Using CognitIDE to Capture Developers' Cognitive Load via Physiological Activity During Everyday Software Development Tasks
March 05, 2025 Β· Declared Dead Β· π Ide
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Fabian Stolp, Charlotte Brandebusemeyer, Franziska Hradilak, Lara Kursawe, Magnus Menger, Franz Sauerwald, Bert Arnrich
arXiv ID
2503.03537
Category
cs.SE: Software Engineering
Citations
0
Venue
Ide
Last Checked
5 months ago
Abstract
Integrated development environments (IDE) support developers in a variety of tasks. Unobtrusively capturing developers' cognitive load while working on different programming tasks could help optimize developers' work experience, increase their productivity, and positively impact code quality. In this paper, we propose a study in which the IntelliJ-based IDE plugin CognitIDE is used to collect, map, and visualize software developers' physiological activity data while they are working on various software development tasks. In a feasibility study, participants completed four simulated everyday working tasks of software developers - coding, debugging, code documentation, and email writing - based on Java open source code in the IDE whilst their physiological activity was recorded. Between the tasks, the participants' perceived workload was assessed. Feasibility testing showed that CognitIDE could successfully be used for data collection sessions of one hour, which was the most extended duration tested and was well-perceived by those working with it. Furthermore, the recorded physiological activity indicated higher cognitive load during working tasks compared to baseline recordings. This suggests that cognitive load can be assessed, mapped to code positions, visualized, and discussed with participants in such study setups with CognitIDE. These promising results indicate the usefulness of the plugin for diverse study workflows in a natural IDE environment.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Software Engineering
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Microservices: yesterday, today, and tomorrow
π
π
The Cartographer
A Survey of Machine Learning for Big Code and Naturalness
R.I.P.
π»
Ghosted
An Overview on Smart Contracts: Challenges, Advances and Platforms
R.I.P.
π»
Ghosted
Slither: A Static Analysis Framework For Smart Contracts
R.I.P.
π»
Ghosted
ContractFuzzer: Fuzzing Smart Contracts for Vulnerability Detection
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted