MétaCan
Menu
← Back to cohort
Record W7026469395

Abstract Formal Specification and Verification of Computational Digital Logic Systems

2025· dissertation· en· W7026469395 on OpenAlexfundno aff

Bibliographic record

VenueQSpace (Queen's University Library) · 2025
Typedissertation
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsnot available
FundersMinistry of Colleges and Universities
KeywordsCorrectnessFormal verificationComputation tree logicModel checkingFormal specificationComputational complexity theoryTemporal logicSpecification languageFormal methodsFormal language
DOInot available

Abstract

fetched live from OpenAlex

Modern computational digital logic systems, including general-purpose computer processors, make use of increasingly complex control logic and algorithms to manage the flow of data between computational elements. Formal verification methods aim to provide guarantees of correctness for this logic, but their use in practice comes with both combinatorial issues and conceptual challenges in capturing the desired behaviour in the specification language. This problem is exacerbated by the tendency to require behaviour to be specified in terms of the system state trajectory, which is often not a natural setting in which to describe the computational requirements, leading to unnecessary and problematic conceptual distance between the formal specification and the informally understood requirements. To address these issues, a novel, value-oriented approach to formal verification of these systems is proposed, which permits desired computational behaviour to be specified directly, with a conceptually simple interpretation. This approach is substantiated through an abstract modelling formalism in which computational systems can be formally described and composed from smaller components by compatibly connecting inputs and outputs; the interface of a component is described by an adapted version of polynomial functors, which captures a limited form of dependent typing that is common in real-world digital systems design. A sound but incomplete verification procedure is provided, by translating the description of each system into a novel extension of regular tree grammars which incorporates a limited form of symbolic logic and structured equality constraints, such that language inclusion implies that the system meets the specification. An inductive proof system for such language inclusion between the grammars, again sound but incomplete, is provided to enable algorithmic implementation of verification by proof search. Finally, the system descriptions are assigned category-theoretic semantics, which are used to prove the soundness of the translation to grammars and provide a formal notion of abstracting and concretizing a system between different layers of abstraction. The result of the thesis is a thorough mathematical foundation for a practical formal verification tool for computational digital logic systems. Remaining work necessary to use such a tool and address the limitations of the underlying theory in its present state is discussed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.004
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.209
Teacher spread0.198 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueQSpace (Queen's University Library)→Same topicPrenatal Screening and Diagnostics→French-language works237,207→