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State-of-the-art Text-to-SQL models rely on fine-tuning or few-shot prompting to help LLMs learn from training datasets containing mappings from natural language (NL) queries to SQL statements. Consequently, the quality of the dataset can greatly affect the accuracy of these Text-to-SQL models. Unlike other NL tasks, Text-to-SQL datasets are prone to errors despite extensive manual efforts due to the subtle semantics of SQL. Our study has found a non-negligible (>30%) portion of incorrect NL to SQL mapping cases exists in popular datasets Spider and BIRD. This paper aims to improve the quality of Text-to-SQL training datasets and thereby increase the accuracy of the resulting models. To do so, we propose a necessary correctness condition called execution consistency. For a given database instance, an NL to SQL mapping satisfies execution consistency if the execution result of an NL query matches that of the corresponding SQL. We develop SQLDriller to detect incorrect NL to SQL mappings based on execution consistency in a best-effort manner by crafting database instances that likely result in violations of execution consistency. It generates multiple candidate SQL predictions that differ in their syntax structures. Using a SQL equivalence checker, SQLDriller obtains counterexample database instances that can distinguish non-equivalent candidate SQLs. It then checks the execution consistency of an NL to SQL mapping under this set of counterexamples. The evaluation shows SQLDriller effectively detects and fixes incorrect mappings in the Text-to-SQL dataset, and it improves the model accuracy by up to 13.6%. 

Abstract Redox is a unique, programmable modality capable of bridging communication between biology and electronics. Previous studies have shown that theE. coliredox-responsive OxyRS regulon can be re-wired to accept electrochemically generated hydrogen peroxide (H₂O₂) as an inducer of gene expression. Here we report that the redox-active phenolic plant signaling molecule acetosyringone (AS) can also induce gene expression from the OxyRS regulon. AS must be oxidized, however, as the reduced state present under normal conditions cannot induce gene expression. Thus, AS serves as a “pro-signaling molecule” that can be activated by its oxidation—in our case by application of oxidizing potential to an electrode. We show that the OxyRS regulon is not induced electrochemically if the imposed electrode potential is in the mid-physiological range. Electronically sliding the applied potential to either oxidative or reductive extremes induces this regulon but through different mechanisms: reduction of O₂to form H₂O₂or oxidation of AS. Fundamentally, this work reinforces the emerging concept that redox signaling depends more on molecular activities than molecular structure. From an applications perspective, the creation of an electronically programmed “pro-signal” dramatically expands the toolbox for electronic control of biological responses in microbes, including in complex environments, cell-based materials, and biomanufacturing.