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Debugging by skilled and novice programmers

Authors:

L. Gugerty,

G. OlsonAuthors Info & Claims

ACM SIGCHI Bulletin, Volume 17, Issue 4

Pages 171 - 174

https://doi.org/10.1145/22339.22367

Published: 01 April 1986 Publication History

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Abstract

Two experiments investigated expert-novice differences in debugging computer programs. Debugging was done on programs provided to the subject, and were run on a microcomputer. The programs were in LOGO in Exp. 1 and Pascal in Exp. 2. Experts debugged more quickly and accurately, largely because they generated high quality hypotheses on the basis of less study of the code than novices. Further, novices frequently added bugs to the program during the course of trying to find the original one. At least for these simple programs, experts superior debugging performance seemed to be due primarily to their superior ability to comprehend the program.

References

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Jeffries, R. Computer program debugging by experts. Paper presented at the meetings of the Psychonomic Soci ety, 1981.

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Jeffries, R. A comparison of the debugging behavior of expert and novice programmers. Paper presented at the meetings of the American Educationa/Research Association, 1982.

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McKeithen, K.B., Reitman, J.S., Rueter, H.H.& Hirtle, S.C. Knowledge organization and skill differences in computer programmers. Cognitive Psychology, 1981, 13, 307-325.

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Weber TWiniker CMayer S(2024)An Investigation of How Software Developers Read Machine Learning CodeProceedings of the 18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement10.1145/3674805.3686678(165-176)Online publication date: 24-Oct-2024
https://dl.acm.org/doi/10.1145/3674805.3686678
Jayathirtha GFields DKafai Y(2024)Distributed debugging with electronic textiles: understanding high school student pairs’ problem-solving strategies, practices, and perspectives on repairing physical computing projectsComputer Science Education10.1080/08993408.2023.229773834:4(718-752)Online publication date: 21-Jan-2024
https://doi.org/10.1080/08993408.2023.2297738
Lee JKazerouni ASiu CMigler TDoyle MStephenson BDorn BSoh LBattestilli L(2023)Exploring the Impact of Cognitive Awareness Scaffolding for Debugging in an Introductory Programming ClassProceedings of the 54th ACM Technical Symposium on Computer Science Education V. 110.1145/3545945.3569871(1007-1013)Online publication date: 2-Mar-2023
https://dl.acm.org/doi/10.1145/3545945.3569871
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Debugging by skilled and novice programmers

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Debugging by skilled and novice programmers
CHI '86: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Two experiments investigated expert-novice differences in debugging computer programs. Debugging was done on programs provided to the subject, and were run on a microcomputer. The programs were in LOGO in Exp. 1 and Pascal in Exp. 2. Experts debugged ...
An expert system for debugging novice programmers' pascal programs
CSC '89: Proceedings of the 17th conference on ACM Annual Computer Science Conference

To better understand the analysis process used in developing expert systems, i.e. knowledge engineering, we have undertaken the creation of a relatively large expert system. This expert system will aid students in locating and correcting errors in their ...
Understanding the bugs of novice programmers (pascal, human-computer interaction, problem solving)

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Information

Published In

ACM SIGCHI Bulletin Volume 17, Issue 4

Special issue: CHI '86 Conference Proceedings

April 1986

346 pages

ISSN:0736-6906

DOI:10.1145/22339

Editors:
M. Mantei,
P. Orbeton

Issue’s Table of Contents

CHI '86: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
April 1986
362 pages
ISBN:0897911806
DOI:10.1145/22627
Editors:
Marilyn Mantei,
Peter Orbeton

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 April 1986

Published in SIGCHI Volume 17, Issue 4

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Cited By

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Weber TWiniker CMayer S(2024)An Investigation of How Software Developers Read Machine Learning CodeProceedings of the 18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement10.1145/3674805.3686678(165-176)Online publication date: 24-Oct-2024
https://dl.acm.org/doi/10.1145/3674805.3686678
Jayathirtha GFields DKafai Y(2024)Distributed debugging with electronic textiles: understanding high school student pairs’ problem-solving strategies, practices, and perspectives on repairing physical computing projectsComputer Science Education10.1080/08993408.2023.229773834:4(718-752)Online publication date: 21-Jan-2024
https://doi.org/10.1080/08993408.2023.2297738
Lee JKazerouni ASiu CMigler TDoyle MStephenson BDorn BSoh LBattestilli L(2023)Exploring the Impact of Cognitive Awareness Scaffolding for Debugging in an Introductory Programming ClassProceedings of the 54th ACM Technical Symposium on Computer Science Education V. 110.1145/3545945.3569871(1007-1013)Online publication date: 2-Mar-2023
https://dl.acm.org/doi/10.1145/3545945.3569871
Alaboudi ALaToza T(2023)What constitutes debugging? An exploratory study of debugging episodesEmpirical Software Engineering10.1007/s10664-023-10352-528:5Online publication date: 11-Sep-2023
https://doi.org/10.1007/s10664-023-10352-5
Lehman JGordon JJain SNdousse KYeh CStanley K(2023)Evolution Through Large ModelsHandbook of Evolutionary Machine Learning10.1007/978-981-99-3814-8_11(331-366)Online publication date: 2-Nov-2023
https://doi.org/10.1007/978-981-99-3814-8_11
Pérez Angulo JCastro Rosales J(2022)JUSECA: UN JUEGO SERIO PARA LA COMPRENSIÓN DE ALGORITMOSInnoeduca. International Journal of Technology and Educational Innovation10.24310/innoeduca.2022.v8i1.84658:1(5-16)Online publication date: 1-Jun-2022
https://doi.org/10.24310/innoeduca.2022.v8i1.8465
Zhang YPaquette LPinto JLiu QFan A(2022)Combining latent profile analysis and programming traces to understand novices’ differences in debuggingEducation and Information Technologies10.1007/s10639-022-11343-728:4(4673-4701)Online publication date: 22-Oct-2022
https://doi.org/10.1007/s10639-022-11343-7
Michaeli TRomeike R(2020)Investigating Students’ Preexisting Debugging Traits: A Real World Escape Room StudyProceedings of the 20th Koli Calling International Conference on Computing Education Research10.1145/3428029.3428044(1-10)Online publication date: 19-Nov-2020
https://dl.acm.org/doi/10.1145/3428029.3428044
Li PKo ABegel A(2020)What distinguishes great software engineers?Empirical Software Engineering10.1007/s10664-019-09773-y25:1(322-352)Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.1007/s10664-019-09773-y
Michaeli TRomeike R(2019)Improving Debugging Skills in the ClassroomProceedings of the 14th Workshop in Primary and Secondary Computing Education10.1145/3361721.3361724(1-7)Online publication date: 23-Oct-2019
https://dl.acm.org/doi/10.1145/3361721.3361724
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