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 49
Doing More with Less Tokens: Hierarchical Reinforcement Learning for Efficient Coding Agents
Recently, coding agents have emerged as a dominant paradigm for real-world software engineering (SWE) scenarios, which solve complex tasks through multi-turn interactions with development…Approval Laundering: Systematizing Approval--Execution Binding Failures in AI Coding-Agent Harnesses
Modern AI coding-agent harnesses (Claude Code, Codex CLI, Cursor) rest their security boundary on a largely unexamined assumption: that the action A a human approves is the same action A' the…From Verification Failures to Reusable Guidance for Coding Agents
Coding agents need to establish that a program satisfies a specification and that the specification captures the requested behavior.Trustworthy Runtime Error Healing in Real-World Repositories: A Benchmark and Guardrail
Runtime error healing lets a crashed program continue by generating code that repairs its live runtime state.EngramBench: A Capability-Grounded Benchmark for Skill-Evolution Harnesses
While large language models have achieved remarkable success in isolated code generation, authentic software engineering requires sustained reasoning, complex state management, and continuous…Self-Spec Verifiable Code Generation
Large language models (LLMs) may generate unreliable code on corner cases missed by testing, while formal verification can provide machine-checkable guarantees.Aletheia: Permission-Minimality Testing for Coding-Agent Rules
Repository instruction files guide coding agents, but also expose them to prompt injection.Trust Is Not a Score: Runtime Assurance Contracts for High-Risk AI Agents
Benchmarks, audits, and agent protocols describe performance, permissions, and repair, but not how observed evidence should change an agent's authority during a consequential task.COMPASS: Predicting the Relationship of Multiple Patches for Vulnerabilities with LLMs
Modern software heavily relies on code reuse, so upstream vulnerability fixes do not automatically propagate to downstream codebases.DoGBench: Can Agents Meet Expert Standards for User-Facing Documentation?
We introduce DoGBENCH (Documentation Generation Benchmark), to our knowledge, the first benchmark for generating and maintaining real user-facing software documentation.Learning When and How to Intervene: A Hindsight-Distilled Sentinel for Coding Agents
Coding agents solve repository-level tasks through sequences of actions, where a single erroneous action can misdirect subsequent decisions and increase recovery costs.Leveraging Game-Based Platform to Teach Code Refactoring: An Experience with Refactoria
Refactoring is the art of improving the internal structure of the code without altering its external behavior.Automatically Building Machine-Checked Assurance Cases from C Codebases to Requirements
Large language models (LLMs) have shown promise in automating interactive theorem proving, yet verification of real-world C codebases requires more than discharging individual proof goals.Code That Works, Environments That Don't: Measuring Environment Reproducibility in AI-Generated Software
Code generation has emerged as a central capability of large language models, with coding agents now able to produce functionally correct software projects from natural language prompts.Extending LLM-based support for software engineers with ADHD
Software engineering workflows are often not designed to accommodate the needs of developers with Attention Deficit Hyperactivity Disorder (ADHD), despite known challenges related to task…Understanding and Mitigating Library-Related Issues in LLM-Generated Code
Software practitioners increasingly rely on Large Language Models (LLMs) to generate code that integrates external libraries.ASAD: Adaptive Software Agents for Debugging
The integration of Large Language Models (LLMs) into multi-agent systems has shown great potential for automated debugging.WitnessGym: Benchmarking Coding Agents on the Construction of Bug Witnesses
Bug validation asks a coding agent to produce an executable witness for a reported bug.CTE-Bench: Counterfactual Trace Evaluation for Stateful Software Simulators
Coding agents change running software: they patch a service's code or overwrite its stored state, and then act on their own expectation of how the service will respond afterwards.Can Agents Design Libraries for Agents?
Agents increasingly build on code written by other agents, and they reimplement rather than reuse, growing the codebases later agents must work in.