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@inproceedings{2227159,
author = {Effenberger, Tomáš and Pelánek, Radek},
address = {New York, NY, USA},
booktitle = {Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V. 1},
doi = {http://dx.doi.org/10.1145/3478431.3499415},
editor = {Larry Merkle, Maureen Doyle},
keywords = {introductory programming; python; code quality; feedback},
howpublished = {elektronická verze "online"},
language = {eng},
location = {New York, NY, USA},
isbn = {978-1-4503-9070-5},
pages = {941-947},
publisher = {Association for Computing Machinery},
title = {Code Quality Defects Across Introductory Programming Topics},
url = {https://doi.org/10.1145/3478431.3499415},
year = {2022}
}
TY - JOUR
ID - 2227159
AU - Effenberger, Tomáš - Pelánek, Radek
PY - 2022
TI - Code Quality Defects Across Introductory Programming Topics
PB - Association for Computing Machinery
CY - New York, NY, USA
SN - 9781450390705
KW - introductory programming
KW - python
KW - code quality
KW - feedback
UR - https://doi.org/10.1145/3478431.3499415
N2 - Research on feedback in introductory programming focuses mostly on incomplete and incorrect programs. However, most of the functionally correct programs also contain defects that call for feedback. We analyzed 114,000 solutions to 161 short coding problems in Python and compiled a catalog of 32 defects in code quality. We found that most correct solutions contain some defects and that students do not stop making them if they do not receive targeted feedback. The catalog of defects, together with their prevalence across common topics like expressions, loops, and lists, informs educators which defects to address in which lectures and guides the development of exercises on code quality. Additionally, we describe defect detectors, which can be used to generate valuable feedback to students automatically.
ER -
EFFENBERGER, Tomáš a Radek PELÁNEK. Code Quality Defects Across Introductory Programming Topics. Online. In Larry Merkle, Maureen Doyle. \textit{Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V. 1}. New York, NY, USA: Association for Computing Machinery, 2022, s.~941-947. ISBN~978-1-4503-9070-5. Dostupné z: https://dx.doi.org/10.1145/3478431.3499415.
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