Automated cross-browser compatibility testing
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.
Bibliographic record
Abstract
With the advent of Web 2.0 applications and new browsers, the cross-browser compatibility issue is becoming increasingly important. Although the problem is widely recognized among web developers, no systematic approach to tackle it exists today. None of the current tools, which provide screenshots or emulation environments, specifies any notion of cross-browser compatibility, much less check it automatically. In this paper, we pose the problem of cross-browser compatibility testing of modern web applications as a 'functional consistency' check of web application behavior across different web browsers and present an automated solution for it. Our approach consists of (1) automatically analyzing the given web application under different browser environments and capturing the behavior as a finite-state machine; (2) formally comparing the generated models for equivalence on a pairwise-basis and exposing any observed discrepancies. We validate our approach on several open-source and industrial case studies to demonstrate its effectiveness and real-world relevance.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it