A Systematic Mapping on Software Fairness: Focus, Trends and Industrial Context
Kessia Nepomuceno, Fabio Petrillo

TL;DR
This paper systematically maps current research on software fairness, highlighting its focus areas, trends, and the gap between academic research and industrial application, emphasizing the need for broader integration across development stages.
Contribution
It introduces a new classification framework for software fairness research and analyzes 95 studies to assess their industrial viability and focus areas.
Findings
Research is expanding but still focused on methods and algorithms.
Primarily emphasizes group fairness and post-processing techniques.
Limited industry collaboration and low to medium TRL levels.
Abstract
Context: Fairness in systems has emerged as a critical concern in software engineering, garnering increasing attention as the field has advanced in recent years. While several guidelines have been proposed to address fairness, achieving a comprehensive understanding of research solutions for ensuring fairness in software systems remains challenging. Objectives: This paper presents a systematic literature mapping to explore and categorize current advancements in fairness solutions within software engineering, focusing on three key dimensions: research trends, research focus, and viability in industrial contexts. Methods: We develop a classification framework to organize research on software fairness from a fresh perspective, applying it to 95 selected studies and analyzing their potential for industrial adoption. Results: Our findings reveal that software fairness research is expanding,…
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Taxonomy
TopicsSoftware Engineering Techniques and Practices · Ethics and Social Impacts of AI · Software Engineering Research
