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 48
Trustworthy Data- and ML-Ops for Intelligent Transportation Systems and Logistics
The rapid evolution of Intelligent Transportation Systems and Logistics (ITS\&L) has become a cornerstone of the modern social economy, relying heavily on the integration of Data, Artificial…A Design Theory for AI-Assisted Software Development Derived from Christopher Alexander's Theory of Form
Code generated by large language models (LLMs) cannot be assumed to meet specified requirements.Refactoring React Component Hierarchies to Eliminate Prop Drilling
In React front-end development, Prop Drilling is the practice of propagating data through component properties across multiple levels of the component hierarchy.When Does a Second Model Help? Cross-Model Review in LLM Verification
Large language models now generate code, documentation, and analyses, and are increasingly used to review such output.MCRI: A Four-Dimensional Framework for Analyzing and Evaluating Agent Skills
As agents evolve from single-tool systems into modular, composite architectures, skills are becoming an important mechanism for capability development and distribution.Architectural Degradation: How to Measure and to Remediate
Architectural degradation undermines software maintainability, evolvability, and quality.Code Detectors Have a Half-Life: Obsolescence and Metric Illusions in LLM-Generated Code Detection
Code detectors can become obsolete as code-generating models evolve: a detector validated on one generation of models may not transfer to the next.CONTRA: Discovering and Qualifying Behavior-Changing Questions for Selective Clarification in LLM Code Generation
Coding agents can generate code that appears correct but implements behavior the user never intended.Continuous Process-Level Evaluation for Evolving Enterprise AI Agent Skills
Enterprise AI agent skills evolve as tool APIs, models, and specifications change, yet final-output evaluation can miss process-level behavioral drift.Detecting Inconsistencies in Model Specifications with LLM-as-Verifier Reasoning
Model specifications define how large language models (LLMs) should behave, guiding alignment training, inference-time behavior, and evaluation.FastCI: Efficient GPU-Intensive CI for LLM Training Frameworks
As large language models (LLMs) keep growing in size and complexity, their training frameworks evolve at a rapid pace as well.From Alert Floods to Precedence Forests: Zero-Prior-Knowledge Incident Triage with LOGOS
Commercial observability platforms rely on domain artifacts like distributed traces, topology maps, and baseline metrics.SimuVerity: Benchmarking Agents for Engineering-Grade Simulink Model Generation
Existing Simulink benchmarks mainly evaluate whether generated models compile, execute, or resemble a reference model.Compound AI System Reliability: A Failure Taxonomy and Resilience Pattern Catalog from 150 Production Incidents
Deploying compound AI systems reliably and safely requires understanding failure modes that emerge at component boundaries, not within individual models.An Extensive Empirical Study on Evaluation Metrics for Combinatorial Interaction Testing
Combinatorial interaction testing (CIT) is a black-box testing method that has received extensive attention in both research and practice over recent years.Improving the Energy-Efficiency of the Code Generated by LLMs through Effective Prompting
As AI-assisted programming becomes increasingly mainstream, the environmental impact of AI-generated software has emerged as an important consideration.Fine-Grained Emotion Classification from Mobile App Reviews: An Empirical Study with Large Language Models
Fine-grained emotion classification of mobile app reviews enables requirements engineering activities that go beyond polarity-based opinion mining, including emotionally informed issue…Adaptive-GEPA: Make Your Harness Fit Heterogeneous Requests
Reflective optimizers such as GEPA improve language model prompts from execution traces and evaluator feedback; full-program extensions can also rewrite tools and control flow.PatchHolmes: Agentic Patch Retrieval via Listwise Selection
Patch retrieval, the task of finding the commit that fixes a known vulnerability, is the foundation of vulnerability management workflows, yet 60% to 63% of CVEs in the major advisory databases lack…Toward Quantum Software Automation: A Quantum-Aware Harness for LLM-Guided Evolution
Quantum software is critical for improving the efficiency and reliability of scarce quantum hardware.