APSIPA Transactions on Signal and Information Processing > Vol 11 > Issue 1

Identifying Code Reading Strategies in Debugging using STA with a Tolerance Algorithm

Christine Lourrine S. Tablatin, Ateneo de Manila University and Pangasinan State University, Philippines, tablatinchristine@gmail.com , Maria Mercedes T. Rodrigo, Ateneo de Manila University, Philippines
 
Suggested Citation
Christine Lourrine S. Tablatin and Maria Mercedes T. Rodrigo (2022), "Identifying Code Reading Strategies in Debugging using STA with a Tolerance Algorithm", APSIPA Transactions on Signal and Information Processing: Vol. 11: No. 1, e6. http://dx.doi.org/10.1561/116.00000040

Publication Date: 03 Mar 2022
© 2022 C. L. S. Tablatin and M. M. T. Rodrigo
 
Subjects
 

Share

Open Access

This is published under the terms of CC BY-NC.

Downloaded: 906 times

In this article:
Introduction 
Methodology 
Results and Discussion 
Discussion 
Threats to Validity 
Conclusion 
References 

Abstract

The purpose of this study was to identify the common code reading strategies of the high and low performing students engaged in a debugging task. Using Scanpath Trend Analysis (STA) with a tolerance on eye tracking data, common scanpaths of high and low performing students were generated. The common scanpaths revealed differences in the code reading patterns and code reading strategies of high and low performing students. High performing students follow a bottom-up code reading strategy when debugging complex programs with logical and semantic errors. A top-down code reading strategy is employed when debugging programs with simple control structures, few lines of code, and simple error types. These results imply that high performing students use flexible debugging strategies based on the program structure. The generated common scanpaths of the low performing students, on the other hand, showed erratic code reading patterns, implying that no obvious code reading strategy was applied. The identified code reading strategies of the high performing students could be explicitly taught to low performing students to help improve their debugging performance.

DOI:10.1561/116.00000040

Companion

APSIPA Transactions on Signal and Information Processing Special Issue - Information Processing for Understanding Human Attentional and Affective States: Articles Overview
See the other articles that are part of this special issue.