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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
Understanding and Reusing Test Suites Across Database Sys...
Suyang Zhong, Manuel Rigger · 2024-10-29 · via cs.SE updates on arXiv.org

Database Management System (DBMS) developers have implemented extensive test suites to test their DBMSs. For example, the SQLite test suites contain over 92 million lines of code. Despite these extensive efforts, test suites are not systematically reused across DBMSs, leading to wasted effort. Integration is challenging, as test suites use various test case formats and rely on unstandardized test runner features. We present a unified test suite, SQuaLity, in which we integrated test cases from three widely-used DBMSs, SQLite, PostgreSQL, and DuckDB. In addition, we present an empirical study to determine the potential of reusing these systems' test suites. Our results indicate that reusing test suites is challenging: First, test formats and test runner commands vary widely; for example, SQLite has 4 test runner commands, while MySQL has 112 commands with additional features, to, for example, execute file operations or interact with a shell. Second, while some test suites contain mostly standard-compliant statements (e.g., 99% in SQLite), other test suites mostly test non-standardized functionality (e.g., 31% of statements in the PostgreSQL test suite are nonstandardized). Third, test reuse is complicated by various explicit and implicit dependencies, such as the need to set variables and configurations, certain test cases requiring extensions not present by default, and query results depending on specific clients. Despite the above findings, we have identified 3 crashes, 3 hangs, and multiple compatibility issues across four different DBMSs by executing test suites across DBMSs, indicating the benefits of reuse. Overall, this work represents the first step towards test-case reuse in the context of DBMSs, and we hope that it will inspire follow-up work on this important topic.