Hridya Dhulipala, Xiaokai Rong, Aashish Yadavally, Tien N. Nguyen · 2026 · arXiv (Cornell University)
DOI: 10.48550/arxiv.2610.25601 · cited by 0 works (OpenAlex) · open-access PDF
إن إنتاج أوتوماتيكية فعالة من اختبارات الويب في نهاية المطاف لا يزال تكلفة كبيرة: يجب على المطورين تحديد اختبارات مستدامة، إدخال عمليات العمل متعددة الخطوات، إدخال التأكيدات، وإبقاء الملفات مع التطور التفاعلية. يمكن للمستخدمين الالكترونيين المتخصصين في برنامج LLM إكمال وظائف اللغة الطبيعية في جلسة مبسطة في متصفح الويب الحي، ولكن إكمال الملفات لا يختلف عن إنتاج اختبارات الويب الأرضية التي تتكون من رمز تعامل قابل للتحقيق، وتأكيدات حالة الهدف، وتأكيدات المستقبل على مستوى الخطوة التي يتم إجراءها من حالة إعادة التشغيل، والتي يمكن تقييمها من قبل المطورين، ونحن نقدم TESSARA،
Machine translation (Meta M2M100); the English original follows.
Automated generation of end-to-end web tests remains costly: developers must identify stable selectors, encode multi-step workflows, attach assertions, and maintain scripts as interfaces evolve. Recent LLM-based web agents can complete natural-language tasks in a live browser session, but task completion is not the same as producing a test-ware artifact - code that is executable, replay-able from a reset state, inspectable by developers, and tied to an oracle. We present TESSARA, an adaptive test-script generation framework that converts natural-language test intent into Playwright scripts consisting of executable interaction code, goal-state assertions, and step-level provenance linking each step to its generated code fragment, selector evidence, execution outcome, and repair history. TESSARA grounds each planned step via Step-Aligned Scripting (SAS), enabling fine-grained failure localization, selective regeneration of failing suffixes, and reversibility-aware backtracking that avoids undoing likely commit points (e.g., form submissions). A three-level verification pipeline (syntactic, execution, and semantic/oracle), detects and repairs malformed code, interaction failures, and incorrect landing states. We evaluate TESSARA on three public web benchmarks, measuring script executability, oracle satisfaction, replay stability, and repair efficiency, and show substantial improvements over baselines and underlying VLMs used directly as script generators.
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Topics: Computer science, Scripting language, Commit, Executable, Web application, Programming language
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