Applied & Human-Centered · Computer Science & AI
Software Engineering
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1,466 papers, from 31 August 2026 to 5 November 2026: 1,451 arXiv preprints and 15 OpenAlex records.
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Newest papers, page 69
Evaluating the NIST Bugs Framework Against CWE as a Successor for Automated Vulnerability Classification
Vulnerability classification based on root cause weaknesses is essential for numerous cybersecurity activities, where the Common Weakness Enumeration (CWE) serves as a public repository of such flaws.AI Assisted Workflow Optimization and Automation
Against the backdrop of digital transformation and stricter regulation, enterprise compliance work demands higher efficiency and accuracy.A Hybrid Dependency-Aware Framework for Task Decomposition and Dynamic Agent Generation in Oracle-to-PostgreSQL Migration
Large language model (LLM)-based database migration is often treated as direct code transformation, although enterprise Oracle systems contain heterogeneous SQL and PL/SQL artifacts with different…A Building as a Repository: KIR, a Typed Intermediate Representation for Agent-Authored Building Information Models
Autonomous agents that author building information models need more than access to a host API.A Two-Dimensional Study of the Model Context Protocol: Publication and Adoption
The Model Context Protocol (MCP), released by Anthropic in November 2024, standardizes how large language model applications connect to external tools and data sources.Fabrication After Tool Failure: Tool-Augmented Agents Assert Values Their Tools Did Not Return
Tool-augmented language models are evaluated on whether they reach the right answer, not on whether they report honestly when a tool fails to supply one.The Stochastic Deputy: Structural Tenant Isolation for Tool-Using LLM Agents
Multi-tenant tools commonly accept a tenant identifier and validate it against the caller's entitlement.Enhancing Automated Unit Test Generation for NLP Libraries Using Large Language Models
Automated unit test generation tools like EvoSuite perform well on general-purpose software but often struggle with domain-specific software such as Natural Language Processing (NLP) libraries…Transformed in Translation: Two-Stage Structural Uncertainty in LLM-Based Scientific Autoformalization
Scientific autoformalization turns verbal accounts into executable mathematics, but executable code does not settle which model has been constructed.Trust by Design: Trust Calibration Through Non-Advisory Socratic Dialogue in Conversational Agents
As conversational AI systems increasingly operate in sensitive domains, the central challenge shifts from usability to trust calibration, ensuring that users rely on systems neither too much nor too…The Case for Automated Hyperspecialization: Evidence from SAT
The software status quo is to use one system to process many different kinds of inputs.Efficiency Hallucination: Formalizing and Measuring Behavioral Calibration in LLM-Based Code Optimization
The integration of Large Language Models (LLMs) into automated code optimization introduces a critical reliability risk we term the Efficiency Hallucination: an LLM's tendency to issue…TyPatch: Transforming Patches into Typestate Rules for Kernel Bug Detection
Historical Linux kernel patches capture defect knowledge that applies beyond their original repair sites.Learning How Much to Collaborate: Difficulty-Aware Topology Selection for Multi-Agent Code Generation
Multi-agent systems for code generation are deployed with a single communication topology, chosen once for every problem.Introspective Uncertainty Estimation for LLM-Based Code Generation
Large Language Models (LLMs) are increasingly used for code generation but can produce fluent yet functionally incorrect outputs, which limits trust in their usage for practical software engineering…ParaRecover: A Process-Level Benchmark for Error Localization and Recovery in Parallel Tool-Use Agents
Existing agent benchmarks mainly evaluate final task success or tool-call correctness, providing limited insight into whether agents can reliably diagnose and recover from intermediate execution…Confidence-Gated Transductive Test Generation for Code Reranking
Test case synthesis is crucial for evaluating and ranking programs generated by large language models (LLMs).Separating Engineering Reasoning from DEXPI Serialization in LLM-Based Greenfield Surface-Process Design: A Three-Case Study for Underground Gas Storage
Large language models can produce engineering descriptions and structured process representations, but standards-level serialization can substantially increase the generation burden.What is the Difference Between Me and You? Benchmarking the Quality Gap Between Human-Written and AI-Generated Code
AI coding assistants are becoming co-authors of production software, yet their evaluation centers on functional correctness, leaving open whether their code differs from human code in the quality…What Drives Recovery in Agentic Text-to-Cypher? LAST-CQ: An LLM Agent Self-Refinement Framework
Agentic pipelines for structured-query generation are rapidly expanding, but it is unclear which part of the loop produces the gain.