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

Vercel News
Vercel News
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
雷峰网
雷峰网
有赞技术团队
有赞技术团队
罗磊的独立博客
博客园 - 叶小钗
Jina AI
Jina AI
博客园 - 司徒正美
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
T
Tailwind CSS Blog
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
人人都是产品经理
人人都是产品经理
Apple Machine Learning Research
Apple Machine Learning Research
阮一峰的网络日志
阮一峰的网络日志
Microsoft Security Blog
Microsoft Security Blog
大猫的无限游戏
大猫的无限游戏
量子位
MyScale Blog
MyScale Blog
V
Visual Studio Blog
博客园 - 聂微东
The Cloudflare Blog
Engineering at Meta
Engineering at Meta
小众软件
小众软件
宝玉的分享
宝玉的分享

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
Desyan: A Platform for Seamless Value-Flow and Symbolic A...
Panagiotis Diamantakis, Thanassis Avgerinos, Yannis Smaragdakis · 2025-08-01 · via cs.SE updates on arXiv.org

Over the past two decades, two different types of static analyses have emerged as dominant paradigms both in academia and industry: value-flow analysis (e.g., data-flow analysis or points-to analysis) and symbolic analysis (e.g., symbolic execution). Despite their individual successes in numerous application fields, the two approaches have remained largely separate; an artifact of the simple reality that there is no broadly adopted unifying platform for effortless and efficient integration of symbolic techniques with high-performance data-flow reasoning. To bridge this gap, we introduce Desyan: a platform for writing program analyses with seamless integration of value-flow and symbolic reasoning. Desyan expands a production-ready Datalog fixpoint engine (Soufflé) with full-fledged SMT solving invoking industry-leading SMT engines. Desyan provides constructs for automatically (and efficiently!) handling typical patterns that come up in program analysis. At the same time, the integration is agnostic with respect to the solving technology, and supports Datalog-native symbolic reasoning, via a bottom-up algebraic reasoning module. The result is an engine that allows blending different kinds of reasoning, as needed for the underlying analysis. For value-flow analysis, the engine is the best-in-class Datalog evaluator (often by a factor of over 20x in execution time); for applications that require full SMT (e.g., a concolic execution engine or other symbolic evaluator that needs to solve arbitrarily complex conditions), the engine is leveraging the leading SMT solvers; for lightweight symbolic evaluation (e.g., solving simple conditionals in the context of a path-sensitive analysis), the engine can use Datalog-native symbolic reasoning, achieving large speedups (often of over 2x) compared to eagerly appealing to an SMT solver.