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Record W1813837568 · doi:10.1109/icst.2015.7102635

Testing Web Applications Through Layout Constraints

2015· article· en· W1813837568 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 institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsComputer scienceWeb pageWindow (computing)World Wide WebSet (abstract data type)Web browserWeb applicationOn the flyClient-side scriptingWeb testingInformation retrievalStatic web pageWeb modelingWeb navigationProgramming languageThe InternetOperating systemWeb intelligence

Abstract

fetched live from OpenAlex

The paper focuses on bugs in web applications that can be detected by analyzing the contents and layout of page elements inside a browser's window. Based on an empirical analysis of 35 real-world web sites and applications (such as Facebook, Dropbox, and Moodle), it provides a survey and classification of more than 90 instances of layout-based bugs. It then introduces Cornipickle, an automated testing tool that provides a declarative language to express desirable properties of a web application as a set of human-readable assertions on the page's HTML and CSS data. Such properties can be verified on-the-fly as a user interacts with an application.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.609
Threshold uncertainty score0.590

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 communication0.0000.000
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 head0.098
GPT teacher head0.298
Teacher spread0.201 · 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

Citations14
Published2015
Admission routes1
Has abstractyes

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