惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

L
LangChain Blog
J
Java Code Geeks
P
Proofpoint News Feed
Recent Announcements
Recent Announcements
罗磊的独立博客
H
Hackread – Cybersecurity News, Data Breaches, AI and More
博客园_首页
Hugging Face - Blog
Hugging Face - Blog
MongoDB | Blog
MongoDB | Blog
人人都是产品经理
人人都是产品经理
博客园 - 【当耐特】
雷峰网
雷峰网
D
DataBreaches.Net
B
Blog RSS Feed
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
博客园 - 聂微东
V
Visual Studio Blog
Apple Machine Learning Research
Apple Machine Learning Research
N
Netflix TechBlog - Medium
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
Martin Fowler
Martin Fowler
有赞技术团队
有赞技术团队
Blog — PlanetScale
Blog — PlanetScale
Engineering at Meta
Engineering at Meta

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
Industrial Requirements for Supporting AI-Enhanced Model-...
Johan Bergelin, Per Erik Strandberg · 2022-08-29 · via cs.SE updates on arXiv.org

There is an increasing interest in research on the combination of AI techniques and methods with MDE. However, there is a gap between AI and MDE practices, as well as between researchers and practitioners. This paper tackles this gap by reporting on industrial requirements in this field. In the AIDOaRt research project, practitioners and researchers collaborate on AI-augmented automation supporting modeling, coding, testing, monitoring, and continuous development in cyber-physical systems. The project specifically lies at the intersection of industry and academia collaboration with several industrial use cases. Through a process of elicitation and refinement, 78 high-level requirements were defined, and generalized into 30 generic requirements by the AIDOaRt partners. The main contribution of this paper is the set of generic requirements from the project for enhancing the development of cyber-physical systems with artificial intelligence, DevOps, and model-driven engineering, identifying the hot spots of industry needs in the interactions of MDE and AI. Future work will refine, implement and evaluate solutions toward these requirements in industry contexts.