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

C
Check Point Blog
IT之家
IT之家
V
Visual Studio Blog
The Cloudflare Blog
博客园 - 司徒正美
Jina AI
Jina AI
博客园_首页
阮一峰的网络日志
阮一峰的网络日志
美团技术团队
S
SegmentFault 最新的问题
博客园 - 聂微东
人人都是产品经理
人人都是产品经理
T
Tailwind CSS Blog
罗磊的独立博客
酷 壳 – CoolShell
酷 壳 – CoolShell
量子位
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
Hugging Face - Blog
Hugging Face - Blog
博客园 - 【当耐特】
博客园 - 三生石上(FineUI控件)
爱范儿
爱范儿
博客园 - Franky
Last Week in AI
Last Week in AI
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

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
The Promise and Reality of Continuous Integration Caching...
Taher A. Ghaleb, Daniel Alencar da Costa, Ying Zou · 2026-01-27 · via cs.SE updates on arXiv.org

Continuous Integration (CI) provides early feedback by automatically building software, but long build durations can hinder developer productivity. CI services use caching to speed up builds by reusing infrequently changing artifacts, yet little is known about how caching is adopted in practice and what challenges it entails. In this paper, we conduct a large-scale empirical study of CI caching in Travis CI, analyzing 513,384 builds from 1,279 GitHub projects. We find that only 30% of projects adopt CI caching, and early adopters are typically more mature, with more dependencies, commits, and longer CI lifespans. To understand non-adoption, we submit pull requests enabling caching in non-adopting projects, and nearly half are accepted or merged. Developer feedback indicates that non- or late adoption mainly results from limited awareness of CI caching support. We further study cache maintenance and identify five common activities, performed by 24% of cache-enabled projects. While one-third of projects see substantial build-time reductions, cache uploads occur in 97% of builds, and 27% of projects contain stale cached artifacts. An analysis of reported caching issues shows developers mainly struggle with corrupted or outdated caches and request broader caching features. Overall, CI caching does not benefit all projects, requires ongoing maintenance, and is more complex in practice than many developers expect.