Clean Code Tutoring: Makings of a Foundation

Abstract

High-quality code enables sustainable software development, which is a prerequisite of a healthy digital society. To train software engineers to write higher-quality code, we developed an intelligent tutoring system (ITS) grounded in recent advances in ITS design. Its hallmark feature is the refactoring challenge subsystem, which enables engineers to develop procedural knowledge for analyzing code quality and improving it through refactoring. We conducted a focus group discussion with five working software engineers to get feedback for our system. We further conducted a controlled experiment with 51 software engineering learners, where we compared learning outcomes from using our ITS with educational pages offered by a learning management system. We examined the correctness of knowledge, level of knowledge retention after one week and the learners’ perceived engagement. We found no statistically significant difference between the two groups, establishing that our system does not lead to worse learning outcomes. Additionally, instructors can analyze challenge submissions to identify common incorrect coding patterns and unexpected correct solutions to improve the challenges and related hints. We discuss how our instructors benefited from the challenge subsystem, shed light on the need for a specialized ITS design grounded in contemporary theory, and examine the broader educational potential.