For this purpose, we present novel algorithms for both NLP-based synthesis and regex repair. We evaluate TRANSREGEX with ten relevant state-of-theart tools on three publicly available datasets. The evaluation results demonstrate that the accuracy of our TRANSREGEX is 17.4%, 35.8% and 38.9% ...
While deep learning has been effective in image detection [59], translation [60], speech recognition [61], [62], sound synthesis [63] and even automated neural architecture search [64], clinical diagnosis and treatment tasks often need more care (e.g., patient interests, beliefs, social ...
In this paper, we address these challenges via Large Language Models (LLMs) together with semantic manipulations of sub-expressions, and propose PowerSyn, a framework for regex synthesis based on both natural language descriptions and examples and supports extended features. Specifically, we design ...