相关论文: Understanding Open Source Contributor Profiles in …

Modern software systems are increasingly including machine learning (ML) as an integral component. However, we do not yet understand the difficulties faced by software developers when learning about ML libraries and using them within their…

Contributors to open source software (OSS) communities assume diverse roles to take different responsibilities. One major limitation of the current OSS tools and platforms is that they provide a uniform user interface regardless of the…

Participation of women in Open Source Software (OSS) is very unbalanced, despite various efforts to improve diversity. This is concerning not only because women do not get the chance of career and skill developments afforded by OSS, but…

Machine Learning (ML) Operations (MLOps) frameworks have been conceived to support developers and AI engineers in managing the lifecycle of their ML models. While such frameworks provide a wide range of features, developers may leverage…

Following continuous software engineering practices, there has been an increasing interest in rapid deployment of machine learning (ML) features, called MLOps. In this paper, we study the importance of MLOps in the context of data…

Machine Learning Operations (MLOps) has become increasingly critical as more organisations move ML models into production. However, the growing landscape of MLOps solutions has introduced complexity for practitioners trying to select…

Open Source Software (OSS) projects offer valuable opportunities to train the next generation of software engineers while benefiting projects and society as a whole. While research has extensively explored student participation in OSS and…

Open-source software (OSS) community managers face significant challenges in retaining contributors, as they must monitor activity and engagement while navigating complex dynamics of collaboration. Current tools designed for managing…

Open Source Software (OSS) has changed drastically over the last decade, with OSS projects now producing a large ecosystem of popular products, involving industry participation, and providing professional career opportunities. But our…

The maintenance and evolution of Free/Libre Open Source Software (FLOSS) projects demand the constant attraction of core developers. In this paper, we report the results of a survey with 52 developers, who recently became core contributors…

Computational research and data analytics increasingly relies on complex ecosystems of open source software (OSS) "libraries" -- curated collections of reusable code that programmers import to perform a specific task. Software documentation…

As big data grows ubiquitous across many domains, more and more stakeholders seek to develop Machine Learning (ML) applications on their data. The success of an ML application usually depends on the close collaboration of ML experts and…

The development of open source software (OSS) is a broad field which requires diverse skill sets. For example, maintainers help lead the project and promote its longevity, technical writers assist with documentation, bug reporters identify…

While machine learning (ML) technology affects diverse stakeholders, there is no one-size-fits-all metric to evaluate the quality of outputs, including performance and fairness. Using predetermined metrics without soliciting stakeholder…

When inspiring software developers to contribute to open source software, the act is often referenced as an opportunity to build tools to support the developer community. However, that is not the only charge that propels contributions --…

The fact that the number of users of open source software (OSS) is practically un-limited and that ultimately the software quality is determined by end users experience, makes the usability an even more critical quality attribute than it is…

Rapid growth of applying Machine Learning (ML) in different domains, especially in safety-critical areas, increases the need for reliable ML components, i.e., a software component operating based on ML. Understanding the bugs…

Usability is an increasing concern in open source software (OSS). Given the recent changes in the OSS landscape, it is imperative to examine the OSS contributors' current valued factors, practices, and challenges concerning usability. We…

Invisible labor is an intrinsic part of the modern workplace, and includes labor that is undervalued or unrecognized such as creating collaborative atmospheres. Open source software (OSS) is software that is viewable, editable and shareable…

Recent advances in deep learning (dl) have led to the release of several dl software libraries such as pytorch, Caffe, and TensorFlow, in order to assist machine learning (ml) practitioners in developing and deploying state-of-the-art deep…