A tool-supported approach to integrate cognitive indicators into the Visual Studio Code

Abstract

Wearable devices capable of capturing psychophysiological data have emerged as a tangible reality. Recent academic investigations emphasize the pivotal role of developers’ cognitive indicators, such as attention levels and cognitive load, in influencing their effectiveness in understanding and managing code-related tasks. However, existing Integrated Development Environments (IDEs) and code editors, such as Visual Studio (VS) Code, lack comprehensive contextual information on cognitive indicators alongside source code. This article, therefore, introduces CognIDE, a novel tool-supported methodology aimed at seamlessly integrating psy-chophysiological data linked to cognitive indicators into VS Code. Addressing this crucial gap, CognIDE enriches VS Code by offering actionable contextual cues alongside dynamic source code. The evaluation of CognIDE, involving a survey with six industry professionals and in-depth interviews, examined its perceived utility, ease of use, and real-world applicability. Encouragingly, professionals demonstrated high acceptance, indicating CognIDE’s potential to identify and prioritize code segments with specific cognitive indicators, notably related to bugs or code comprehension issues. This underscores CognIDE’s promise in improving code review processes.