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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
The Future of Hackathon Research and Practice
Jeanette Falk, Alexander Nolte, Daniela Huppenkothen, Marion Wei · 2022-11-16 · via cs.SE updates on arXiv.org

Hackathons are time-bounded collaborative events which have become a global phenomenon adopted by both researchers and practitioners in a plethora of contexts. Hackathon events are generally used to accelerate the development of, for example, scientific results and collaborations, communities, and innovative prototypes addressing urgent challenges. As hackathons have been adopted into many different contexts, the events have also been adapted in numerous ways corresponding to the unique needs and situations of organizers, participants and other stakeholders. While these interdisciplinary adaptions, in general affords many advantages - such as tailoring the format to specific needs - they also entail certain challenges, specifically: 1) limited exchange of best practices, 2) limited exchange of research findings, and 3) larger overarching questions that require interdisciplinary collaboration are not discovered and remain unaddressed. We call for interdisciplinary collaborations to address these challenges. As a first initiative towards this, we performed an interdisciplinary collaborative analysis in the context of a workshop at the Lorentz Center, Leiden in December 2021. In this paper, we present the results of this analysis in terms of six important areas which we envision to contribute to maturing hackathon research and practice: 1) hackathons for different purposes, 2) socio-technical event design, 3) scaling up, 4) making hackathons equitable, 5) studying hackathons, and 6) hackathon goals and how to reach them. We present these areas in terms of the state of the art and research proposals and conclude the paper by suggesting next steps needed for advancing hackathon research and practice.