Automated clustering and program repair for introductory programming assignments

Sumit Gulwani, Ivan Radiček, Florian Zuleger
2018 Proceedings of the 39th ACM SIGPLAN Conference on Programming Language Design and Implementation - PLDI 2018  
Providing feedback on programming assignments is a tedious task for the instructor, and even impossible in large Massive Open Online Courses with thousands of students. Previous research has suggested that program repair techniques can be used to generate feedback in programming education. In this paper, we present a novel fully automated program repair algorithm for introductory programming assignments. The key idea of the technique, which enables automation and scalability, is to use the
more » ... ing correct student solutions to repair the incorrect attempts. We evaluate the approach in two experiments: (I) We evaluate the number, size and quality of the generated repairs on 4,293 incorrect student attempts from an existing MOOC. We find that our approach can repair 97% of student attempts, while 81% of those are small repairs of good quality. (II) We conduct a preliminary user study on performance and repair usefulness in an interactive teaching setting. We obtain promising initial results (the average usefulness grade 3.4 on a scale from 1 to 5), and conclude that our approach can be used in an interactive setting.
doi:10.1145/3192366.3192387 dblp:conf/pldi/GulwaniRZ18 fatcat:snqnsyss25aizi46qd4q5fsajy