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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
Exploratory and Live, Programming and Coding: A Literatur...
2018-07-23 · via cs.SE updates on arXiv.org

Various programming tools, languages, and environments give programmers the impression of changing a program while it is running. This experience of liveness has been discussed for over two decades and a broad spectrum of research on this topic exists. Amongst others, this work has been carried out in the communities around three major ideas which incorporate liveness as an important aspect: live programming, exploratory programming, and live coding. While there have been publications on the focus of each particular community, the overall spectrum of liveness across these three communities has not been investigated yet. Thus, we want to delineate the variety of research on liveness. At the same time, we want to investigate overlaps and differences in the values and contributions between the three communities. Therefore, we conducted a literature study with a sample of 212 publications on the terms retrieved from three major indexing services. On this sample, we conducted a thematic analysis regarding the following aspects: motivation for liveness, application domains, intended outcomes of running a system, and types of contributions. We also gathered bibliographic information such as related keywords and prominent publications. Besides other characteristics the results show that the field of exploratory programming is mostly about technical designs and empirical studies on tools for general-purpose programming. In contrast, publications on live coding have the most variety in their motivations and methodologies with a majority being empirical studies with users. As expected, most publications on live coding are applied to performance art. Finally, research on live programming is mostly motivated by making programming more accessible and easier to understand, evaluating their tool designs through empirical studies with users. In delineating the spectrum of work on liveness, we hope to make the individual communities more aware of the work of the others. Further, by giving an overview of the values and methods of the individual communities, we hope to provide researchers new to the field of liveness with an initial overview.