InnerSource practices, inspired by open source methodologies, offer significant value to organizations by fostering software reuse, improving collaboration, and eliminating inefficiencies [1]. However, quantifying this value is essential to justify investments and sustain InnerSource initiatives. This paper presents a framework to measure the impact of InnerSource projects in the financial industry defining four key areas and their corresponding data gathering strategies. It focuses on metrics for cost savings through reuse, enhanced time-to-market, reduced maintenance expenses, and improved engineering health. By leveraging automated tools, surveys, and analytical models, organizations can assess the financial benefits of InnerSource contributions while fostering transparency and collaboration among teams [2]. This approach provides actionable insights to drive strategic decisions and optimize software development processes.

Abstract Context Current data visualization interfaces predominantly rely on 2-D screens. However, the emergence of virtual reality (VR) devices capable of immersive data visualization has sparked interest in exploring their suitability for visualizing software development data. Despite this, there is a lack of detailed investigation into the effectiveness of VR devices specifically for interacting with software development data visualizations. Objective Our objective is to investigate the following question: “How do VR devices compare to traditional screens in visualizing data about software development?” Specifically, we aim to assess the accuracy of conclusions derived from exploring visualizations for understanding the software development process, as well as the time required to reach these conclusions. Method In our controlled experiment, we recruited N=32 volunteers with diverse backgrounds. Participants interacted with similar data visualizations in both VR and traditional screen environments. For the traditional screen setup, we utilized a commercially available set of interactive dashboards based on Kibana, commonly used by Bitergia customers for data insights. In the VR environment, we designed a set of visualizations, tailored to provide an equivalent dataset within a virtual room. Participants answered questions related to software evolution processes, specifically code review and issue tracking, in both VR and traditional screen environments, for two projects. We conducted statistical analyses to compare the correctness of their answers and the time taken for each question. Results Our findings indicate that the correctness of answers in both environments is comparable. Regarding time spent, we observed similar durations, except for complex questions that required examining multiple interconnected visualizations. In such cases, participants in the VR environment were able to answer questions more quickly. Conclusion Based on our results, we conclude that VR immersion can be equally effective as traditional screen setups for understanding software development processes through visualization of relevant metrics in most scenarios. Moreover, VR may offer advantages in comprehending complex tasks that require navigating through multiple interconnected visualizations. However, further experimentation is necessary to validate and reinforce these conclusions.

Open source communities hosted in large foundations operate in a complex socio-technical ecosystem, which includes a heterogeneous mix of projects and stakeholders. Previous work has thus far investigated the challenges faced in OSS communities from the point of view of specific stakeholders, primarily at the level of individual projects. None have yet studied the challenges faced within a large, federated open source organization. In this paper, we aim to bridge this gap to identify ongoing challenges contributors face in a mature OSS organization. To do so, we surveyed 624 contributors at the Apache Software Foundation (ASF) and ran 11 semi-structured follow up interviews. We validated our findings through member checking with the interviewees as well as the ASF Diversity and Inclusion (D&I) committee. The contributions of this paper include: (1) an empirically-evidenced conceptual model of the 88 challenges that contributors face in a mature OSS foundation and (2) a set of 48 community-recommended strategies for alleviating these challenges. Our results show that even well-established and mature organizations still face a variety of individual and project-specific challenges and that it is difficult to design a comprehensive set of processes and guidelines to match the needs and expectations of a diverse and large federated community. Our conceptual challenges model and associated strategies to mitigate them can provide guidance to other OSS foundations and projects helping them in building better support processes and tools to create a successful, thriving community of contributors.

During 2015, some members of the Xen Project Advisory Board became worried about the performance of their code review process. The Xen Project is a free, open source software project developing one of the most popular virtualization platforms in the industry. They use a pre-commit peer review process similar to that in the Linux kernel, based on email messages. They had observed a large increase over time in the number of messages related to code review, and were worried about how this could be a signal of problems with their code review process.

Many software development projects have introduced mandatory code review for every change to the code. This means that the project needs to devote a significant effort to review all proposed changes, and that their merging into the code base may get considerably delayed. Therefore, all those projects need to understand how code review is working, and the delays it is causing in time to merge.

Researchers working with software repositories, often when building performance or quality models, need to recover traceability links between bug reports in issue tracking repositories and reviews in code review systems. However, very often the information stored in bug tracking repositories is not explicitly tagged or linked to the issues reviewing them. Researchers have to adopt various heuristics to tag the data. These includes, for example, identifying if an issue is a bug report or not. In this study we promote a research artifact in software engineering, a reusable unit of research that can be used to support other research endeavors and has acted as a support material that enabled the creation of the results published in a great number of papers until now – linking issues and reviews of the code review software process. We present two state-of-the-practice algorithms on how to link issues and reviews, selecting as our case study the open source cloud computing project of OpenStack. OpenStack enforces strict development guidelines and rules on the quality of the data in its issue tracking repository. We empirically compare the outcome of the two approaches, highlighting the most prominent one.

Free/libre/open source software projects are usually developed by a geographically distributed community of developers and contributors. In contrast to traditional corporate environments, it is hard to obtain information about how the community is geographically distributed, mainly because participation is open to volunteers and in many cases it is just occasional. During the last years, specially with the increasing implication of institutions, non-profit organizations and companies, there is a growing interest in having information about the geographic location of developers. This is because projects want to be as global as possible, in order to attract new contributors, users and, of course, clients. In this paper we show a methodology to obtain the geographical distribution of a development community by analyzing the source code management system and the mailing lists they use.

The Metrics Grimoire system is composed by a set of tools designed to retrieve data from repositories related to software development. Their aim is to produce organized databases suitable for easy querying with research and industrial purposes. The data in those databases have a similar structure, to easy cross-database studies, and can be enriched with information such as linkage of the multiple identities of actors, or their affiliation. This paper presents the general structure of those databases, and a collection of up-to-date database dumps that are publicly available. They correspond to two well-known projects, Open Stack, and Eclipse, including data from source code management repositories, issue tracking systems, mailing lists, and code review systems.

Because of the distributed and collaborative nature of free / open source software (FOSS) projects, the development effort invested in a project is usually unknown, even after the software has been released. However, this information is becoming of major interest, especially ---but not only--- because of the growth in the number of companies for which FOSS has become relevant for their business strategy. In this paper we present a novel approach to estimate effort by considering data from source code management repositories. We apply our model to the OpenStack project, a FOSS project with more than 1,000 authors, in which several tens of companies cooperate. Based on data from its repositories and together with the input from a survey answered by more than 100 developers, we show that the model offers a simple, but sound way of obtaining software development estimations with bounded margins of error.