Applied & Human-Centered · Computer Science & AI
Software Engineering
The newest papers in Software Engineering that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
1,466 papers, from 31 August 2026 to 5 November 2026: 1,451 arXiv preprints and 15 OpenAlex records.
Get the few papers worth your time in Software Engineering every morning.
Follow Software Engineering and ReadSearch reads its new papers each day, then brings you the few worth reading, each with its key finding in a sentence.
Newest papers, page 73
CIT-CAD: Constraint Intent Tree-based CAD Code Generation and Verification
Natural-language Computer-Aided Design (CAD) code generation aims to turn design intent into executable and editable parametric programs.A Tool-Augmented, GPT-4 Chatbot for Real-Time Repository Data Analysis
Software repositories contain vast amounts of data on code contributions, bug reports, and project activities, yet this information remains challenging for non-technical stakeholders and developers…Do AI Coding Assistants Check Before They Install? A Pre-Registered Demand-Side Audit of Trust Signals in the Research Software Supply Chain
AI coding assistants now select, install, and configure software, and attackers have exploited that position through invented package names, compromised maintainer accounts, and manipulated…CodeTD: Topology of Attention Detects Hallucinations in Code LLMs
As AI-code assistant tools become widespread, automatic assessment of the correctness of generated code becomes a significant challenge.VEX-Bench: Benchmarking LLM Agents for Assessing Exploitability of Software Supply Chain Vulnerabilities
The software supply chain has become an increasingly exposed attack surface because of its reliance on intricate yet fragile dependencies.Scores Alone Do Not Prove Discovery: The Discovery Certification Protocol for Auditing AI Research Agents
AI research agents combine prior knowledge, public sources, and experimental feedback to produce useful results.Cost-Aware Post-Hoc Deferral Under Calibration and Shift: An Environmental AI Case Study
Choosing a deferral policy for a frozen classifier requires more than ranking uncertain cases: confidence may be miscalibrated, errors have unequal costs, reviewers can err, and deployment data can…From Reading Code to Reading Spec: A Verified Layer for LLM-Driven Codebase Maintenance
The rapid growth of LLM-generated code increases software complexity and the maintenance burden on engineers.A Unified Policy Architecture (UPA): The Governance Kernel for Enterprise AI Operating Systems
Enterprise AI is evolving into an Enterprise Operating System where autonomous AI agents can plan, reason, use memory, invoke tools, execute workflows, and collaborate with other agents.CAROL: Context-Aware Online Learning for Fuzzer Scheduling
Ensemble fuzzing runs multiple fuzzers on a target while a scheduler allocates CPU time among them.AURA-Eval: Evaluation Framework for Acting Under Risk Awareness in LLM Agent Trajectories
LLM agents operate in workflows where unsafe actions can have real consequences.Diffs vs. Whole Files: An Empirical Comparison of Iterative Edit-Based and Direct Generation for Flutter/Dart Code Models
Large language models used for code editing can be trained and deployed in at least two output regimes: direct generation, where the model emits the entire modified file in one shot, and iterative…Broken on Arrival: Silently Defective LLM Artifacts in Public Model Registries and How to Catch Them
Developers increasingly run large language models locally by pulling quantized GGUF artifacts from public registries, yet nothing in the distribution pipeline functionally tests these conversions…SkillSpec: Intent-Masked Specification Reasoning for Agent Skill Correctness
Autonomous agent systems increasingly depend on reusable skill abstractions for consolidating experiential knowledge and domain expertise.SWE-Test: Benchmarking LLM Vulnerability Discovery via Input Prediction
Vulnerability discovery is becoming an important ability of large language model (LLM) agents: agents that silently miss real defects leave critical software exposed.Trace2Tower: Transition-Aware EigenTrace Induction of Multi-Level Skills for LLM Agents
Large language model agents increasingly rely on execution traces to master complex interactive tasks.The History Is the Detector: Executing CVE Patch History, End-to-End
Public vulnerability databases collect rich information about known software flaws, including their weakness types, affected components, and related patches.Who Maintains Agent Skills? A Longitudinal Study of Human-Governed, AI-Assisted Skill Maintenance
Lifelong LLM agents increasingly rely on external skill artifacts as one element for preserving and reusing capabilities over time.TreeFI: Value-Aware Statistical Fault Injection for Deep Neural Networks
Reliability evaluation of deep neural networks under hardware faults commonly relies on fault injection, but exhaustive campaigns are intractable for modern models and datasets.ARIA - An Agentic Framework for Autonomous Testing of Infotainment Systems
Automotive infotainment validation still relies on manual testing, slow, costly, and incompatible with agile releases and OTA updates.