Publication details
Diagnosable Code Duplication in Introductory Programming
| Authors | |
|---|---|
| Year of publication | 2025 |
| Type | Paper in proceedings |
| Conference | Proceedings of the 56th ACM Technical Symposium on Computer Science Education V. 1 |
| MU Faculty or unit | |
| Citation | |
| web | ACM Digital Library |
| Doi | https://doi.org/10.1145/3641554.3701975 |
| Keywords | automated feedback; code quality; duplicate code; novice programmers; python |
| Description | Code quality is an important aspect of programming education, with duplicate code being a common issue. To help students learn to avoid code duplication, it is useful to provide them with actionable, specific feedback, not just a generic code duplication warning. In this paper, we introduce the concept of diagnosable code duplication, provide an overview of its various types, and propose a framework for automatic detection. We apply the framework to an introductory programming dataset to demonstrate its ability to provide specific feedback and reveal non-trivial differences in detected cases compared to simpler detectors. |
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