Scale-driven automatic hint generation for coding style

Abstract

While the use of autograders for code correctness is widespread, less effort has focused on automating feedback for good programming style: the tasteful use of language features and idioms to produce code that is not only correct, but also concise, elegant, and revealing of design intent. We present a system that can provide real-time actionable code style feedback to students in large introductory computer science classes. We demonstrate that in a randomized controlled trial, 70% of students using our system achieved the best style solution to a coding problem in less than an hour, while only 13% of students in the control group achieved the same. Students using our system also showed a statistically-significant greater improvement in code style than students in the control group.