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.
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Newest papers, page 29
When LLM-Generated Refactorings Ripple: An Empirical Study of Repository Adoption Readiness
Large Language Models (LLMs) are increasingly used to refactor source files, but file-local evaluations do not reveal changes to contracts, dependencies, or caller assumptions affecting repository…Teaching Code Agents to Ask Without Leaking Private Code
Local coding agents can extend their reach by consulting a stronger cloud model.Pattern-Driven Evaluation of LLM Code Optimization: Isolating Compiler-Transcendent Semantic Reasoning
Existing evaluations of LLM-based code optimization primarily measure end-to-end speedup, obscuring whether a model actually performs the intended optimization.When Does UML Software Modeling Pay Off? A Contingency Model of Industrial Modeling Value
With the emergence of specification-driven development (SDD), software modeling has regained strategic importance as a way to translate human intentions, requirements, and design decisions into…RXSynth: A Seed-Grounded Corpus for Studying Java Runtime-Exception Bugs
Existing Java bug benchmarks offer limited method-level data for studying runtime-exception detection.CAT-RAG: Improving Secure Code Generation with Category-Aware Agentic Retrieval
Despite rapid progress in LLM-based code generation, security vulnerabilities remain widespread, and retrieval-augmented code generation (RACG) can further amplify risk when retrieved knowledge is…InterType: Breaking the Single-Function Barrier in Neural Binary Type Inference
Variable type recovery is a critical task in binary reverse engineering, enabling downstream applications such as vulnerability discovery, malware analysis, and security enforcement.Between Spoilers and Guesswork: Avoiding Over-Specification in Coding Benchmarks
Benchmarks drive AI progress, but are hampered by task under-specification and over-specification.No One-Size-Fits-All: Adaptive Code Editing with Feature-Based Strategy Selection
Large language models have shown strong potential in automating code editing (CE) tasks, yet most existing systems rely on a fixed CE strategy (i.e., one-step, search-replace, and plan-apply) across…MergeShuffle: Reconstruct Shared Libraries for Improved Performance and Security
Debloating shared libraries has been an active research topic for years.VulnSAGE: Adjudicating SAST Reports by Connecting LLM Reasoning to Program Structure
Static Application Security Testing (SAST) reports flag operations whose safety depends on project-specific context, and maintainers must decide which reports describe real defects.Efficient Program Reduction for Library Fuzzing Harnesses
Library fuzzing harnesses translate generated inputs into API calls.Code Skill Server: A Large-Scale Search Engine for Code Generation Skills
Agent skills have proven to be an effective technique for improving agent ability on specific tasks, including software engineering, natural science, and mathematics.Towards Agentic Proof Harness Engineering
Formal verification of real-world projects requires substantial manual effort, from specifying correctness properties to constructing the infrastructure needed to check them.SpinControl: Control Software for Prototyping and Benchmarking of Spin-Qubit Devices and Measurement Protocols
Quantum computers require software to control the states of the qubits.Robust Function Calling for LLM Agents Under Interface Drift
Tool-augmented language-model agents rely on interface text: tool descriptions, argument schemas, and the candidate tool list shown at inference time.Monitor-Validity Failures: LLM Safety Evidence Paths at Evolving Framework Boundaries
Modern LLM applications rely on runtime monitors that inspect tool calls, traces, streams, detector outputs, and verifier inputs.MLOps-Bench: Benchmarking AI Agents on Production ML Engineering in Real Repositories
AI agents are increasingly expected to modify and maintain machine-learning systems in production, yet existing benchmarks primarily evaluate either competition-style ML experimentation or generic…Recall-Oriented Precise Binary-to-Source Function Matching
Binary-to-source function matching supports software composition analysis by identifying reused third-party code, but existing embedding-based approaches restrict subsequent refinement to initially…An Interactive GraphRAG Workspace for Reifying, Auditing, and Steering Conversational AI Memories
Conversational Large Language Models (LLMs) are widely employed in software engineering for code generation, debugging, and architectural design.