Microstructure of Collaboration: The Network of Open Source Software

The open source model is a form of software development with source code that is typically made available to all interested parties. At the core of this process is a decentralized production process: open source software development is done by a network of unpaid software developers. Using data from Sourceforge.net, the largest repository of Open Source Software (OSS) projects and contributors on the Internet, we construct two related networks: A Project network and a Contributor network. Knowledge spillovers may be closely related to the structure of such networks, since contributors who work on several projects likely exchange information and knowledge. Defining the number of downloads as output we finds that (i) additional contributors are associated with an increase in output, but that additional contributors to projects in the giant component are associated with greater output gains than additional contributors to projects outside of the giant component; (ii) Betweenness centrality of the project is positively associated with the number of downloads. (iii) Closeness centrality of the project appears also to be positively associated with downloads, but the effect is not statistically significant over all specifications. (iv) Controlling for the correlation between these two measures of centrality (betweenness and closeness), the degree is not positively associated with the number of downloads. (v) The average closeness centrality of the contributors that participated in a project is positively correlated with the success of the project. These results suggest that there are positive spillovers of knowledge for projects occupying critical junctures in the information flow. When we define projects as connected if and only if they had at least two contributors in common, we again find that additional contributors are associated with an increase in output, and again find that this increase is much higher for projects with strong ties than other projects in the giant component

Technical alignment

This essay discusses the importance of the areas of infrastructure and testing to help digital preservation services demonstrate reliability, transparency, and accountability. It encourages practitioners to build a strong culture in which transparency and collaborations between technical frameworks are valued highly. It also argues for devising and applying agreed-upon metrics that will enable the systematic analysis of preservation infrastructure. The essay begins by defining technical infrastructure and testing in the digital preservation context, provides case studies that exemplify both progress and challenges for technical alignment in both areas, and concludes with suggestions for achieving greater degrees of technical alignment going forward

Measuring success of open source projects using web search engines

What makes an open source project successful? In this paper we show that the traditional factors of success of open source projects, such as number of downloads, deployments or commits are sometimes inconvenient or even insufficient. We then correlate success of an open source project with its popularity on the Web. We show several ideas of how such popularity could be measured using Web search engines and provide experimental results from quantitative analysis of the proposed measures on representative large samples of open source projects from SourceForge

Why Modern Open Source Projects Fail

Open source is experiencing a renaissance period, due to the appearance of modern platforms and workflows for developing and maintaining public code. As a result, developers are creating open source software at speeds never seen before. Consequently, these projects are also facing unprecedented mortality rates. To better understand the reasons for the failure of modern open source projects, this paper describes the results of a survey with the maintainers of 104 popular GitHub systems that have been deprecated. We provide a set of nine reasons for the failure of these open source projects. We also show that some maintenance practices -- specifically the adoption of contributing guidelines and continuous integration -- have an important association with a project failure or success. Finally, we discuss and reveal the principal strategies developers have tried to overcome the failure of the studied projects.Comment: Paper accepted at 25th International Symposium on the Foundations of Software Engineering (FSE), pages 1-11, 201

Open Source Software Development Projects: Determinants of Project Popularity

This paper is an initial exploration of the determinants of open source project success as measured by project popularity. We simultaneously model the impact of project-specific characteristics on project popularity, and the impact of intended users and choice of operating system on the choice of end-user license. These models are jointly estimated using Full Information Maximum Likelihood Method. The results show that the software-user license, age of the project, project status, certain types of potential users, and compatibility with certain operating systems have a statistically significant impact on project popularity. An interesting finding is that GPL, the most widely used software license has an adverse impact on the popularity of an open source project.Open source project, OSS, FLOSS, OSS popularity, OSS success

Measuring Software Process: A Systematic Mapping Study

Context: Measurement is essential to reach predictable performance and high capability processes. It provides support for better understanding, evaluation, management, and control of the development process and project, as well as the resulting product. It also enables organizations to improve and predict its process’s performance, which places organizations in better positions to make appropriate decisions. Objective: This study aims to understand the measurement of the software development process, to identify studies, create a classification scheme based on the identified studies, and then to map such studies into the scheme to answer the research questions. Method: Systematic mapping is the selected research methodology for this study. Results: A total of 462 studies are included and classified into four topics with respect to their focus and into three groups based on the publishing date. Five abstractions and 64 attributes were identified, 25 methods/models and 17 contexts were distinguished. Conclusion: capability and performance were the most measured process attributes, while effort and performance were the most measured project attributes. Goal Question Metric and Capability Maturity Model Integration were the main methods and models used in the studies, whereas agile/lean development and small/medium-size enterprise were the most frequently identified research contexts.Ministerio de Economía y Competitividad TIN2013-46928-C3-3-RMinisterio de Economía y Competitividad TIN2016-76956-C3-2- RMinisterio de Economía y Competitividad TIN2015-71938-RED

Grand Challenges of Traceability: The Next Ten Years

In 2007, the software and systems traceability community met at the first Natural Bridge symposium on the Grand Challenges of Traceability to establish and address research goals for achieving effective, trustworthy, and ubiquitous traceability. Ten years later, in 2017, the community came together to evaluate a decade of progress towards achieving these goals. These proceedings document some of that progress. They include a series of short position papers, representing current work in the community organized across four process axes of traceability practice. The sessions covered topics from Trace Strategizing, Trace Link Creation and Evolution, Trace Link Usage, real-world applications of Traceability, and Traceability Datasets and benchmarks. Two breakout groups focused on the importance of creating and sharing traceability datasets within the research community, and discussed challenges related to the adoption of tracing techniques in industrial practice. Members of the research community are engaged in many active, ongoing, and impactful research projects. Our hope is that ten years from now we will be able to look back at a productive decade of research and claim that we have achieved the overarching Grand Challenge of Traceability, which seeks for traceability to be always present, built into the engineering process, and for it to have "effectively disappeared without a trace". We hope that others will see the potential that traceability has for empowering software and systems engineers to develop higher-quality products at increasing levels of complexity and scale, and that they will join the active community of Software and Systems traceability researchers as we move forward into the next decade of research

Open Source Software Development Projects: Determinants of Project Popularity

This paper is an initial exploration of the determinants of open source project success as measured by project popularity. We simultaneously model the impact of project-specific characteristics on project popularity, and the impact of intended users and choice of operating system on the choice of end-user license. These models are jointly estimated using Full Information Maximum Likelihood Method. The results show that the software-user license, age of the project, project status, certain types of potential users, and compatibility with certain operating systems have a statistically significant impact on project popularity. An interesting finding is that GPL, the most widely used software license has an adverse impact on the popularity of an open source project.Open source project, OSS, FLOSS