Decoding Debugging Instruction: A Systematic Literature Review of Debugging Interventions
Abstract
Students learning computer science frequently struggle with debugging errors in their code. These struggles can have significant downstream effects—negatively influencing how students assess their programming ability and contributing to their decision to drop out of CS courses. However, debugging instruction is often an overlooked topic, and instructors report feeling unaware of effective approaches to teach debugging. Within the literature, research on the topic is sporadic, and though there are rigorous and insightful studies to be found, there is a need to synthesize instructional approaches for debugging. In this article, we review research from 2010 to 2022 on debugging interventions. We summarize the common pedagogical approaches for learning and categorize how these target specific cognitive and non-cognitive debugging skills, such as self-efficacy and emotion regulation. We also present a summary of assessment methods and their outcomes in order to discuss intervention efficacy and directions for further research. Our sample displays a diverse variety of debugging interventions and pedagogical approaches, ranging from games to unplugged activities. An evaluation of article results also presents encouraging findings, revealing several interventions that improved debugging accuracy and learning. Still, we notice gaps in interventions addressing non-cognitive debugging skills and observe limited success in guiding students toward adopting systematic debugging strategies. The review concludes with a discussion of future directions and implications for researchers and instructors in the field.
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Unplugged Debugging Activities for Developing Young Learners’ Debugging Skills
Ahn, J., Sung, W., & Black, J. B. (2021) · Journal of Research in Childhood Education · doi:10.1080/02568543.2021.1981503 · Cited by 23 · see citing works
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Introducing computer systems from a programmer's perspective
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Using Electrodermal Activity Measurements to Understand Student Emotions While Programming
Benario, J. G., Cunningham, K. I., Worsley, M. B., & O'Rourke, E. (2022) · ACM Conference on International Computing Education Research (ICER) · doi:10.1145/3501385.3543981 · Cited by 20 · see citing works
Self-citationDebugging as a Context for Fostering Reflection on Critical Thinking and Emotion
DeLiema, D., Dahn, M., Flood, V. J., Asuncion, A., Abrahamson, D., Enyedy, N., & Steen, F. F. (2019) · Routledge eBooks · doi:10.4324/9780429323058-13 · Cited by 18 · see citing works
Proceedings of the 5th international symposium on Software visualization
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Dynamic program visualizations
Cross, J. H., Hendrix, D., Barowski, L. A., et al. (2014) · ACM Technical Symposium on Computer Science Education (SIGCSE) · doi:10.1145/2538862.2538958 · Cited by 16 · see citing works
Reusing Bugged Source Code to Support Novice Programmers in Debugging Tasks
Ardimento, P., Bernardi, M. L., Cimitile, M., et al. (2019) · ACM Transactions on Computing Education · doi:10.1145/3355616 · Cited by 16 · see citing works
Computational Thinking in Augmented Reality: An Investigation of Collaborative Debugging Practices
Chung, C.-Y., & Hsiao, I. (2020) · International Conference of the Immersive Learning Research Network (iLRN) · doi:10.23919/ilrn47897.2020.9155152 · Cited by 14 · see citing works
Analysis of a Process for Introductory Debugging
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CS1 assessment using memory diagrams
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Carter, E. J. (2015) · Journal of computing sciences in colleges · Cited by 11 · see citing works
Art as a Point of Departure for Understanding Student Experience in Learning to Code
Dahn, M., DeLiema, D., & Enyedy, N. (2020) · Teachers College Record The Voice of Scholarship in Education · doi:10.1177/016146812012200802 · Cited by 11 · see citing works
Greifenstein, L., Obermüller, F., Wasmeier, E., Heuer, U., & Fraser, G. (2021) · Workshop in Primary and Secondary Computing Education · doi:10.1145/3481312.3481344 · Cited by 11 · see citing works
Defining and Supporting a Debugging Mindset in Computer Engineering Courses
Duwe, H., Rover, D. T., Jones, P. H., et al. (2022) · 2022 IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie56618.2022.9962605 · Cited by 10 · see citing works
Alrashidi, M., Gardner, M., & Callaghan, V. (2017) · International Conference on Computer and Automation Engineering · doi:10.1145/3057039.3057088 · Cited by 9 · see citing works
An AR/TUI-supported Debugging Teaching Environment
Resnyansky, D., Billinghurst, M., & Dey, A. (2019) · Australian Conference on Human-Computer Interaction (OzCHI) · doi:10.1145/3369457.3369538 · Cited by 7 · see citing works
Edmison, B., & Edwards, S. H. (2020) · IEEE/ACM International Conference on Software Engineering: Software Engineering Education and Training (ICSE-SEET) · doi:10.1145/3377814.3381707 · Cited by 7 · see citing works
Effects of a Pathfinding Program Visualization on Algorithm Development
Lytle, N., Floryan, M., & Barnes, T. M. (2019) · ACM Technical Symposium on Computer Science Education (SIGCSE) · doi:10.1145/3287324.3287391 · Cited by 7 · see citing works
Eranki, K. L. N., & Moudgalya, K. M. (2016) · Conference on Information Technology Education · doi:10.1145/2978192.2978215 · Cited by 6 · see citing works
Proceedings of the second international workshop on Computing education research
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Enhancing Visualizations in Pedagogical Debuggers by Leveraging on Code Analysis
Santos, A. L. (2018) · Koli Calling International Conference on Computing Education Research · doi:10.1145/3279720.3279732 · Cited by 6 · see citing works
Jemmali, C., El‐Nasr, M. S., & Cooper, S. (2022) · International Conference on the Foundations of Digital Games (FDG) · doi:10.1145/3555858.3555892 · Cited by 5 · see citing works
From video games to debugging code
Deitz, S., & Buy, U. A. (2016) · doi:10.1145/2896958.2896964 · Cited by 5 · see citing works
Re-evaluation of debugging in the computer science curriculum
Heilman, R. L., & Ashby, G. (1971) · ACM SIGCSE Bulletin · doi:10.1145/382214.382215 · Cited by 5 · see citing works
Reflective Debugging in Spinoza V3.0
Deeb, F. A., & Hickey, T. J. (2021) · Australasian Computing Education Conference · doi:10.1145/3441636.3442313 · Cited by 5 · see citing works
Proctor, C. P. (2019) · Computer Supported Collaborative Learning · Cited by 4 · see citing works
Falk, R., & Kim, S. S. (2019) · Routledge eBooks · doi:10.4324/9780429315879 · Cited by 4 · see citing works
Read the Debug Manual: A Debugging Manual for CS1 Students
Garcia, R., Liao, C.-J., & Pearce, A. (2022) · IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie56618.2022.9962675 · Cited by 3 · see citing works
Using quicksand to improve debugging practice in post-novice level students
Fenwick, J., & Sutton, P. (2012) · Cited by 1 · see citing works
Flagged first, then by citations
3 of the 182 references couldn’t be matched to a known paper.
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Learning by teaching with ChatGPT : The effect of teachable ChatGPT agent on programming education
Chen, A., Wei, Y., Le, H., & Zhang, Y. (2025) · British Journal of Educational Technology · doi:10.1111/bjet.70001 · Cited by 47 · see citing works
Chandrasekaran, A., Bielicke, L., Shah, D., Janakiraman, H., & Mauriello, M. L. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713269 · Cited by 7 · see citing works
Investigating Debugging Processes: A Scoping Review
Spörer, E., & Michaeli, T. (2025) · Koli Calling International Conference on Computing Education Research · doi:10.1145/3769994.3770005 · Cited by 3 · see citing works
“To this end, in 2024 a systematic review from Yang et al. (2024) synthesized knowledge about interventions on debugging.”
Tshidi, M. (2025) · African Journal of Research in Mathematics Science and Technology Education · doi:10.1080/18117295.2025.2533736 · Cited by 1 · see citing works
“Explicit instruction, which refers to direct and structured teaching where learning goals, strategies and outcomes are modelled, is also crucial for developing CT understanding (Yang et al., 2025).”
Goal‐Setting and Self‐Explanation in Elementary Programming: A Self‐Regulated Learning Study
Chen, M., & Feng, C. (2025) · Journal of Computer Assisted Learning · doi:10.1002/jcal.70177 · Cited by 1 · see citing works
Lee, J., & Yoonhee, S. (2026) · Journal of Educational Computing Research · doi:10.1177/07356331251410016 · Cited by 1 · see citing works
“As a result, recent research in CTeducation has increasingly shifted toward collaborative learning approaches to address pedagogical constraints (Garcia, 2023; Yang et al., 2025; Yin et al., 2025).”
A Taxonomy of Software Debugging Process
Shynkarenko, V., & Zhevaho, O. (2025) · doi:10.55056/ceur-ws.org/vol-4053/s_5_shynkarenko_zhevaho.pdf · Cited by 1 · see citing works
“Existing research has explored various aspects of debugging, including specific techniques, tool development, and cognitive factors [4-6].”
Emerging Debugging Strategies of Novice Programmers: The Role of Self-Efficacy
Yun, H., Sung, G., Feng, Y., et al. (2025) · Proceedings. · doi:10.22318/icls2025.757106
Self-citationBlockNKey: A Game for Teaching Systematic Hypothesis Testing
Agrawal, S., Rallabhandi, I., & Ragavan, S. S. (2025) · ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE) · doi:10.1145/3724363.3729035
“Yet, the learning and teaching of testing and debugging has received lesser attention compared to other CT skills [27, 40, 49].”
Transfer of agent-based modelling skills to educational practice
Patarakin, E., & Шишков, М. С. (2025) · Vestnik of Minin University · doi:10.26795/2307-1281-2025-13-2-3 · Cited by 1 · see citing works
Impact of AI Debugging on Student Code Complexity and Readability: A Literature Review
Thang, H. V., & Vi, T. L. (2025) · International STEM Education Conference (iSTEM-Ed) · doi:10.1109/istem-ed65612.2025.11129285
Explicitly Teaching Debugging in Primary School: Effectiveness, Transferability and Durability
Tuor, N., El-Hamamsy, L., Chevalier, M., Brender, J., & Bumbacher, E. (2025) · European Conference on Modelling and Simulation · doi:10.1145/3769994.3769999 · Cited by 2 · see citing works
“…this intervention (1) did not explore whether the effects were long lasting, and (2) contradicts the results of other studies that found no or limited transfer of CS problem-solving strategies to other contexts [61] (e.g. [43]), likely due to the high similarity between both types of tasks.”
A Qualitative Study of How Computer Science Students Develop Debugging Skills in a Curriculum
Banweer, K., & Trytten, D. (2025) · IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie63693.2025.11328512
Problem-Solving Strategies in Computer Science
Hazzan, O., Ragonis, N., & Lapidot, T. (2026) · Springer eBooks · doi:10.1007/978-3-032-00953-1_10
McKee, D., Lin, Z., Fox, B., et al. (2026) · ACM Technical Symposium on Computer Science Education (SIGCSE) · doi:10.1145/3770762.3772657
“Furthermore, teaching students how to diagnose and debug programs (parallel or not) is arguably as important as teaching code development itself [41].”
Pedagogical Process Models of Undergraduate Computing Tutors
Ciego, E., Steiert, S., & Kapoor, A. (2026) · ACM Technical Symposium on Computer Science Education (SIGCSE) · doi:10.1145/3770761.3777166
Drill-type adaptive debugging to boost programming skills
Pozzan, G., Padova, C., Montuori, C., Arfé, B., & Vardanega, T. (2026) · Computer Science Education · doi:10.1080/08993408.2026.2672717
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Learning by Teaching: A Teachable AI Bot for Software Development Education
Du, S., Shi, J., Shah, D., Distante, D., Heimann, L., & Huang, S. H. (2026) · International Conference on Information and Education Technology (ICIET) · doi:10.1109/iciet69664.2026.11561604
“When students construct the problem space, they externalize a mental model of the program behavior and then form and test hypotheses about causal relationships in code [17].”
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“…CT skills (Misirli & Komis, 2023; Moreno-León & Robles, 2015; Shute et al., 2017), prior studies have noted that testing does not manifest as a single homogeneous action, particularly in tasks where learners physically manipulate rule-based systems (Wambugu & Njeru, 2017; Yang et al., 2025).”
Nixon, J., Bhaduri, S., Shehzad, U., et al. (2026) · Journal of Science Education and Technology · doi:10.1007/s10956-026-10350-4
Evaluating the Effect of Generative AI-Assisted Debugging on Students’ Critical Thinking
Albadarin, Y., Saqr, M., Pope, N., & Tukiainen, M. (2026) · Technology Knowledge and Learning · doi:10.1007/s10758-026-09998-z
CAMP: Cognition-Aligned Multi-stage Automated Program Repair
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Towards a Theory-Based Approach for Analyzing Students' Debugging Processes
Spörer, E., & Michaeli, T. (2026) · doi:10.1145/3830800.3830802
Achievement Goal Motivation Influences Self-Efficacy in AI-Supported Collaborative Programming
Tzou, W., Ma, C.-H., Yeh, Y., & Simarmata, M. T. A. (2026) · International Journal of Engineering Pedagogy (iJEP) · doi:10.3991/ijep.v16i5.62296
How Feedback Literacy Shapes Novice Programmers’ Debugging Trajectories with LLM-Based Feedback
Liu, M., Qian, Y., & Wang, M. (2026) · ACM Turing Celebration Conference - China (ACM TURC) · doi:10.1145/3833142.3833156
“Consequently, considerable research has investigated how to support learners during debugging and improve debugging instruction in programming education[22].”
Investigating How Quizzes Shape Problem-Solving Strategies in Elementary Programming
Quach, N. H., Ghosh, A., Su, M., et al. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-41153-2_8
- Authors
- Yang, S., Baird, M., O’Rourke, E., Brennan, K., & Schneider, B.
- Affiliations
- Harvard University (US)
- Northwestern University (US)
- Venue
- ACM Transactions on Computing Education
- Published
- 2024-11-15
- Volume
- 24
- Issue
- 4
- Pages
- 1-44
- ISSN
- 1946-6226 (ISSN-L)
- OpenAlex
- W4402273575
- Semantic Scholar
- 6351d6f91483ad158a05d4e75f5444c40c8e0b2e
- Cited by
- 29
- References
- 182
- Citations by year
- 2026: 17 · 2025: 12
- FWCI
- 2.19
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- ACM Transactions on Computing Education (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
- Physical Sciences › Mathematics › Statistics and Probability › Statistics Education and Methodologies
- Physical Sciences › Computer Science › Artificial Intelligence › Educational Robotics and Engineering
- Keywords
- computer science education, programming education, teaching methods, self-efficacy, emotion regulation, non-cognitive skills, unplugged activities, game-based learning, intervention efficacy
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