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Record W2118477958 · doi:10.1142/s021819400300124x

A BUSINESS PROCESS CENTERED SOFTWARE ANALYSIS METHOD

2003· article· en· W2118477958 on OpenAlexaff
JINGZHOU LI, Brien Maguire, Yiyu Yao

Bibliographic record

VenueInternational Journal of Software Engineering and Knowledge Engineering · 2003
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Process Modeling and Analysis
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsComputer scienceBusiness process modelingArtifact-centric business process modelBusiness processSoftware engineeringWorkflowBusiness Process Model and NotationProcess modelingBusiness process discoveryBusiness process managementProcess (computing)Business logicProcess managementSystems engineeringDatabaseProgramming languageWork in processEngineering

Abstract

fetched live from OpenAlex

Based on the requirements arising from process-centered organizations and because of the lack of process modeling mechanisms in traditional software development methods, this paper presents a Business Process-centered Software Analysis method (BPSA), which supports the modeling of business process control logic. As a method, BPSA is composed of two main parts: a model and the steps of how to model the requirements using this model. The model includes the functional, informational and organizational aspects as well as the behavioral aspect that provides the mechanism for modeling the process control logic. The event mechanism is employed in this method as a main technique for modeling the control aspect of business processes. This method is based on technologies such as Structured Analysis, OOA & OOD, Workflow, XML, and has been used in the development of several medium and large information systems, proving to be both useful and effective.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0050.002
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.004

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 head0.011
GPT teacher head0.249
Teacher spread0.238 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2003
Admission routes1
Has abstractyes

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