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Record W1491459646 · doi:10.1109/sefm.2004.18

Formal derivation of functional architectural design

2004· article· en· W1491459646 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

VenueSoftware Engineering and Formal Methods · 2004
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Software Engineering Methodologies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsComputer scienceFunctional requirementArchitectural geometryComponent (thermodynamics)Architectural patternSoftware engineeringArchitectural designFormal specificationMainstreamSystems engineeringSoftware designProgramming languageSoftwareArchitectureSoftware developmentEngineeringSoftware construction

Abstract

fetched live from OpenAlex

One of the drawbacks of mainstream design methods is that their processes are based on crafty procedures rather than on rigorous mathematically founded procedures. Software designers spend a lot of time attempting to come up with an Architectural Design that is very often inefficient and not directly and systematically derived from the requirements. The lack of a systematic and a mathematical way to decompose the requirements into simpler pieces (components) leads to inconsistency of different parts of the designed system. This paper proposes a two stages architectural design as well as attempts to answer the following questions: (1) How can we derive the functional structure of the system (i.e., functional architectural design) from its functional requirements? (2) What are the mathematical properties of an architectural component? (3) What kind of connectors might we have between these components? We adopt a state-oriented relational approach to the specification of the requirements and to the specification and the derivation of the architectural design.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.459
Threshold uncertainty score0.787

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.044
GPT teacher head0.294
Teacher spread0.250 · 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