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Record W2037276439 · doi:10.1109/soca.2012.6449448

Extracting RESTful services from Web applications

2012· article· en· W2037276439 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWeb Data Mining and Analysis
Canadian institutionsQueen's University
Fundersnot available
KeywordsComputer scienceWeb serviceWorld Wide WebReuseWeb modelingWeb developmentWeb standardsTask (project management)Web APIComponent (thermodynamics)Data WebWeb navigationWeb engineeringWeb designMashupWeb application securityEngineering

Abstract

fetched live from OpenAlex

The Web contains large amount of information and services primarily intended for human users. A Web application offers high user experience and responsiveness. A user performs different task, such as reserving flight tickets from a Web application. A task is a set of activities required for a user to achieve a goal. Similar tasks are often used in different websites. Therefore, facilitating their reuse would improve development productivity and ease maintenance of Web applications. However, designing a reusable Web application component is often neglected by Web developers due to the pressure for the time-to-market. To circumvent this limitation, we propose an approach to interactively identify tasks from Web applications and represent these tasks as services.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.803
Threshold uncertainty score0.816

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.015
GPT teacher head0.255
Teacher spread0.240 · 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

Quick stats

Citations11
Published2012
Admission routes1
Has abstractyes

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