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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? 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Automating Structural Analysis Across Multiple Software Platforms Using Large Language Models CCCE: A Continuous Code Calibration Engine for Autonomous Enterprise Codebase Maintenance via Knowledge Graph Traversal and Adaptive Decision Gating Building Trust in the Skies: A Knowledge-Grounded LLM-based Framework for Aviation Safety Contract-Coding: Towards Repo-Level Generation via Structured Symbolic Paradigm ECM Contracts: Contract-Aware, Versioned, and Governable Capability Interfaces for Embodied Agents Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering AgentOpt v0.1 Technical Report: Client-Side Optimization for LLM-Based Agent CODESTRUCT: Code Agents over Structured Action Spaces Chinese Language Is Not More Efficient Than English in Vibe Coding: A Preliminary Study on Token Cost and Problem-Solving Rate Inside the Scaffold: A Source-Code Taxonomy of Coding Agent Architectures Evaluating the Formal Reasoning Capabilities of Large Language Models through Chomsky Hierarchy WybeCoder: Verified Imperative Code Generation QuanBench+: A Unified Multi-Framework Benchmark for LLM-Based Quantum Code Generation ContractSkill: Repairable Contract-Based Skills for Multimodal Web Agents From Natural Language to PromQL: A Catalog-Driven Framework with Dynamic Temporal Resolution for Cloud-Native Observability Evaluating Reliability Gaps in Large Language Model Safety via Repeated Prompt Sampling From Scalars to Tensors: Declared Losses Recover Epistemic Distinctions That Neutrosophic Scalars Cannot Express Automating Crash Diagram Generation Using Vision-Language Models: A Case Study on Multi-Lane Roundabouts LoRA-MME: Multi-Model Ensemble of LoRA-Tuned Encoders for Code Comment Classification MobiFlow: Real-World Mobile Agent Benchmarking through Trajectory Fusion A Pythonic Functional Approach for Semantic Data Harmonisation in the ILIAD Project Help Without Being Asked: A Deployed Proactive Agent System for On-Call Support with Continuous Self-Improvement ACE-Bench: A Lightweight Benchmark for Evaluating Azure SDK Usage Correctness X-SYS: A Reference Architecture for Interactive Explanation Systems KRONE: Scalable LLM-Augmented Log Anomaly Detection via Hierarchical Abstraction Capture the Flags: Family-Based Evaluation of Agentic LLMs via Semantics-Preserving Transformations VeruSAGE: A Study of Agent-Based Verification for Rust Systems Process-Centric Analysis of Agentic Software Systems Enabling Predictive Maintenance in District Heating Substations: A Labelled Dataset and Fault Detection Evaluation Framework based on Service Data Context-Guided Decompilation: A Step Towards Re-executability Saber: An Efficient Sampling with Adaptive Acceleration and Backtracking Enhanced Remasking for Diffusion Language Model From Charts to Code: A Hierarchical Benchmark for Multimodal Models E2Edev: Benchmarking Large Language Models in End-to-End Software Development Task AISysRev -- LLM-based Tool for Title-abstract Screening SecureVibeBench: Benchmarking Secure Vibe Coding of AI Agents via Reconstructing Vulnerability-Introducing Scenarios TriagerX: Dual Transformers for Bug Triaging Tasks with Content and Interaction Based Rankings CodeFlowBench: A Multi-turn, Iterative Benchmark for Complex Code Generation A PennyLane-Centric Dataset to Enhance LLM-based Quantum Code Generation using RAG
How to Sustain a Scientific Open-Source Software Ecosystem: Learning from the Astropy Project
Jiayi Sun, Aarya Patil, Youhai Li, Jin L. C. Guo, Shurui Zhou · 2024-02-23 · via cs.SE updates on arXiv.org

Scientific open-source software (OSS) has greatly benefited research communities through its transparent and collaborative nature. Given its critical role in scientific research, ensuring the sustainability of such software has become vital. Earlier studies have proposed sustainability strategies for conventional scientific software and open-source communities. However, it remains unclear whether these solutions can be easily adapted to the integrated framework of scientific OSS and its larger ecosystem. This study examines the challenges and opportunities to enhance the sustainability of scientific OSS in the context of interdisciplinary collaboration, open-source community, and multi-project ecosystem. We conducted a case study on a widely-used software ecosystem in the astrophysics domain, the Astropy Project, using a mixed-methods design approach. This approach includes an interview with core contributors regarding their participation in an interdisciplinary team, a survey of disengaged contributors about their motivations for contribution, reasons for disengagement, and suggestions for sustaining the communities, and finally, an analysis of cross-referenced issues and pull requests to understand best practices for collaboration on the ecosystem level. Our study reveals the implications of major challenges for sustaining scientific OSS and proposes concrete suggestions for tackling these challenges.