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 66
An Empirical Evaluation of Cost-Efficient Large Language Models on Algorithmic Programming Tasks
This study empirically evaluates whether cost-efficient Large Language Models (LLMs) can be trusted to generate enterprise code to a written specification.Relationally Guided Use Case Modeling with LLMs
Use case flows are important elements of use case modeling because they support downstream software engineering activities, including requirements analysis, architectural and detailed design, and…A Study of the Reliability of Agentic AI-Generated Programs
Agentic-AI based software development offers the promise of faster completion of the software, greater programmer efficiency, and more reliable code.A Study on the Impact of Natural Language Differences in Prompts on Automatic Code Generation Using LLMs
Large Language Models (LLMs) have demonstrated remarkable performance in automatic code generation tasks, thereby encouraging new research in this area.From Component Snapshots to Lifecycle Traces: Agent-Based Software Composition Analysis
Software supply-chain security requires accurate identification of third-party components and an understanding of how they evolve from development to execution.AIJon: Automated Generation of Annotations for Fuzzing
Modern fuzzers use code coverage as feedback to guide their exploration which has proven to be an effective strategy for driving exploration.Evaluating the Health of Open-Source Smart City Platforms
To manage the complexity of smart cities, a variety of smart city platforms (SCPs), both proprietary and open-source, have been proposed.ProgramDistill: From Interactive Web Apps to Verifiable Reference-Guided SWE Tasks
Coding agents are typically evaluated with desired behavior specified through issues or instructions.Affora: A Design System for Agent-Friendly Interfaces
Computer-use agents increasingly operate software designed for people, but interfaces often leave actions or task state unclear to machine readers.Code-as-Auditor: Executable Compliance Reasoning via Regulation-to-Code
Large Language Models (LLMs) are increasingly adopted for compliance and legal reasoning tasks, yet their outputs often lack explicit grounding in legal logic and evidence.MAGS: Multi-agent Auto-formalization Guarantees Safety for Agentic Outputs
LLM coding agents now generate complex programs at a scale that makes thorough human review increasingly difficult, raising the risk of safety and security failures.Closed-World Resolution Against Tool Hallucination in LLM Agents
Tool-augmented large language model (LLM) agents fail in a way no tool-selection or tool-security method addresses: they call tools that do not exist and pass arguments no schema declares.FloatLib: Verified Floating-Point Arithmetic in Lean
We present FloatLib, a verified arbitrary-precision floating-point arithmetic library in Lean 4 that combines broad format coverage, machine-checked correctness, and efficient certified execution.Protocol-Preserving Context Trimming for Agentic Workflows: Benefits, Failure Regimes, and Budget Guardrails
Agentic large language model (LLM) systems rely on long interaction histories to preserve instructions, tool states, intermediate decisions, and unresolved dependencies, but unrestricted context…AI Policies: Help or Hindrance? A Software Developer's Perspective
AI policies introduced by software organisations to mitigate LLM-related risks such as sensitive information leaks and unauthorised usage are not useful if software developers do not engage with them.ExecuCritic: Calibrated Critic Shaping for Code Generation with Verifiable Rewards
Execution feedback is a useful supervision signal for code models because unit tests are objective and directly measure program correctness.An Exploratory Study of Dependabot Cooldown Adoption in Open-Source GitHub Projects
Automated dependency updates can rapidly propagate malicious package releases before maintainers and the broader community have enough time to detect them.Memory-Skill Isomorphism: One Skill Carrier, Two Native Uses
Memory and skills improve agents without changing weights: memory carries prior experience, skills carry reusable procedures.RECTIFY: An Interactive Workbench for Post-Evaluation RAG Diagnosis, Repair, and Verification
Retrieval-Augmented Generation (RAG) evaluators can identify failures such as weak retrieval, poor grounding, incomplete answers, and unsupported generation, but they rarely help developers decide…RepoAtlas: Guiding Coding Agents via Evolving Multimodal Repository Views
Large language model (LLM)-powered coding agents have made rapid progress in automating software engineering tasks, yet repository-level issue resolution remains challenging.