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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
Software-Defined Vehicle Ecosystems in Transformation -- ...
Heidi Hietala, Nirnaya Tripathi, Prabhash Rathnayake, Yueqiang X · 2026-02-24 · via cs.SE updates on arXiv.org

The automotive industry is shifting from hardware-centric development toward software-defined vehicles (SDVs), where software drives functionality, value creation, and competitive differentiation. Growing software complexity renders firm-centric and proprietary software development models insufficient, prompting a shift toward ecosystem collaboration among OEMs, suppliers, and software firms. Yet, how these SDV ecosystems emerge and operate in response to software-driven development remains insufficiently understood. This study enhances our understanding of SDV ecosystems, outlines their collaborative structures, identifies stakeholders, their roles and authority, and highlights associated challenges and opportunities. This study identifies six levels of collaboration involving twelve stakeholder groups shaping SDV ecosystem transformation. These collaborations are influenced by five dimensions of authority. SDV ecosystems face six core software development challenges alongside six organisational, six industry and market, and four regulatory, legal, and ethical challenges. The literature also highlights five key software development opportunities complemented by six organisational, four industry and market, and two public value and ethical opportunities. SDV ecosystem research is primarily technical, concentrating on architectures and standardisation, while lacking studies on governance and collaborative software business models that reflect regional characteristics and power dynamics. We reposition SDVs as multi-level socio-technical ecosystems where software functions as the core structuring principle but does not alone determine ecosystem success. We develop a multi-level SDV ecosystem model, integrating stakeholders, collaborative structures, and governance across ecosystem levels, and outline directions for future research and practice.