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

Martin Fowler
Martin Fowler
WordPress大学
WordPress大学
月光博客
月光博客
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
大猫的无限游戏
大猫的无限游戏
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
博客园 - 聂微东
Apple Machine Learning Research
Apple Machine Learning Research
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
雷峰网
雷峰网
小众软件
小众软件
酷 壳 – CoolShell
酷 壳 – CoolShell
博客园 - 叶小钗
美团技术团队
宝玉的分享
宝玉的分享
Hugging Face - Blog
Hugging Face - Blog
阮一峰的网络日志
阮一峰的网络日志
A
About on SuperTechFans
Jina AI
Jina AI
D
Docker
Last Week in AI
Last Week in AI
MongoDB | Blog
MongoDB | Blog
Stack Overflow Blog
Stack Overflow Blog
Microsoft Azure Blog
Microsoft Azure Blog

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
Checking Finite State Machine Conformance when there are ...
Robert M Hierons · 2011-08-26 · via cs.SE updates on arXiv.org

This paper concerns state-based systems that interact with their environment at physically distributed interfaces, called ports. When such a system is used a projection of the global trace, called a local trace, is observed at each port. This leads to the environment having reduced observational power: the set of local traces observed need not uniquely define the global trace that occurred. We consider the previously defined implementation relation $\sqsubseteq_s$ and start by investigating the problem of defining a language ${\mathcal {\tilde L}} (M)$ for a multi-port finite state machine (FSM) $M$ such that $N \sqsubseteq_s M$ if and only if every global trace of $N$ is in ${\mathcal {\tilde L}} (M)$. The motivation is that if we can produce such a language ${\mathcal {\tilde L}} (M)$ then this can potentially be used to inform development and testing. We show that ${\mathcal {\tilde L}} (M)$ can be uniquely defined but need not be regular. We then prove that it is generally undecidable whether $N \sqsubseteq_s M$, a consequence of this result being that it is undecidable whether there is a test case that is capable of distinguishing two states or two multi-port FSM in distributed testing. This result complements a previous result that it is undecidable whether there is a test case that is guaranteed to distinguish two states or multi-port FSMs. We also give some conditions under which $N \sqsubseteq_s M$ is decidable. We then consider the implementation relation $\sqsubseteq_s^k$ that only concerns input sequences of length $k$ or less. Naturally, given FSMs $N$ and $M$ it is decidable whether $N \sqsubseteq_s^k M$ since only a finite set of traces is relevant. We prove that if we place bounds on $k$ and the number of ports then we can decide $N \sqsubseteq_s^k M$ in polynomial time but otherwise this problem is NP-hard.