Psychological safety continues to pique the interest of scholars in a variety of disciplines of study. Recent research indicates that psychological safety fosters knowledge sharing and norm clarity and complements agile values. Although software quality remains a concern in the software industry, academics have yet to investigate whether and how psychologically safe teams provide superior results. In this study, we explore how psychological safety influences agile teams’ quality-related behaviors aimed at enhancing software quality. To widen the empirical coverage and evaluate the results, we chose a two-phase mixed-methods research design with an exploratory qualitative phase (20 interviews) followed by a quantitative phase (survey study, N = 423). Our findings show that, when psychological safety is established in agile software teams, it induces enablers of a social nature that advance the teams’ ability to pursue software quality. For example, admitting mistakes and taking initiatives equally help teams learn and invest their learning in their future decisions related to software quality. Past mistakes become points of reference for avoiding them in the future. Individuals become more willing to take initiatives aimed at enhancing quality practices and mitigating software quality issues. We contribute to our endeavor to understand the circumstances that promote software quality. Psychological safety requires organizations, their management, agile teams, and individuals to maintain and propagate safety principles. Our results also suggest that technological tools and procedures can be utilized alongside social strategies to promote software quality.

Pull requests facilitate inclusion and improvement of contributions in distributed software projects, especially in open source communities. An author makes a pull request to present a contribution as a candidate for inclusion in a code base. The request is inspected by maintainers and reviewers. The initiated process of review and collaborative improvement can be loaded with debates, opinions, and emotions. It heavily influences the atmosphere in the community. It can demotivate and detract contributors or it can fail to guard the code quality. Both problems put the existence of a community at risk. This mixed methods study aims to elucidate the mechanisms of evaluating pull requests in diverse open source software communities from the perspectives of developers and maintainers. We interviewed 30 participants from five different communities and conducted a survey with N=387 respondents. The data shows that acceptance of contributions in open source depends not only on technical criteria, but also significantly on social and strategic aspects. As a result, we identify three governance styles for pull requests: (1) protective, (2) equitable, and (3) lenient. While the protective style values trustworthiness and reliability of the contributor, the lenient style believes in creating a positive and welcoming environment where contributors are mentored to evolve contributions until the community standards are met. Each of the governance styles safeguards the quality of the project code in different ways. We hope that this material will help researchers and community managers to obtain a more nuanced view on the peculiarities of different communities and the strengths and weakness of their pull requests evaluation process.

Context: Free and Open Source Software (FOSS) communities’ ability to stay viable and productive over time is pivotal for society as they maintain the building blocks that digital infrastructure, products, and services depend on. Sustainability may, however, be characterized from multiple aspects, and less is known how these aspects interplay and impact community outputs, and software quality specifically. Objective: This study, therefore, aims to empirically explore how the different aspects of FOSS sustainability impact software quality. Method: 16 sustainability metrics across four categories were sampled and applied to a set of 217 OSS projects sourced from the Apache Software Foundation Incubator program. The impact of a decline in the sustainability metrics was analyzed against eight software quality metrics using Bayesian data analysis, which incorporates probability distributions to represent the regression coefficients and intercepts. Results: Findings suggest that selected sustainability metrics do not significantly affect defect density or code coverage. However, a positive impact of community age was observed on specific code quality metrics, such as risk complexity, number of very large files, and code duplication percentage. Interestingly, findings show that even when communities are experiencing sustainability, certain code quality metrics are negatively impacted. Conclusion: Findings imply that code quality practices are not consistently linked to sustainability, and defect management and prevention may be prioritized over the former. Results suggest that growth, resulting in a more complex and large codebase, combined with a probable lack of understanding of code quality standards, may explain the degradation in certain aspects of code quality.