An Exploratory Eye Tracking Study on How Developers Classify and Debug Python Code in Different Paradigms

TL;DR

This study uses eye-tracking to explore how developers classify and debug Python code across different paradigms, revealing paradigm-specific comprehension challenges and reading patterns.

Contribution

It provides novel empirical insights into how paradigm features influence code comprehension and debugging, highlighting differences in reading behavior and performance.

Findings

Confusion between Functional and Procedural paradigms

Functional code takes longer to debug

Changing paradigms does not affect debugging success

Abstract

Modern programming languages, such as Python, support language features from several paradigms, such as object-oriented, procedural, and functional. Research has shown that code written in some paradigms can be harder to comprehend, but to date, no research has looked at which paradigm-specific language features impact comprehension. To this end, this study seeks to uncover which paradigm-specific features impactcomprehension and debugging of code or how multi-paradigm code might affect a developer's ability to do so. We present an exploratory empirical eye-tracking study to investigate 1) how developers classify the predominant paradigm in Python code and 2) how the paradigm affects their ability to debug Python code. The goal is to uncover if specific language features are looked at more often while classifying and debugging code with a predominant paradigm. Twenty-nine developers (primarily students) were recruited for the study and were each given four classification and four debugging tasks in Python. Eye movements were recorded during all the tasks. The results indicate confusion in labeling Functional and Procedural paradigms, but not Object-Oriented. The code with predominantly functional paradigms also took the longest to complete. Changing the predominant paradigm did not affect the ability to debug the code, though developers did rate themselves with lower confidence for Functional code. We report significant differences in reading patterns during debugging, especially in the Functional code. During classification, results show that developers do not necessarily read paradigm-relevant token types.