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Record W1258088647 · doi:10.5220/0002371301900195

USE CASE BASED REQUIREMENTS VERIFICATION - Verifying the Consistency between Use Cases and Assertions

2007· article· en· W1258088647 on OpenAlex
Stéphane S. Somé, Divya K. Nair

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
TopicAdvanced Software Engineering Methodologies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsComputer scienceConsistency (knowledge bases)Programming languageFormal verificationSoftware engineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Use cases and operations are complementary requirements artefacts. A use case refers to operations and imposes their sequencing. Use cases templates usually include assertions such as preconditions, postconditions and invariants. Similarly operations are specified using contracts consisting in preconditions and postconditions. In this paper, we present an approach aiming at checking the consistency of each description against the other. We attempt to answer questions such as the following. Is the use case postcondition guaranteed by the operations? Are all operations possible according to their preconditions? We provide answers to these questions by deriving state predicates corresponding to each step in a use case, and by showing the satisfaction of assertions according to these predicates. 1

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.348
Threshold uncertainty score0.611

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
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 head0.297
GPT teacher head0.374
Teacher spread0.076 · 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