiv:2607.03215), which lists it as reference [5]. That paper is a theoretical framework proposing a coincident-failure model (in the style of Eckhardt and Lee) for AI-generated build/defend/test roles, framed as testable hypotheses with a refutation protocol — it does not report an empirical replication of arXiv:2607.02808's own numbers. No other citing paper, benchmark report, or independent empirical study was found that engages with the 0.43/0.44 fractions or the "dropping below 0.3" same-model figure specifically. The number stands exactly as previously recorded: [unverified-quant — needs primary] in the sense that only the paper's own authors have produced it.

Claim: A genuinely independent, contemporaneous preprint corroborates the qualitative finding — LLM/agent-generated code does not satisfy NVP's failure-independence assumption — using a different dataset, different statistic, and different numbers

verifies: question-corroborate-nogueira-2026-arxiv-2607-02808-single-source-cap

Javier Ron, Benoit Baudry, and Martin Monperrus's "N-Version Programming with Coding Agents" (arXiv:2606.20158, KTH Royal Institute of Technology and Université de Montréal, submitted 18 Jun 2026 — two weeks before arXiv:2607.02808, ruling out any citation or response relationship in either direction) independently reproduces the classic Knight & Leveson multi-version-independence experiment using AI coding agents (Cursor, Claude Code, OpenAI Codex, Gemini, OpenCode; 23 underlying models; Python/Rust/Pascal) rather than LLM prompting directly. On 48 admitted implementations evaluated against a one-million-case test campaign, the paper reports: "The generated AI-agent implementations do not fail independently, according to a uniform random model. At the pooled level, the experiment produces 429 coincident-failure cases where the independence model predicts only 115.36; the null hypothesis is rejected with p ≈ 1.765 × 10−187." This is a different author group (no overlap with Nogueira, Pattabiraman, Vieira, or Campos), a different institution, and a different statistical framework (the Knight–Leveson z-statistic on binary pass/fail vectors, not a reliability-gain-fraction calculation) — it clears the independence bar the vault's single-source cap requires. It corroborates the direction and existence of the failure-independence violation that arXiv:2607.02808 reports, but not the specific 0.43/0.44 figures, which remain unique to the original paper.

Claim: The same independent preprint also corroborates, with its own distinct numbers, that redundancy still yields partial practical benefit despite the correlation

verifies: question-corroborate-nogueira-2026-arxiv-2607-02808-single-source-cap

Ron, Baudry & Monperrus report that despite the failure correlation, majority-vote redundancy still measurably helps: "across majority voting three-version units, the mean failure count drops from 387.44 for single versions to 130.99 for triples, and 11,844 N-version units exhibit zero observed failures" (of 17,296 possible three-version combinations from the 48 admitted implementations). This parallels — without matching — arXiv:2607.02808's claim that three- and five-version ensembles realize "only 0.43 and 0.44 of the reliability gain achievable under independence." Both papers converge on the same shape of finding (partial, not full, benefit from diversity) via independently-designed experiments and independently-computed statistics; this is the strongest form of corroboration currently available for arXiv:2607.02808's qualitative claim, but it is corroboration of the pattern, not of the number.

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Tier 1 Rodrigo Pato Nogueira, Karthik Pattabiraman, Marco Vieira, João R. Campos 2026-07-02
https://arxiv.org/abs/2607.02808
“N-version reliability analysis reinforces this: three- and five-version ensembles realize only 0.43 and 0.44 of the reliability gain achievable under independence, dropping below 0.3 when ensembles are built from the same model.”
written by claude-sonnet-5 · Batch capture run, 2026-11-05, following up [[question-corroborate-nogueira-2026-arxiv-2607-02808-single-source-cap]] with a dedicated citation/corroboration search. · raw markdown