State-of-the-art log compressors typically rely on a decoupled “parse-then-compress” workflow, where parsing is optimized for semantic accuracy (i.e., event identification) rather than storage efficiency. Through a comprehensive empirical study, we reveal that this architectural decoupling prevents the exploitation of...
Yang Liu, Kai-Ming Zhang, Zhuang-Bin Chen et al.· 0 citations
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 qu...
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.
Jun-Song Pu, Yichen Li, Zhuang-Bin Chen et al.· 0 citations
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