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Record W2896097868 · doi:10.1109/modre.2018.00007

Modelling and Testing Requirements via Executable Abstract State Machines

2018· article· en· W2896097868 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSoftware Testing and Debugging Techniques
Canadian institutionsYork University
Fundersnot available
KeywordsEiffelComputer scienceExecutableProgramming languageFormal specificationNotationSoftware engineeringObject-oriented programmingMathematics

Abstract

fetched live from OpenAlex

We describe a method and tools for deriving specification models from requirements, and for validating that the final software product satisfies the requirements. ETF (Eiffel Testing Framework) is a tool for generating code from an abstract grammar specification of user interface actions derived from the requirements document. Mathmodels extends the classical Eiffel contracting notation with the use of mathematical models (based on sets, sequences, relations, functions, bags). The Mathmodels library has immutable queries (for specifications) as well as relatively efficient mutable commands (for describing executable abstract state machines). Models are developed and validated using the industrial strength Eiffel IDE, and the use of these tools thus scale up to the development of large systems in a way that supports the derivation of specification models from requirements, and seamlessness between models and code.

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: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.931
Threshold uncertainty score0.402

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 head0.070
GPT teacher head0.294
Teacher spread0.224 · 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