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Record W2163743319 · doi:10.1007/s00165-005-0079-4

The verified software repository: a step towards the verifying compiler

2006· article· en· W2163743319 on OpenAlexfundno aff
Juan Bicarregui, C. A. R. Hoare, Jim Woodcock

Bibliographic record

VenueFormal Aspects of Computing · 2006
Typearticle
Languageen
FieldComputer Science
TopicDistributed systems and fault tolerance
Canadian institutionsnot available
FundersUniversidade Federal de PernambucoUniversity of Illinois at Urbana-ChampaignLondon South Bank UniversityMcMaster University
KeywordsComputer scienceCompilerDependabilitySoftware engineeringSoftware developmentSoftwareProgramming language

Abstract

fetched live from OpenAlex

Abstract The verified software repository is dedicated to a long-term vision of a future in which all computer systems justify the trust that society increasingly places in them. This would be accompanied by a substantial reduction in the current high costs of programming error, incurred during the design, development, testing, installation, maintenance, evolution, and retirement of computer software. An important technical contribution to this vision will be a verifying compiler: a tool-set that automatically proves that a program will always meet its specification, insofar as this has been formalised, without even needing to run it. This has been a challenge for computing research for over 30 years, but the current state of the art now gives grounds for hope that it may be implemented in the foreseeable future. Achievement of the overall vision will depend also on continued progress of research into dependability and software evolution, as envisaged by the UKCRC Grand Challenge project in dependable systems evolution . The verified software repository is a first step towards the realisation of this long-term vision. It will maintain and develop an evolving collection of state-of-the-art tools, together with a representative portfolio of real programs and specifications on which to test, evaluate, and develop the tools. It will contribute initially to the inter-working of tools, and eventually to their integration. It will promote transfer of the relevant technology to industrial tools and into software engineering practice. It will build on the recognised achievements of practical formal development of safety-critical computer applications, and contribute to an international initiative in verified software, covering theory, tools, and experimental validation.

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)0.043
metaresearch head score (Gemma)0.078
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.043
Threshold uncertainty score0.225

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0430.078
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.002
Science and technology studies0.0020.004
Scholarly communication0.0090.023
Open science0.0080.008
Research integrity0.0040.012
Insufficient payload (model declined to judge)0.0090.009

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 head0.010
GPT teacher head0.217
Teacher spread0.207 · 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 designSimulation or modeling
Domainnot available
GenreEmpirical

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

Citations47
Published2006
Admission routes1
Has abstractyes

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