Graph Neural Networks For Mapping Variables Between Programs
In this work, we propose using graph neural networks (GNNs) to map the set of variables between two programs based on both programs' abstract syntax trees (ASTs). To demonstrate …
Learning Variable Mappings to Repair and Verify Programs
In this talk I will propose using graph neural networks (GNNs) to map the set of variables between two programs based on both programs' abstract syntax trees (ASTs).
MultIPAs: Applying Program Transformations to Introductory Programming Assignments for Data Augmentation
In this talk I will present MultIPAs, a program transformation tool that can augment IPAs benchmarks by (1) applying six syntactic mutations that conserve the program's semantics …
MultIPAs: Applying Program Transformations to Introductory Programming Assignments for Data Augmentation
This paper presents MultIPAs, a program transformation tool that can augment IPAs benchmarks by (1) applying six syntactic mutations that conserve the program's semantics and (2) …
Project Proposal: Learning Variable Mappings to Repair Programs
In this talk I propose to learn how to map the set of variables between different small imperative programs based on both programs' abstract syntax trees (ASTs) using graph neural …
Project Proposal: Learning Variable Mappings to Repair Programs
In this position paper, we propose to learn how to map the set of variables between different small imperative programs based on both programs' abstract syntax trees (ASTs) using …