Previous research has revealed that newcomer women are disproportionately affected by gender-biased barriers in open source software (OSS) projects. However, this research has focused mainly on social/cultural factors, neglecting the software tools and infrastructure. To shed light on how OSS tools and infrastructure might factor into OSS barriers to entry, we conducted two studies: (1) a field study with five teams of software professionals, who worked through five use cases to analyze the tools and infrastructure used in their OSS projects; and (2) a diary study with 22 newcomers (9 women and 13 men) to investigate whether the barriers matched the ones identified by the software professionals. The field study produced a bleak result: software professionals found gender biases in 73 percent of all the newcomer barriers they identified. Further, the diary study confirmed these results: Women newcomers encountered gender biases in 63 percent of barriers they faced. Fortunately, many kinds of barriers and biases revealed in these studies could potentially be ameliorated through changes to the OSS software environments and tools.

Software developers who want to start contributing to an Open Source Software (OSS) project often struggle to find appropriate first tasks. The voluntary, self-organizing distribution of decentralized labor and the distinct nature of some OSS projects intensifies this challenge. Mentors, who work closely with newcomers, develop strategies to recommend tasks. However, to date neither the challenges mentors face in recommending tasks nor their strategies have been formally documented or studied. In this paper, we interviewed mentors of well-established OSS projects (n=10) and qualitatively analyzed their answers to identify both challenges and strategies related to recommending tasks for newcomers. Then, we employed a survey (n=30) to map the strategies to challenges and collect additional strategies. Our study identified 7 challenges and 13 strategies related to task recommendation. Strategies such as "tagging the issues based on difficulty," "adding documentation," "assigning a small task first and then challenge the newcomers with bigger tasks," and "dividing tasks into smaller pieces" were frequently mentioned as ways to overcome multiple challenges. Our results provide insights for mentors about the strategies OSS communities can use to guide their mentors and for tool builders who design automated support for task assignment.

While open-source software has become ubiquitous, its sustainability is in question: without a constant supply of contributor effort, open-source projects are at risk. While prior work has extensively studied the motivations of open-source contributors in general, relatively little is known about how people choose which project to contribute to, beyond personal interest. This question is especially relevant in transparent social coding environments like GitHub, where visible cues on personal profile and repository pages, known as signals, are known to impact impression formation and decision making. In this paper, we report on a mixed-methods empirical study of the signals that influence the contributors' decision to join a GitHub project. We first interviewed 15 GitHub contributors about their project evaluation processes and identified the important signals they used, including the structure of the README and the amount of recent activity. Then, we proceeded quantitatively to test out the impact of each signal based on the data of 9,977 GitHub projects. We reveal that many important pieces of information lack easily observable signals, and that some signals may be both attractive and unattractive. Our findings have direct implications for open-source maintainers and the design of social coding environments, e.g., features to be added to facilitate better project searching experience.

Research has revealed that significant barriers exist when entering Open-Source Software (OSS) communities and that women disproportionately experience such barriers. However, this research has focused mainly on social/cultural factors, ignoring the environment itself --- the tools and infrastructure. To shed some light onto how tools and infrastructure might somehow factor into OSS barriers to entry, we conducted a field study with five teams of software professionals, who worked through five use-cases to analyze the tools and infrastructure used in their OSS projects. These software professionals found tool/infrastructure barriers in 7% to 71% of the use-case steps that they analyzed, most of which are tied to newcomer barriers that have been established in the literature. Further, over 80% of the barrier types they found include attributes that are biased against women.