An Exploratory Study on Automatic Identification of Assumptions in the Development of Deep Learning Frameworks

1 code implementation • 8 Jan 2024 • Chen Yang, Peng Liang, Zinan Ma

To overcome the issues of manually identifying assumptions in DL framework development, we constructed a new and largest dataset (i. e., AssuEval) of assumptions collected from the TensorFlow and Keras repositories on GitHub; explored the performance of seven traditional machine learning models (e. g., Support Vector Machine, Classification and Regression Trees), a popular DL model (i. e., ALBERT), and a large language model (i. e., ChatGPT) of identifying assumptions on the AssuEval dataset.

Language Modelling Large Language Model