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Record W2052103584 · doi:10.1142/s0218194002000810

USE CASE PATTERNS

2002· article· en· W2052103584 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

VenueInternational Journal of Software Engineering and Knowledge Engineering · 2002
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Software Engineering Methodologies
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsUse Case DiagramComputer scienceUse Case PointsSoftware engineeringSet (abstract data type)Class (philosophy)Object-oriented programmingProcess (computing)SoftwareSoftware developmentUnified Modeling LanguageSoftware development processArtificial intelligenceClass diagramProgramming language

Abstract

fetched live from OpenAlex

A use case represents a unit of the functionality specification of a system. Industrial object-oriented projects have applied use cases to capture user requirements. Use cases can be used throughout the whole process of object-oriented software development [14]. But, the problem of how to write use cases is still puzzling even software experts [6]. It reflects the lack of a systematic approach to capturing use cases. The set of use cases in a use case model is unstructured regarding the structure of the problem addressed by an application. This paper presents a notion of a use case pattern and proposes using a use case pattern to guide use case capturing. A use case pattern encodes reusable knowledge on the structure and function of a specific class of applications. It guides the work of use case gathering. We illustrate the approach to use case modeling with several use case patterns.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.449
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.042
GPT teacher head0.265
Teacher spread0.223 · 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