Automated Feedback for Introductory Programming Exercises
Delivering valuable and personalised feedback to students remains one of the greatest challenges in programming education, particularly in courses with large enrollments. Providing …
C-Pack of IPAs: A C90 Program Benchmark of Introductory Programming Assignments
In this talk I will present C-Pack-IPAs, a publicly available benchmark comprising student-program submissions for 25 distinct introductory programming assignments (IPAs).
C-Pack of IPAs: A C90 Program Benchmark of Introductory Programming Assignments
A C90 Program Benchmark of Introductory Programming Assignments (IPAs), that contains semantically correct, semantically incorrect, and syntactically incorrect programs and a test …
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
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 …
Anonymized Abstract Syntax Trees and Invariant-Based Program Clustering
In this talk I propose a novel approach for program clustering that uses dynamically generated program invariants to cluster semantically equivalent programming assignments.