Author

Zi-Bin Zheng

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Jul 2026

LogNLQ: Natural-Language Log Querying with Parser-Induced and Semantically Grounded Schemas

LogNLQ is a framework that formulates natural-language log querying as executable SQL generation over parser-induced and semantically grounded schemas, and demonstrates that LogNLQ consistently outperforms all representative baselines by wide margins, with especially pronounced gains on analytically complex scenario queries.

Jue Wang, Jinyang Liu, Zhuang-Bin Chen et al. · arXiv.org · 0 citations

Preprint Aug 2026

AutoSQL: Extracting SQL Templates from Imperative ORM Code in Large-Scale Repositories

This work presents AutoSQL, a system that reconstructs SQL templates from Go ORM code that constructs a Code Index, a directed graph that captures structural dependencies between functions, types, and global variables as navigable edges and synthesizes SQL templates.

Junsong Pu, Yichen Li, Zhuangbin Chen et al. · 0 citations