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.
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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
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher United States of America
Confidentiality degree is not subject to a state or trade secret
Publication form electronic version available online
WWW 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
Tags core_A, firank_A
Tags International impact, Reviewed
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 28/3/2023 12:00.
Abstract
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 MUName: 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 MUName: Zapojení studentů Fakulty informatiky do mezinárodní vědecké komunity 22 (Acronym: SKOMU)
Investor: Masaryk University
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