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Record W816408658

Mise En Scene: Conversion of Scenarios to CSP Traces for the Requirements-To-Design-To-Code Project

2013· book· en· W816408658 on OpenAlex
Carter. John D., William B. Gardner, James L. Rash, Mike Hinchey

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

VenueNASA Technical Reports Server (NASA) · 2013
Typebook
Languageen
FieldComputer Science
TopicAdvanced Software Engineering Methodologies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsNotationComputer scienceTRACE (psycholinguistics)Programming languageCommunicating sequential processesCode (set theory)ScheduleSoftware engineeringSemantics (computer science)Operating systemSet (abstract data type)
DOInot available

Abstract

fetched live from OpenAlex

The Requirements-to-Design-to-Code (R2D2C) project at NASA's Goddard Space Flight Center is based on deriving a formal specification expressed in Communicating Sequential Processes (CSP) notation from system requirements supplied in the form of CSP traces. The traces, in turn, are to be extracted from scenarios, a user-friendly medium often used to describe the required behavior of computer systems under development. This work, called Mise en Scene, defines a new medium (Scenario Notation Language, SNL) suitable for control-dominated systems, coupled with a two-stage process for automatic translation of scenarios to a new trace medium (Trace Notation Language, TNL) that encompasses CSP traces. Mise en Scene is offered as an initial solution to the problem of the scenarios-to-traces D2 phase of R2D2C. A survey of the scenario concept and some case studies are also provided.

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)0.004
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.153
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0030.002
Research integrity0.0010.001
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 head0.088
GPT teacher head0.343
Teacher spread0.255 · 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