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 39
Implementing the Spec Growth Engine: Preventing Spec-Code Divergence, and Growing the Spec with Agents
The Spec Growth Engine anchors AI-assisted software development in a graph of specifications that the code is coupled to.MAP4CS: A Multi-dimensional Data Pruning Framework for Efficient Code Retriever Fine-tuning
Retrieval-Augmented Generation (RAG) has become a cornerstone in software engineering for enhancing Large Language Models (LLMs) with domain-specific knowledge.ObliVul: Alert-Conditioned Safety Obligation Modeling and Bidirectional Counterfactual Validation for Code Vulnerability Detection
In real-world software development, the primary challenge in vulnerability detection is often not finding suspicious code, but identifying which alerts among the large number of candidate alerts…On the Risks of using LLM-Generated Tests for Regression Testing
Software is under constant evolution: developers continuously add features, fix bugs, and refactor code, and any of these changes may break existing functionality.Trajectory-Guided Fault Localization for Agent Skill Evolution
Agent skills provide reusable guidance for code agents, but incomplete or unsuitable guidance can impair task execution.NosRacer: Dynamic Detection of Race Conditions in On-Device Network Operating Systems
Commercial on-device network operating systems (NOSes) run complex control planes in production routers and switches, where configuration update tasks are executed by multiple loosely coupled…Evaluating Exact Output and Checkpoint-State Prediction in Real Programs
We present a benchmark for predicting final output and checkpoint state from source and input alone.Forms of LLM-Integrated Applications from LLM-Chats to Autonomous AI Agent System
Large language models (LLMs) are increasingly embedded as components in software systems, marketed under labels such as chatbot, copilot, retrieval-augmented generation, workflow, coding agent and…Can LLMs Fix It Without Code? Toward Automated Verification of No-Code Bug Fixes
A no-code fix resolves an invalid bug report by directing the user to change a setting, update to a version where the problem is already fixed, or adjust their workflow.Neural Network Verification for Deep Joint Source-Channel Coding
Deep joint source-channel coding (DeepJSCC) transmits data end-to-end over wireless channels using a neural encoder-decoder, but reconstruction quality can degrade sharply under adversarial…Traceable World State: A Provenance-Aware State Representation and Deterministic Replay Framework for Robotic Systems
Robotic systems operating over extended tasks must maintain a world state assembled from observations arriving at different times, with varying confidence and potential revisions.Protecting CPU AI On Edge TEEs: WebAssembly's Promise and Practical Challenges
AI models on edge hardware contain important intellectual property (IP), but an adversary can steal it when they achieve root access.Reliability Characterization for N-version Object Detection
N-version object detection (OD) is an approach to diversifying detection results using multiple models or input frames and reducing detection errors by aggregating individual results.Cadence: Strategic Guidance for Coding Agents
Runtime monitors are increasingly used to improve the reliability of LLM-based coding agents by inspecting execution trajectories and delivering corrective guidance upon detecting misbehavior.TestPrism: Rethinking Test Evaluation Beyond a Single Reference
Large language model (LLM) coding agents have advanced test generation across diverse programming tasks.Fix What's Wrong, Keep What's Right: Hallucination Repair for LLM-Based Optimization Modeling
Large language models (LLMs) are increasingly being explored to automate operations research modeling, reduce modeling time and lower the expertise barrier to optimization based decision support.SWE-Duel: Towards a Self-Scaling Arena for Coding Agents
Static coding benchmarks are fixed at release.Beyond Binary Verifiable Rewards: Behavioral Self-Rewarding for SWE Agents
Reinforcement learning with verifiable rewards (RLVR) provides reliable supervision for software engineering agents through executable tests, but binary rewards fail to distinguish trajectories with…SoftwareGym: Scaling Computer-Use Agent Training with Diverse Synthesized Software Environments
Computer-use agents (CUAs) are rapidly improving, yet synthesizing diverse and reliable software environments at scale remains challenging.Quantifying SMT Solver Instability for Formal Verification
Program verification has become commonplace in software development projects, and much of its feasibility can be attributed to the potential of SMT solvers to automate model checking and other…