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

G
Google Developers Blog
S
SegmentFault 最新的问题
Jina AI
Jina AI
D
DataBreaches.Net
人人都是产品经理
人人都是产品经理
罗磊的独立博客
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
爱范儿
爱范儿
大猫的无限游戏
大猫的无限游戏
C
Check Point Blog
酷 壳 – CoolShell
酷 壳 – CoolShell
WordPress大学
WordPress大学
博客园 - 三生石上(FineUI控件)
B
Blog
博客园 - 【当耐特】
博客园 - Franky
M
MIT News - Artificial intelligence
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
L
LangChain Blog
MyScale Blog
MyScale Blog
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
博客园 - 叶小钗
Last Week in AI
Last Week in AI
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
Java Extensions for OMNeT++
Henning Puttnies, Peter Danielis, Christian Koch, Dirk Timmerman · 2017-09-09 · via cs.SE updates on arXiv.org

On the one side, network simulation frameworks are important tools for research and development activities to evaluate novel approaches in a time- and cost-efficient way. On the other side, Java as a highly platform-independent programming language is ideally suited for rapid prototyping in heterogeneous scenarios. Consequently, Java simulation frameworks could be used to firstly perform functional verification of new approaches (and protocols) in a simulation environment and afterwards, to evaluate these approaches in real testbeds using prototype Java implementations. Finally, the simulation models can be refined using real world measurement data. Unfortunately, there is to the best of our knowledge no satisfying Java framework for network simulation, as the OMNeT++ Java support ended with OMNeT++ version 4.6. Hence, our contributions are as follows: we present Java extensions for OMNeT++ 5.0 that enable the execution of Java simulation models and give a detailed explanation of the working principles of the OMNeT++ Java extensions that are based on Java Native Interface. We conduct several case studies to evaluate the concept of Java extensions for OMNeT++. Most importantly, we show that the combined use of Java simulation models and C++ models (e.g., from the INET framework) is possible.