Static Inference Meets Deep Learning: A Hybrid Type Inference Approach for Python

Type inference for dynamic programming languages such as Python is an important yet challenging task. Static type inference techniques can precisely infer variables with enough static constraints but are unable to handle variables with dynamic features. Deep learning (DL) based approaches are featur...

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Veröffentlicht in:	arXiv.org 2022-02
Hauptverfasser:	Peng, Yun, Gao, Cuiyun, Li, Zongjie, Gao, Bowei, Lo, David, Zhang, Qirun, Lyu, Michael
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Annotations Artificial neural networks Computer Science - Programming Languages Computer Science - Software Engineering Deep learning Drift Dynamic programming Inference Machine learning Natural language (computers) Programming languages
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