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Record W2119686964 · doi:10.1109/wcre.2008.12

Detecting Clones in Business Applications

2008· article· en· W2119686964 on OpenAlexaff
Jin Guo, Ying Zou

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Research
Canadian institutionsQueen's University
Fundersnot available
KeywordsBusiness ruleBusiness process modelingComputer scienceArtifact-centric business process modelBusiness processBusiness process discoveryBusiness process managementBusiness domainBusiness Process Model and Notationclone (Java method)Source codeBusiness logicSoftware engineeringOpen sourceBusiness analysisDatabaseBusiness modelSoftwareOperating systemBusinessWork in processMarketing

Abstract

fetched live from OpenAlex

A business application automates a collection of business processes. A business process describes how a set of logically related tasks are executed, ordered and managed by following business rules to achieve business objectives. An online bookstore business application contains several tasks such as buying a book, ordering a book, and sending out promotions. Business analysts specify business tasks and software developers implement these tasks. Throughout the lifetime of a business application, business analysts may clone (e.g., copy and slightly modify) business processes to handle special circumstances or promotions. Identifying these clones and removing them helps improve the efficiency of an organization. However most clone detection techniques are source code based not business process based. In this paper, we propose an approach that makes use of traditional source code detection techniques to detect clones in business applications. The effectiveness of our approach is demonstrated through a case study on 10 large open source business applications in the Apache Open for Business Project.

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 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)0.000
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: Empirical · Consensus signal: none
Teacher disagreement score0.824
Threshold uncertainty score0.147

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.026
GPT teacher head0.262
Teacher spread0.236 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations20
Published2008
Admission routes1
Has abstractyes

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