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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
CertiA360: Enhance Compliance Agility in Aerospace Softwa...
J. Antonio Dantas Macedo, Hugo Fernandes, J. Eduardo Ferreira Ri · 2025-11-15 · via cs.SE updates on arXiv.org

Agile methods are characterised by iterative and incremental processes with a strong focus on flexibility and accommodating changing requirements based on either technical, regulatory, or stakeholder feedback. However, integrating Agile methods into safety-critical system development in the aerospace industry presents substantial challenges due to its strict compliance requirements, such as those outlined in the DO-178C standard. To achieve this vision, the flexibility of Agile must align with the rigorous certification guidelines, which emphasize documentation, traceability of requirements across different levels and disciplines, and comprehensive verification and validation (V&V) activities. The research work described in this paper proposes a way of using the strengths of the flexible nature of Agile methods to automate and manage change requests throughout the whole software development lifecycle, ensuring robust traceability, regulatory compliance and ultimately facilitating successful certification. This study proposes CertiA360, a tool designed to help teams improve requirement maturity, automate the changes in traceability, and align with the regulatory objectives. The tool was designed and validated in close collaboration with aerospace industry experts, using their feedback to ensure practical application and real-life effectiveness. The feedback collected demonstrated that the automation given by CertiA360 may reduce manual effort and allow response to changing requirements while ensuring compliance with DO-178C. While the tool is not yet qualified under DO-330 (Tool Qualification), findings suggest that when tailored appropriately, Agile methods can not only coexist with the requirements of safety-system development and certification in highly regulated domains like aerospace, but also add efficiency.