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cs.SE updates on arXiv.org

VLA Foundry: A Unified Framework for Training Vision-Language-Action Models Evaluating LLM-Generated Obfuscated XSS Payloads for Machine Learning-Based Detection Do Agents Dream of Root Shells? Partial-Credit Evaluation of LLM Agents in Capture the Flag Challenges Refute-or-Promote: An Adversarial Stage-Gated Multi-Agent Review Methodology for High-Precision LLM-Assisted Defect Discovery From Particles to Perils: SVGD-Based Hazardous Scenario Generation for Autonomous Driving Systems Testing Choose Your Own Adventure: Non-Linear AI-Assisted Programming with EvoGraph Human-Machine Co-Boosted Bug Report Identification with Mutualistic Neural Active Learning LLMSniffer: Detecting LLM-Generated Code via GraphCodeBERT and Supervised Contrastive Learning Neurosymbolic Repo-level Code Localization CodeMMR: Bridging Natural Language, Code, and Image for Unified Retrieval Symbolic Guardrails for Domain-Specific Agents: Stronger Safety and Security Guarantees Without Sacrificing Utility Verification Modulo Tested Library Contracts The Semi-Executable Stack: Agentic Software Engineering and the Expanding Scope of SE Scaling Test-Time Compute for Agentic Coding AI-Assisted Requirements Engineering: An Empirical Evaluation Relative to Expert Judgment From Procedural Skills to Strategy Genes: Towards Experience-Driven Test-Time Evolution Atropos: Improving Cost-Benefit Trade-off of LLM-based Agents under Self-Consistency with Early Termination and Model Hotswap Vibe-Coding: Feedback-Based Automated Verification with no Human Code Inspection, a Feasibility Study Benchmarks for Trajectory Safety Evaluation and Diagnosis in OpenClaw and Codex: ATBench-Claw and ATBench-Codex Bounded Autonomy for Enterprise AI: Typed Action Contracts and Consumer-Side Execution AIPC: Agent-Based Automation for AI Model Deployment with Qualcomm AI Runtime Analyzing Chain of Thought (CoT) Approaches in Control Flow Code Deobfuscation Tasks Asking What Matters: Reward-Driven Clarification for Software Engineering Tasks Prompt-Driven Code Summarization: A Systematic Literature Review LinuxArena: A Control Setting for AI Agents in Live Production Software Environments LLMs taking shortcuts in test generation: A study with SAP HANA and LevelDB Large Language Models to Enhance Business Process Modeling: Past, Present, and Future Trends CollabCoder: Plan-Code Co-Evolution via Collaborative Decision-Making for Efficient Code Generation Sentiment analysis for software engineering: How far can zero-shot learning (ZSL) go? Learning from Change: Predictive Models for Incident Prevention in a Regulated IT Environment
Declarative Ajax Web Applications through SQL++ on a Unif...
Yupeng Fu, Kian Win Ong, Yannis Papakonstantinou · 2013-08-03 · via cs.SE updates on arXiv.org

Implementing even a conceptually simple web application requires an inordinate amount of time. FORWARD addresses three problems that reduce developer productivity: (a) Impedance mismatch across the multiple languages used at different tiers of the application architecture. (b) Distributed data access across the multiple data sources of the application (SQL database, user input of the browser page, session data in the application server, etc). (c) Asynchronous, incremental modification of the pages, as performed by Ajax actions. FORWARD belongs to a novel family of web application frameworks that attack impedance mismatch by offering a single unifying language. FORWARD's language is SQL++, a minimally extended SQL. FORWARD's architecture is based on two novel cornerstones: (a) A Unified Application State (UAS), which is a virtual database over the multiple data sources. The UAS is accessed via distributed SQL++ queries, therefore resolving the distributed data access problem. (b) Declarative page specifications, which treat the data displayed by pages as rendered SQL++ page queries. The resulting pages are automatically incrementally modified by FORWARD. User input on the page becomes part of the UAS. We show that SQL++ captures the semi-structured nature of web pages and subsumes the data models of two important data sources of the UAS: SQL databases and JavaScript components. We show that simple markup is sufficient for creating Ajax displays and for modeling user input on the page as UAS data sources. Finally, we discuss the page specification syntax and semantics that are needed in order to avoid race conditions and conflicts between the user input and the automated Ajax page modifications. FORWARD has been used in the development of eight commercial and academic applications. An alpha-release web-based IDE (itself built in FORWARD) enables development in the cloud.