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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
A Practical Implementation of Customized Scrum-Based Agil...
Malik Muhammad Umer · 2025-11-18 · via cs.SE updates on arXiv.org

The increasing complexity of aerospace systems requires development processes that balance agility with stringent safety and certification demands. This study presents an empirically validated Scrum-based Agile framework tailored for DO-178C compliant, safety-critical aerospace software. The framework adapts core Scrum roles, artifacts, and events to meet certification, verification, and independence objectives. Key enhancements include a multi-disciplinary product ownership model, dual compliance-and-functionality acceptance criteria, independent testing and documentation teams, and dedicated certification liaisons. The approach was evaluated through two comparable aerospace projects-one using the customized Agile process and the other a traditional Waterfall model. Results showed significant improvements: a 76% reduction in Total Effort per Requirement, 75% faster Defect Detection, 78% faster Defect Resolution, and over 50% lower Defect Density, while maintaining full compliance with DO-178C Design Assurance Level A. These findings demonstrate that Agile practices and regulatory compliance can coexist effectively when supported by disciplined tailoring and proactive engagement with certification authorities. The study also notes challenges, including increased V&V effort due to recurring Sprint activities and refactoring inherent to iterative development. Nonetheless, it identifies substantial opportunities for further gains through workflow automation, CI/CD practices, and automated documentation, verification, and configuration management. Future research should expand validation of this framework across the aerospace domain and other safety-critical industries with similar certification requirements.