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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
An Exploration Study on Developing Blockchain Systems the...
Bakheet Aljedaani, Aakash Ahmad, Mahdi Fahmideh, Arif Ali Khan, · 2024-07-25 · via cs.SE updates on arXiv.org

Context: Blockchain-based software (BBS) exploits the concepts and technologies popularized by cryptocurrencies offering decentralized transaction ledgers with immutable content for security-critical and transaction critical systems. Recent research has explored the strategic benefits and technical limitations of BBS in various fields, including cybersecurity, healthcare, education, and financial technologies. Despite growing interest from academia and industry, there is a lack of empirical evidence, leading to an incomplete understanding of the processes, methods, and techniques necessary for systematic BBS development. Objectives: Existing research lacks a consolidated view, particularly empirically driven guidelines based on published evidence and development practices. This study aims to address the gap by consolidating empirical evidence and development practices to derive or leverage existing processes, patterns, and models for designing, implementing, and validating BBS systems. Method: Tied to this knowledge gap, we conducted a two-phase research project. First, a systematic literature review of 58 studies was performed to identify a development process comprising 23 tasks for BBS systems. Second, a survey of 102 blockchain practitioners from 35 countries across six continents was conducted to validate the BBS system development process. Results: Our results revealed a statistically significant difference (p-value <.001) in the importance ratings of 24 out of 26 BBS tasks by our participants. The only two tasks that were not statistically significant were incentive protocol design and granularity design. Conclusion: Our research is among the first to advance understanding on the aspect of development process for blockchain-based systems and helps researchers and practitioners in their quests on challenges and recommendations associated with the development of BBS systems