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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
GitFarm: Git as a Service for Large-Scale Monorepos
Preetam Dwivedi, Akshay Hacholli, Adam Bettigole · 2026-04-14 · via cs.SE updates on arXiv.org

At the scale of Uber's monorepos, traditional Git workflows become a fundamental bottleneck. Cloning multi-gigabyte repositories, maintaining local checkouts, periodically syncing from upstream, and executing repetitive fetch or push operations consume substantial compute and I/O across hundreds of automation systems. Although CI (Continuous Integration) systems such as Jenkins and Buildkite provide caching mechanisms to reduce clone times, in practice, these approaches incur significant infrastructure overhead, manual maintenance, inconsistent cache hit rates, and cold start latencies of several minutes for large monorepos. Moreover, thousands of independent clone and fetch operations add heavy load on upstream Git servers, making them slow and difficult to scale. To address these limitations, we present GitFarm, a platform that provides Git as a stateful, identity-scoped, repository-centric execution service through a gRPC API. GitFarm decouples repository management from clients by executing Git operations remotely within secure, ephemeral sandboxes backed by pre-warmed repositories. The system enforces identity-scoped authorization, supports multi-command workflows, and leverages specialized backend clusters for workload isolation. For clients, this design eliminates local clones, provides a ready-to-use checkout in less than a second, and significantly lowers client-side compute and I/O overhead by offloading operations to GitFarm. Also, client services no longer experience cold starts (up to 15 minutes) due to initial clones of the monorepos on each host. The results demonstrate that Git as a service provides substantial performance and cost benefits, while preserving the flexibility of native Git semantics.