Author

Jiho Shin

York University

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Preprint Sep 2026

NEUROTESTGEN: Neuro-Symbolic Guided Test Generation with Large Language Models

This paper introduces NEUROTESTGEN, a hybrid approach that integrates symbolic execution with LLM-driven test synthesis to generate test cases targeting on-demand code coverage and incorporates an iterative feedback loop that validates LLM-generated tests and provides corrective guidance until the target line or branch...

Rui-Xin Zhang, Jiho Shin, H. Pham et al. · 0 citations

#software testing Preprint Sep 2026

A Large-Scale Empirical Study of Quality Assurance Practices and Gaps in AI Agents

A large-scale empirical study of quality assurance (QA) practices in 157 open-source LLM-based agent projects with at least 100 GitHub stars highlights the need to move beyond feature-level testing toward systematic end-to-end validation that ensures agent workflows remain within intended boundaries when interacting wi...

Wu-Yang Dai, Moses Openja, Jiho Shin et al. · 0 citations

Book Open access Jul 2026

SecVulEval: Context-Aware Benchmarking of LLMs for Vulnerability Detection

This paper introduces SecVulEval, a context-aware benchmark designed to evaluate LLMs on vulnerability detection with rich contextual information, and believes it can serve as a foundation for advancing context-aware vulnerability detection with LLMs.

Md Basim Uddin Ahmed, Nima Shiri Harzevili, Jiho Shin et al. · AIware · 2 citations