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 13
Benchmarking LLM Agents for Behaviorally Adequate Test Generation from Software Requirements
As large language model agents increasingly compile natural-language requirements into repository-level code, requirement-to-test generation grows in importance to provide validation constraints (or…A Fine-Grained Empirical Study of Upstream Security Events and Downstream Mitigation in Maven
Open-source vulnerability mitigation spans upstream libraries and the downstream projects that depend on them.God Does Not Play Dice: Enforcing Batch Invariance in Agentic Kernel Generation
Large language model (LLM) serving systems dynamically batch user requests for GPU execution, so the same request may be processed alongside different requests across runs.ASNER: Software Architecture Recovery with Adaptive Semantic Neighborhoods and Evidence-Grounded Refinement
Automated software architecture recovery provides architectural context for software engineering and repository-level LLM agents.A lightweight C Code Generator for Heterogeneous TinyML Systems
Over the past decade, the significant advancements in artificial intelligence have been closely tied to increasingly sophisticated training frameworks and steadily powerful computing hardware.Beyond QASecClaw: Agent Scaling, Verifier Feedback, and Evidence Reliability in Software Assurance
Can additional specialist language-model contexts improve software assurance when deterministic tool evidence is already available?Does More Thinking Pay Off? Reasoning Cost and Correctness of LLMs in Code Generation and Bug Fixing
Many LLMs now emit an explicit reasoning trace before they write code, but benchmark results for code generation and bug fixing usually report correctness alone.Toward Circuit-Aware Mutation Testing for Quantum Programs: Exact Visibility and Execution Planning
Mutation testing assesses test suites by introducing program changes and checking whether tests detect them.Spine: Compiling Subtask Trees into Structured Context for Long-Horizon Coding Agents
Long-horizon coding tasks contain nested subtasks.Grounding LLM Agents in Business Processes: Process-Aware Knowledge Graphs for Reliable Multi-Step Service Invocation
Large language model (LLM) agents that call enterprise APIs must select the correct endpoints, follow process order, use valid payload keys, and choose coded values from predefined lists.BenchMeUp: Building Software Engineering Benchmarks from Natural-Language Specifications
Software-engineering research relies on benchmarks that evaluate new techniques on a set of problem instances.Hidden in Plain Sight: an Empirical Study about The Instruction Stacks of Coding Agents
Coding agents send their models more than the user's prompt: they add instructions, tool definitions, and environmental context that form an instruction stack.Mind the Intent Gap: A Methodology for Collaborative Agent-Driven Software Engineering
AI agents have entered software teams, first as tools and now as team members.HIDE: Hierarchical Isolation via Documentation and Evidence for Rustc Bugs
Rustc bugs can prevent valid programs from compiling or cause incorrect compilation results, making the identification of responsible source files essential for repair.FeatureArc: Benchmarking Coding Agents on Evolving Features
A software feature usually evolves over time: developers extend its first version as new use cases and requirements arrive, and each extension builds on code written earlier.An EVM-Cosmos Bridge for Atomic, Semantic-Preserving Transfer of Environmental Tokens
Transferring semantically typed tokens between heterogeneous blockchains (e.g. EVM and Cosmos ecosystems) raises two problems: semantic mixing, the loss of a token's domainspecific meaning in…When Skills Tell Agents Not to Ask: A Large-Scale Study of Oversight Directives in Agent Skills
Agent skills, reusable instruction packages centred on a SKILL.md file, extend AI agents on demand, and a single line in a widely copied skill reaches every agent that loads it.Structured Security Explanations for Learning-Based Vulnerability Detection
Software vulnerability detection remains difficult because existing approaches rely on predefined analysis rules, learn vulnerability patterns implicitly from code and labels, or use large language…Measuring Where Intent Gets Lost in Agentic Smart Contract Synthesis
AI agents can now write software from a plain-English description, but code that runs is not the same as code that does what was asked.ICALL-BENCH: Benchmarking LLM Interprocedural Reasoning in Binary Programs
Recent benchmarks show that LLMs achieve strong performance in both function-level binary understanding and end-to-end binary reverse engineering tasks, but whether LLMs can reason over…