相关论文: Understanding Open Source Contributor Profiles in …
Context: Diversity can impact team communication, productivity, cohesiveness, and creativity. Analyzing the existing knowledge about diversity in open source software (OSS) projects can provide directions for future research and raise…
Context: Contemporary software development organizations lack diversity and the ratios of women in Free and open-source software (FOSS) communities are even lower than the industry average. Although the results of recent studies hint the…
Pull-based development has enabled numerous volunteers to contribute to open-source projects with fewer barriers. Nevertheless, a considerable amount of pull requests (PRs) with valid contributions are abandoned by their contributors,…
With the urgent need to secure supply chains among Open Source libraries, attention has focused on mitigating vulnerabilities detected in these libraries. Although awareness has improved recently, most studies still report delays in the…
Company engagement in open source (OSS) is now the new norm. From large technology companies to startups, companies are participating in the OSS ecosystem by open-sourcing their technology, sponsoring projects through funding or paid…
Evidence suggests that Free/Libre Open Source Software (FLOSS) environments provide unlimited learning opportunities. Community members engage in a number of activities both during their interaction with their peers and while making use of…
Onboarding newcomers is vital for the sustainability of open-source software (OSS) projects. To lower barriers and increase engagement, OSS projects have dedicated experts who provide guidance for newcomers. However, timely responses are…
Background: Open source requires participation of volunteer and commercial developers (users) in order to deliver functional high-quality components. Developers both contribute effort in the form of patches and demand effort from the…
Machine learning (ML) is now commonplace, powering data-driven applications in various organizations. Unlike the traditional perception of ML in research, ML production pipelines are complex, with many interlocking analytical components…
Open Source Software for Social Good (OSS4SG) projects aim to address critical societal challenges, such as healthcare access and community safety. Understanding the community dynamics and contributor patterns in these projects is essential…
Large language models (LLMs) are poised to significantly impact software development, especially in the Open-Source Software (OSS) sector. To understand this impact, we first outline the mechanisms through which LLMs may influence OSS…
The open-source software (OSS) community has historically been dominated by English as the primary language for code, documentation, and developer interactions. However, with growing global participation and better support for non-Latin…
Machine learning (ML) techniques increase the effectiveness of software engineering (SE) lifecycle activities. We systematically collected, quality-assessed, summarized, and categorized 83 reviews in ML for SE published between 2009-2022,…
Software technologies are used by programmers with diverse backgrounds. To fulfill programmers' need for information, enthusiasts contribute numerous learning resources that vary in style and content, which act as documentation for the…
It is well-known that the process of developing machine learning (ML) workflows is a dark-art; even experts struggle to find an optimal workflow leading to a high accuracy model. Users currently rely on empirical trial-and-error to obtain…
The growing popularity of machine learning (ML) and the integration of ML components with other software artifacts has led to the use of continuous integration and delivery (CI/CD) tools, such as Travis CI, GitHub Actions, etc. that enable…
Organizational efforts to utilize and operationalize artificial intelligence (AI) are often accompanied by substantial challenges, including scalability, maintenance, and coordination across teams. In response, the concept of Machine…
Selecting an appropriate task is challenging for contributors to Open Source Software (OSS), mainly for those who are contributing for the first time. Therefore, researchers and OSS projects have proposed various strategies to aid…
Large language models (LLMs) have driven significant progress across a wide range of real-world applications. Realizing such models requires substantial system-level support. Deep learning (DL) frameworks provide this foundation by enabling…
Open-source projects often rely on a small group of highly active contributors known as hero developers. Prior work shows that hero developers are common in many OSS and enterprise projects, yet who qualifies as a hero depends heavily on…