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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
From Commits to Confidence: Towards Stability-Informed Ri...
Elijah Kayode Adejumo, Mariam Guizani, Brittany Johnson · 2025-08-04 · via cs.SE updates on arXiv.org

Open source software (OSS) generates trillions of dollars in economic value and has become essential to the technical infrastructures that power organizations worldwide. As these systems increasingly depend on OSS, understanding the evolution of these projects is critical. While existing metrics provide insights into project health, one dimension remains understudied: project resilience, or the ability to return to normal operations after disturbances such as contributor departures,security vulnerabilities and bug report spikes. We hypothesize that stable commit patterns may serve as an indicator of underlying project characteristics such as mature governance, sustained contributors, and robust development processes, factors that existing research associates with resilience. Our findings reveal that only 2% of repositories exhibit daily stability, 29% achieve weekly stability, and 50\% demonstrate monthly stability, while the remaining half are unstable across all levels of granularity. Analysis of the 50 unstable repositories indicate that 86% of activity is concentrated among a few maintainers, with the top 3 contributors accounting for over 50% of commits in the past 5 years. In contrast, the 50 stable repositories distribute work more evenly, with the top 3 contributors representing less than 50% of commits. Our insights thus far indicate the fragile and multi-dimensional nature of OSS project stability, suggesting a need to go beyond commits to understand how our understanding of stability can be enriched with other considerations such as community engagement metrics and issue or pull request churn. Though our efforts only identified two repositories that achieved stability at all three temporal commit granularities, further investigation into their processes and policies can provide insights and foundations for stability-informed risk assessment in practice.