Causal Localization of BiDi Layout Defects through Batched Counterfactual Testing

We propose batched counterfactual CSS interventions that causally localize, rather than merely detect, BiDi defects. Adaptive group testing requires O(k log(m/k)) browser trials for k defects among m candidates, instead of O(m). Simulations indicate improved robustness to intentional asymmetry. Working paper of the Technische Universität Eisenfeld — not peer reviewed. Zusammenfassung (Deutsch): Wir schlagen gruppierte gegenfaktuelle CSS-Interventionen vor, die BiDi-Abweichungen nicht nur erkennen, sondern fehlerhafte Deklarationen kausal lokalisieren. Ein adaptiver Gruppentest benötigt bei k Fehlern unter m Kandidaten O(k log(m/k)) statt O(m) Browserläufe. Simulationen zeigen höhere Robustheit bei absichtlicher Asymmetrie. Published online in the TU Eisenfeld Working Paper Series: https://tu-eisenfeld.de/en/library/publications/counterfactual-bidi-localization-20261026

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-26
DOI
https://doi.org/10.5281/zenodo.23668765
Primary Topic
Software Testing and Debugging Techniques
Type
article
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article

Causal Localization of BiDi Layout Defects through Batched Counterfactual Testing

Dr. Emeka Okafor, Mateo Rossi
Zenodo (CERN European Organization for Nuclear Research)
Software Testing and Debugging Techniques
article

Causal Localization of BiDi Layout Defects through Batched Counterfactual Testing

Dr. Emeka Okafor, Mateo Rossi
article en

Abstract

We propose batched counterfactual CSS interventions that causally localize, rather than merely detect, BiDi defects. Adaptive group testing requires O(k log(m/k)) browser trials for k defects among m candidates, instead of O(m). Simulations indicate improved robustness to intentional asymmetry. Working paper of the Technische Universität Eisenfeld — not peer reviewed. Zusammenfassung (Deutsch): Wir schlagen gruppierte gegenfaktuelle CSS-Interventionen vor, die BiDi-Abweichungen nicht nur erkennen, sondern fehlerhafte Deklarationen kausal lokalisieren. Ein adaptiver Gruppentest benötigt bei k Fehlern unter m Kandidaten O(k log(m/k)) statt O(m) Browserläufe. Simulationen zeigen höhere Robustheit bei absichtlicher Asymmetrie. Published online in the TU Eisenfeld Working Paper Series: https://tu-eisenfeld.de/en/library/publications/counterfactual-bidi-localization-20261026

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 4%
Software Testing and Debugging Techniques
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