Code Quality Defects Across Introductory Programming Topics

D 2022

Code Quality Defects Across Introductory Programming Topics

EFFENBERGER, Tomáš and Radek PELÁNEK

Basic information

Original name

Code Quality Defects Across Introductory Programming Topics

Authors

EFFENBERGER, Tomáš (203 Czech Republic, guarantor, belonging to the institution) and Radek PELÁNEK (203 Czech Republic, belonging to the institution)

Edition

New York, NY, USA, Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V. 1, p. 941-947, 7 pp. 2022

Publisher

Association for Computing Machinery

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

electronic version available online

References:

ACM Digital library

RIV identification code

RIV/00216224:14330/22:00127006

Organization unit

Faculty of Informatics

ISBN

978-1-4503-9070-5

DOI

http://dx.doi.org/10.1145/3478431.3499415

UT WoS

000884263800136

Keywords in English

introductory programming; python; code quality; feedback

Abstract

V originále

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.

Links

MUNI/A/1195/2021, interní kód MU

Name: Aplikovaný výzkum v oblastech vyhledávání, analýz a vizualizací rozsáhlých dat, zpracování přirozeného jazyka a aplikované umělé inteligence

Investor: Masaryk University

MUNI/A/1230/2021, interní kód MU

Name: Zapojení studentů Fakulty informatiky do mezinárodní vědecké komunity 22 (Acronym: SKOMU)

Investor: Masaryk University

Citovat

EFFENBERGER, Tomáš and Radek PELÁNEK. Code Quality Defects Across Introductory Programming Topics. Online. In Larry Merkle, Maureen Doyle. Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V. 1. New York, NY, USA: Association for Computing Machinery, 2022, p. 941-947. ISBN 978-1-4503-9070-5. Available from: https://dx.doi.org/10.1145/3478431.3499415.

@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 and 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, p.~941-947. ISBN~978-1-4503-9070-5. Available from: https://dx.doi.org/10.1145/3478431.3499415.

Detailed Information on Publication Record