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

罗磊的独立博客
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 - 三生石上(FineUI控件)
Hugging Face - Blog
Hugging Face - Blog
小众软件
小众软件
量子位
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
IT之家
IT之家
V
V2EX
阮一峰的网络日志
阮一峰的网络日志
爱范儿
爱范儿
人人都是产品经理
人人都是产品经理
博客园 - Franky
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_首页
V
Visual Studio Blog
Last Week in AI
Last Week in AI
有赞技术团队
有赞技术团队
WordPress大学
WordPress大学
博客园 - 司徒正美
大猫的无限游戏
大猫的无限游戏
博客园 - 【当耐特】
MyScale Blog
MyScale Blog
月光博客
月光博客

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
Managed Information: A New Abstraction Mechanism for Hand...
David H. Lorenz, Boaz Rosenan · 2020-12-31 · via cs.SE updates on arXiv.org

Management of information is an important aspect of every application. This includes, for example, protecting user data against breaches (like the one reported in the news about 50 million Facebook profiles being harvested for Cambridge Analytica), complying with data protection laws and regulations (like EU's new General Data Protection Regulation), coping with large databases, and retaining user data across software versions. Today, every application needs to cope with such concerns by itself and on its own. In this paper we introduce Managed Information (MI), an abstraction mechanism for managing extra-functional data related concerns, similar to how managed memory today abstracts away many memory related concerns. MI limits the access applications have to user data, which, in return, relieves them from responsibility over it. This is achieved by hosting them on a Managed Information Platform (MIP), and implementing their logic in a language that supports MI. As evidence for the feasibility of MI we describe the design and implementation of such a platform. For demonstration of MI, we describe a simple social network application built with it. The implementation is open source.