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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
Minimalistic Terminal Editor for Julia Programming -- Min...
Poornachandratejasvi Laxman Bhattar, Payal V. Dahiwale, Krishnar · 2026-05-12 · via cs.SE updates on arXiv.org

Developers rely on lightweight, terminal-centric workflows for rapid code iteration. However, within a unified environment for Julia programming language, existing tools provide limited support for integrated workflow such as editing, execution, file management, and debugging. As a result, developers frequently incur context-switching overhead and fragmented tool interactions. Therefore, the proposed work predominantly focuses on the minimalistic approach for developing native terminal editor for Julia programming language. This paper introduces MinTEJ, a terminal-based editor built in Julia, and proposes a Sequential Modal Interaction Architecture (SMIA) that unifies file management, code editing, execution, and debugging through a command-oriented workflow. The presented work formalizes model interaction and reduces cognitive load & errors while transitioning among different modes. In SMIA, buffer is the central data structure that persists across all modes. Each mode interprets and manipulates the buffer according to mode-specific rules. The central controller mediates access to the buffer and enforces sequential transitions between modes. To evaluate the approach, the performance benchmarking of MinTEJ is compared against existing tools i.e., VS code and Notepad++. The effectiveness of the proposed MinTEJ is evaluated based on memory consumption and CPU utilization demonstrating that it has less resource overhead. Findings suggest that integrated terminal-based editor environment is a practical lightweight software tool enabling efficient iterative development.