Toward Optimal Psychological Functioning in AI-driven Software Engineering Tasks: The SEWELL-CARE Assessment Framework
November 13, 2023 Β· Declared Dead Β· π arXiv.org
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Authors
Oussama Ben Sghaier, Jean-Sebastien Boudrias, Houari Sahraoui
arXiv ID
2311.07410
Category
cs.SE: Software Engineering
Citations
1
Venue
arXiv.org
Last Checked
5 months ago
Abstract
In the field of software engineering, there has been a shift towards utilizing various artificial intelligence techniques to address challenges and create innovative tools. These solutions are aimed at enhancing efficiency, automating tasks, and providing valuable support to developers. While the technical aspects are crucial, the well-being and psychology of the individuals performing these tasks are often overlooked. This paper argues that a holistic approach is essential, one that considers the technical, psychological, and social aspects of software engineering tasks. To address this gap, we introduce SEWELL-CARE, a conceptual framework designed to assess AI-driven software engineering tasks from multiple perspectives, with the goal of customizing the tools to improve the efficiency, well-being, and psychological functioning of developers. By emphasizing both technical and human dimensions, our framework provides a nuanced evaluation that goes beyond traditional technical metrics.
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