ABSTRACT

In this paper, we present an experimental study in which an electroencephalogram (EEG) device was used to measure cognitive load in programmers as they attempted to predict the output of C code snippets. Our goal was to see if particular patterns within the snippet induced higher levels of cognitive load, and if the collected EEG data might provide more detailed insights than performance measures. Our results suggest that while cognitive load can be an influence on code comprehension performance, other human factors, such as a tendency to forget certain programming rules or to misread what the code is asking them to do may also play a role, particularly for novice programmers. We conclude that: (1) different types of code patterns can affect programmers' cognitive processes in disparate ways, (2) neither self-reported data nor brainwave activity alone is a reliable indicator of programmers' level of comprehension for all types of code snippets, (3) EEG techniques could be useful to better understand the relationships between program comprehension, code patterns and cognitive processes, and (4) tests like ours could be useful to identify crucial learning gaps in novice programmers, which, in turn can be leveraged to improve programming tools and teaching strategies.

摘要

在本文中，我们提出了一项实验研究，其中使用脑电图 (EEG) 设备来测量程序员在尝试预测 C 代码片段的输出时的认知负荷。我们的目标是查看片段中的特定模式是否会导致更高水平的认知负荷，以及收集的 EEG 数据是否可以提供比性能测量更详细的见解。我们的研究结果表明，虽然认知负荷可能会影响代码理解性能，但其他人为因素，例如忘记某些编程规则或误读代码要求他们做什么的倾向也可能发挥作用，特别是对于新手程序员. 我们得出结论：（1）不同类型的代码模式可以以不同的方式影响程序员的认知过程，