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Record W2051185212 · doi:10.1109/mc.2008.37

A Product-Focused Approach to Software Certification

2008· article· en· W2051185212 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueComputer · 2008
Typearticle
Languageen
FieldEngineering
TopicSafety Systems Engineering in Autonomy
Canadian institutionsMcMaster University
Fundersnot available
KeywordsCertificationComputer scienceProduct (mathematics)Process (computing)Software qualitySoftwareProduct certificationSoftware quality controlProcess managementEngineering managementRisk analysis (engineering)Software engineeringComputer securitySoftware developmentBusinessEngineeringManagement

Abstract

fetched live from OpenAlex

The self-regulation of critical products doesn't work - certification by overseeing bodies is necessary. As software invades more areas of everyday life, certification of systems containing software is increasingly important for governments, industry, and consumers alike. Even if an organization isn't worried about safety, it must consider the consequences of using mission-critical software that isn't certified or qualified as fit for purposes. The US Sarbanes-Oxley Act of 2002, for example, imposes stringent requirements on companies' financial IT systems. Many standards bodies and licensing authorities describe attributes of processes by which software should be developed to meet certain standards or certification criteria. However, a good process on its own doesn't necessarily result in high-quality software. Standards and certification processes should be primarily product-focused rather than process-based to raise the certainty in evaluation of software reliability. Evaluations should be based on direct evidence about the product's attributes, not circumstantial evidence about the process.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.709
Threshold uncertainty score0.566

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.025
GPT teacher head0.184
Teacher spread0.159 · 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