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

P
Proofpoint News Feed
Martin Fowler
Martin Fowler
The GitHub Blog
The GitHub Blog
B
Blog RSS Feed
U
Unit 42
阮一峰的网络日志
阮一峰的网络日志
量子位
GbyAI
GbyAI
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
云风的 BLOG
云风的 BLOG
小众软件
小众软件
博客园 - 三生石上(FineUI控件)
L
LangChain Blog
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
博客园_首页
IT之家
IT之家
V
Visual Studio Blog
Y
Y Combinator Blog
Blog — PlanetScale
Blog — PlanetScale
宝玉的分享
宝玉的分享
Apple Machine Learning Research
Apple Machine Learning Research
I
InfoQ
D
Docker
V
V2EX

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
Scrum for cyber-physical systems: a process proposal
Stefan Wagner · 2017-03-20 · via cs.SE updates on arXiv.org

Agile development processes and especially Scrum are changing the state of the practice in software development. Many companies in the classical IT sector have adopted them to successfully tackle various challenges from the rapidly changing environments and increasingly complex software systems. Companies developing software for embedded or cyber-physical systems, however, are still hesitant to adopt such processes. Despite successful applications of Scrum and other agile methods for cyber-physical systems, there is still no complete process that maps their specific challenges to practices in Scrum. We propose to fill this gap by treating all design artefacts in such a development in the same way: In software development, the final design is already the product, in hardware and mechanics it is the starting point of production. We sketch the Scrum extension Scrum CPS by showing how Scrum could be used to develop all design artefacts for a cyber physical system. Hardware and mechanical parts that might not be available yet are simulated. With this approach, we can directly and iteratively build the final software and produce detailed models for the hardware and mechanics production in parallel. We plan to further detail Scrum CPS and apply it first in a series of student projects to gather more experience before testing it in an industrial case study.