arXiv subjects

Emeralda Sesari

Publications and source records attributed to Emeralda Sesari.

3 recordsLinked to original sources

arXiv2025

Psychological Safety Framework in Pull-based Open Source Projects

Psychological safety refers to the belief that team members can speak up, ask questions, and make mistakes without fear of negative consequences. Although psychological safety has been studied in traditional software teams, less is known about how it may appear in pull-based open-source software development, where contributors are self-directed and often collaborate voluntarily. This paper introduces a theory-informed framework for understanding how psychological safety may be reflected in pull request interactions. Drawing on psychological safety theory and prior work on software teams and open-source collaboration, the framework identifies observable interaction patterns related to feedback exchange, active participation, asking for input, and visible engagement from relevant project actors. To examine the framework empirically, we operationalize these patterns using nine observable variables from 60,684 pull requests across 26 popular GitHub repositories. The empirical results refine the framework by showing that visible engagement from contributors, reviewers, integrators, and other project members is positively associated with sustained participation, while interaction appears most useful when there is enough discussion without becoming excessive.

cs.SE↗

arXiv2024

It is Giving Major Satisfaction: Why Fairness Matters for Software Practitioners

Software practitioners often encounter workplace unfairness, such as unequal recognition and gender bias. While the link between fairness and job satisfaction has been established in other fields, its relevance to software professionals remains underexplored. This study examines how fairness perceptions relate to job satisfaction among software practitioners, focusing on both general trends and demographic-specific differences. We conducted an online survey of 108 software practitioners, followed by ordinal logistic regression to analyze the relationship between fairness perceptions and job satisfaction in software engineering contexts, with moderation analysis examining how this relationship varies across demographic groups. Our findings indicate that all four fairness dimensions (namely distributive, procedural, interpersonal, and informational fairness) significantly affect overall job satisfaction and satisfaction with job security. Among these, interpersonal fairness has the biggest impact. The relationship between fairness and job satisfaction is stronger for female, ethnically underrepresented, less experienced practitioners, and those with work limitations. Fairness in authorship emerged as an important factor for job satisfaction collectively, while fairness in policy implementation, high-demand situations, and working hours impacted specific demographic groups. This study highlights the role of fairness among software practitioners, offering strategies for organizations to promote fair practices and targeted approaches for certain demographic groups.

cs.SE↗

arXiv2024

Understanding Fairness in Software Engineering: Insights from Stack Exchange

Software practitioners discuss problems at work with peers, in-person and online. These discussions can be technical (e.g., how to fix a bug?) and social (e.g., how to assign work fairly?). While there is a growing body of knowledge exploring fairness problems and solutions in the human and social factors of software engineering, most focus has been on specific problems. This study provides fairness discussions by software practitioners on Stack Exchange sites. We present an exploratory study presenting the fairness experience of software practitioners and fairness expectations in software teams. We also want to identify the fairness aspects software practitioners talk about the most. For example, do they care more about fairness in income or how they are treated in the workplace? Our investigation of fairness discussions on eight Stack Exchange sites resulted in a list of 136 posts (28 questions and 108 answers) manually curated from 4,178 candidate posts. The study reveals that the majority of fairness discussions (24 posts) revolve around the topic of income suggesting that many software practitioners are highly interested in matters related to their pay and how it is fairly distributed. Further, we noted that while not discussed as often, discussions on fairness in recruitment tend to receive the highest number of views and scores. Interestingly, the study shows that unfairness experiences extend beyond the protected attributes. In this study, only 25 out of 136 posts mention protected attributes, with gender mainly being discussed.

cs.SE↗