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 43
Beyond the Leaderboard: Multi-Dimensional Evaluation of Dense and Mixture-of-Experts Models for Automated Program Repair
Automated Program Repair (APR) with language models is usually evaluated by whether a generated patch passes the test suite, which can hide differences in maintainability, security, and…GPU Acceleration of Awkward Arrays: Using Python cuda.compute
Awkward Array is a widely used library in high-energy physics (HEP) for representing and manipulating nested, variable-length data in Python.Newer and Bigger, but Safer? A Longitudinal Study of the Functionality-Security Gap in LLM-Generated Code
Large Language Models (LLMs) are widely used to generate code.Learning from Failures: A Failure-Driven Prompt Refinement for LLM-Based Vulnerability Analysis
Large Language Models have emerged as promising tools for software vulnerability analysis, but their effectiveness depends heavily on prompt design.RAPO-Sol: Retrieval-Augmented Preference Optimization for Repository-Level Solidity Code Generation
Smart contracts written in Solidity manage assets, permissions, and irreversible state changes, making code generation both useful and security-critical.How Much Evidence Should a Coding Agent's Self-Correction Carry? Adaptive Dirichlet Evidence for Self-Distillation
Execution feedback lets coding agents revise programs and learn from their own corrections.Recursive Game Creator: An Agentic Product-Level Experience-Oriented Game Harness
Recent game design agents have made substantial progress in generating playable games.A Case Study in Assuring AI-Written Software
Software-engineering agents can enable people without formal software training to build systems they could not otherwise implement and simultaneously can produce more code than even experts can…ParanoiaEval: Benchmarking Unnecessary Defensive Work in Agentic Coding
As coding agents increasingly undertake real-world work autonomously, judging whether their risk treatments are warranted has become important.Mitigating Uncertainty Interactions in GenAI-based Adaptive Systems: Vision, Challenges and Preliminary Guidelines
Modern software-intensive systems increasingly incorporate GenAI components, including LLM and agentic subsystems, which introduce novel and compounding sources of uncertainty across system layers.Psychological Safety in Software Engineering Teams: A Systematic Mapping Study of Team Processes and Performance
Psychological safety is an important human and behavioral factor in software development teams, supporting collaboration, knowledge sharing, interpersonal risk-taking, and learning.Automatically Detecting and Fixing Deadlocks in Go Code with GoDDaR
The Go programming language provides a lightweight abstraction for concurrent programming through goroutines, which are prone to deadlocks.How Fragile Is On-Device Language Model Safety? Localizing Safety-Critical Parameters for Sparse Fault Analysis
As small language models (SLMs) are increasingly deployed on resource-constrained and on-device platforms, including as components of agentic systems, the integrity of locally stored model…Evaluating Change Point Detection Methods for Software Performance Regression Analysis
Performance issues in software systems are a critical quality issue that can erode user trust, violate service-level agreements, and ultimately affect business efficiency.Large-scale Repository Engineering via Agent-Native Reusable Code Primitives
Large language models equipped with development environments have moved code generation toward repository-scale construction, yet building complete repositories remains difficult because interacting…Finding Blind Spots in AppWorld and WorkArena Task Verifiers
Execution-based task verifiers decide whether an agent succeeded.SpecGuard: Proving a Task Is Broken Before the Agent Cheats
As autonomous coding agents get increasingly deployed, the risk that accidental or adversarially injected misspecifications in tasks lead to dangerous agent behavior is critical to address.A Survey on LLM-Integrated Hardware Design Verification
Large language models (LLMs) are increasingly being integrated into hardware verification to automate specification interpretation, verification-artifact generation, debugging, formal reasoning, and…Finite State Machine-Based Traffic Orchestration for Multi-Engine Analysis Platforms
Modern application-security platforms route live traffic from a single proxy into several independent analysis engines -- behavioral anomaly detection, authentication analysis, resource discovery…PreMaQ: Predicting Maintainability-Related Quality of LLM-Generated Code Before Generation
As large language models (LLMs) become increasingly capable of code generation, adopting generated code in software development requires assessing not only its functional correctness but also its…