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

• Main Authors: Tablatin, Christine Lourrine S, Rodrigo, Ma. Mercedes T
• Format: text
• Published: Archīum Ateneo 2022
• Subjects: Codes (symbols); Eye tracking; Program debugging; Semantics; Bottom up; Complex programs; Eye-tracking; Identifying code; Reading patterns; Reading strategies; Scan path; Simple++; Tracking data; Trend analysis; Students; Computer Engineering; Electrical and Computer Engineering; Engineering; Signal Processing
• Online Access: https://archium.ateneo.edu/discs-faculty-pubs/341; https://archium.ateneo.edu/cgi/viewcontent.cgi?article=1341&context=discs-faculty-pubs
• Institution: Ateneo De Manila University

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.