Syntax-guided program reduction for understanding neural code intelligence models
Md Rafiqul Islam Rabin, Aftab Hussain, Mohammad Amin Alipour · 2022
Neural code intelligence (CI) models are opaque black-boxes and offer little insight on the features they use in making predictions. This opacity may lead to distrust in their prediction and hamper their wider adoption in safety-critical applications. Recently, input program reduction techniques have been proposed to identify key features in the input programs to improve the transparency of CI models. However, this approach is syntax-unaware and does not consider the grammar of the programming language.