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Leveraging Error Information from Identical Learning Materials for Debugging Effectiveness

by Keiichi Takahashi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 187 - Number 18
Year of Publication: 2025
Authors: Keiichi Takahashi
10.5120/ijca2025925263

Keiichi Takahashi . Leveraging Error Information from Identical Learning Materials for Debugging Effectiveness. International Journal of Computer Applications. 187, 18 ( Jul 2025), 51-56. DOI=10.5120/ijca2025925263

@article{ 10.5120/ijca2025925263,
author = { Keiichi Takahashi },
title = { Leveraging Error Information from Identical Learning Materials for Debugging Effectiveness },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2025 },
volume = { 187 },
number = { 18 },
month = { Jul },
year = { 2025 },
issn = { 0975-8887 },
pages = { 51-56 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume187/number18/leveraging-error-information-from-identical-learning-materials-for-debugging-effectiveness/ },
doi = { 10.5120/ijca2025925263 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2025-07-09T01:07:36.651666+05:30
%A Keiichi Takahashi
%T Leveraging Error Information from Identical Learning Materials for Debugging Effectiveness
%J International Journal of Computer Applications
%@ 0975-8887
%V 187
%N 18
%P 51-56
%D 2025
%I Foundation of Computer Science (FCS), NY, USA
Abstract

As programming education has become more widespread, helping novices fix bugs remains a significant challenge. While various support methods have been studied, implementing them in educational settings requires customization of specific teaching materials, which demands time and technical resources. This study focuses on the fact that teaching materials are used repeatedly in educational settings. If error information from previous uses of the same teaching materials can help debug similar errors that occur later, it enables debugging support tailored to specific materials by simply conducting classes and collecting error data. To test this hypothesis, a system is proposed that automatically collects error information, searches for similar errors, and suggests appropriate solutions. Experiments were conducted using this system by collecting error data from programming practice courses at Kindai University in 2021 and 2022. The results showed that past error information was able to effectively support debugging for approximately 30% of future errors, confirming the potential of this approach as a new method to support novice programming learning.

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Index Terms

Computer Science
Information Sciences
Algorithms
Design
Experimentation
Human Factors
Measurement
Education

Keywords

Programming Education Debugging Support Error Information Sharing Similar Error Retrieval Web Application Development

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