This abstract accompanies the submission of a research artifact related to our paper titled “The Impact of Interruptions on Software Engineering: A Study of Productivity, Stress, and Perception.” The purpose of this artifact is to provide a comprehensive and interactive means for analyzing the effects of different types of interruptions on software engineering tasks. The artifact encompasses various datasets, including physiological data, performance metrics, and self-reported stress scores, which were integral to our research findings.

We are claiming two badges for our artifact: “Available” and “Reusable.” For the “Available” badge, the artifact has been made publicly accessible in an archival repository, with a DOI/link provided for ease of access. For the “Reusable” badge, the artifact is thoroughly documented, validated, and structured for ease of reuse and repurposing, adhering to the norms and standards of our research community. In addition to those badges, we are also claiming the “Results Reproduced v1.1” badge. This badge signifies that the main results of our paper have been independently reproduced by a third party, utilizing the artifacts provided by us. This independent validation underscores the reliability and significance of our findings in the broader research community.

The technology skills assumed for a reviewer evaluating this artifact include proficiency in R programming (for running the data_analysis.R script), basic understanding of Python (for setting up and running the local server with python server.py), and familiarity with data analysis concepts. The artifact includes pre- and post-task survey data, performance data from code-related tasks, physiological data from Empatica EmbracePlus wristband, and self-reported stress and cognitive scores.

No specific Operating System is required for running the artifact, although a standard environment capable of executing R and Python scripts is necessary. The user interface, accessible through a local Python server, enhances the accessibility and usability of the artifact, making it suitable for a wide range of users interested in the intersection of software engineering and cognitive psychology.

In sum, this artifact not only offers a practical tool for replicating our study’s results but also serves as a versatile resource for future research endeavors in understanding and managing the dynamics of interruptions in software engineering.