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Tag

#software-engineering

8 articles tagged #software-engineering

arxivJun 3bullish

VulnAgent-R2: Evidence-Calibrated Multi-Agent Auditing for Repository-Level Vulnerability Detection

arXiv:2603.13384v2 Announce Type: replace-cross Abstract: Software vulnerabilities often depend on cross-file data flow, build options, framework conventions, and runtime guards, so isolated function classifiers produce fragile and poorly calibrated warnings. Repository-level LLM agents can gather r

VUVU2 models#vulnerability-detection#software-engineering#auditabilityRead on arxiv →
arxivMay 14bullish

HE-SNR: Uncovering Latent Logic via Entropy for Guiding Mid-Training on SWE-bench

arXiv:2601.20255v2 Announce Type: replace-cross Abstract: SWE-bench has emerged as the premier benchmark for evaluating Large Language Models on complex software engineering tasks. While these capabilities are fundamentally acquired during the mid-training phase and subsequently elicited during Supe

#benchmark#software-engineering#large-language-modelsRead on arxiv →
arxivMay 8

BUILD-AND-FIND: An Effort-Aware Protocol for Evaluating Agent-Managed Codebases

arXiv:2605.06136v1 Announce Type: cross Abstract: Most coding-agent benchmarks ask whether generated code behaves correctly. That remains essential, but repository-level engineering is increasingly agent-managed: one agent writes a repository, and later agents inspect, audit, or extend it as working

#benchmark#software-engineering#artificial-intelligenceRead on arxiv →
arxivMay 7bullish

AI Advocate: Educational Path to Transform Squads to the Future

arXiv:2605.03800v1 Announce Type: cross Abstract: This paper analyzes the strategic education process aimed at transitioning traditional software development squads into hybrid structures centered on collaborative work between humans and Artificial Intelligence (AI). In a context where human-AI coll

#collaboration#education#software-engineeringRead on arxiv →
arxivMay 6

Using LLMs in Software Design: An Empirical Study of GitHub and A Practitioner Survey

arXiv:2605.01392v1 Announce Type: cross Abstract: Recent advancements in Large Language Models (LLMs) have demonstrated significant potential across a wide range of software engineering tasks, including software design, an area traditionally regarded as highly dependent on human expertise and judgme

CH1 model#software-engineering#large-language-models#designRead on arxiv →
arxivApr 23bullish

Coding with Eyes: Visual Feedback Unlocks Reliable GUI Code Generating and Debugging

arXiv:2604.19750v1 Announce Type: cross Abstract: Recent advances in Large Language Model (LLM)-based agents have shown remarkable progress in code generation. However, current agent methods mainly rely on text-output-based feedback (e.g. command-line outputs) for multi-round debugging and struggle

GE1 model#gui#debugging#benchmarkRead on arxiv →
arxivApr 17bullish

Contract-Coding: Towards Repo-Level Generation via Structured Symbolic Paradigm

arXiv:2604.13100v1 Announce Type: cross Abstract: The shift toward intent-driven software engineering (often termed "Vibe Coding") exposes a critical Context-Fidelity Trade-off: vague user intents overwhelm linear reasoning chains, leading to architectural collapse in complex repo-level generation.

#software-engineering#autonomous-engineering#intent-drivenRead on arxiv →
arxivApr 10bullish

Triage: Routing Software Engineering Tasks to Cost-Effective LLM Tiers via Code Quality Signals

arXiv:2604.07494v1 Announce Type: cross Abstract: Context: AI coding agents route every task to a single frontier large language model (LLM), paying premium inference cost even when many tasks are routine. Objectives: We propose Triage, a framework that uses code health metrics -- indicators of soft

#software-engineering#model-selection#cost-optimizationRead on arxiv →
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