Rockstar Effect in Distributed Project Management on GitHub Social Networks

The internet has become increasingly social, opening up new space for online collaboration and distributed project management. Decentralized management techniques such as open-source software, distributed development, and software-as-a-service allow software developers to easily connect online and to solve complex problems collaboratively. Online rockstars, who are well-respected in a community and are followed by numerous other users, often influence the decisions of project managers and clients in software development. Understanding the effects of these rockstars can greatly facilitate technology development and adoption in distributed project management. This paper presents a study of the GitHub social network to understand rockstar effect in distributed project management. In GitHub, developers often collaborate in distributed teams and interact in their online social networks, which evolve with the popularity of software repositories and actions of rockstars. To understand how rockstars influence the popularity of software repositories, this research constructed temporal social networks from 2015 to 2017 between 13.5 million software repositories and 2.6 million GitHub users and examined the evolvement of the behavior of 245,501 rockstar followers. The results show that the more followers a rockstar has, the more triadic events there are in his/her participated repository. And the difference of a number of events between top rockstar and other rockstars is much higher in participative events than in contributive events, indicating higher triadic influence from top rockstar in those events for technology development in distributed project management

Necessity of establishing an open source military R&D platform to promote AI development in defense

Nations with advanced military capabilities are now focusing on developing AI algorithms for weapon system intellectualization development to retain their dominance. However, such endeavors are expensive in terms of time, effort, and resources, so it is necessary to develop it using open source to expand sharing and cooperation with industry–academic–government research and development collaboration. This study is aimed at elaborating the need for adoption of it and suggesting future implementation and improvement of open source SW in military despite the negative impact of security vulnerabilities when applied to the military weapon system. For this, the present study was design to investigate the benefit (intercommunity and cooperation) and harm (military sovereignty and technology vulnerability) of this open source platform through analysis of domestic and international case with defense area. The results of the study indicate that establishing an appropriate platform can help secure military sovereignty and prevent technology subordination, increase the efficiency of AI R&D, ensure collaboration and connectivity between weapons systems, and strengthen software security

Qual a relevância da literatura open-source sob a perspectiva de profissionais e estudantes de graduação

Trabalho de Conclusão de Curso (graduação)—Universidade de Brasília, Instituto de Ciências Exatas, Departamento de Ciência da Computação, 2019.Com um aumento significativo de trabalhos de pesquisa em Engenharia de Software nos últimos anos, especialmente daqueles focados no modelo Open-Source, devido à sua ascendência relativamente recente, uma questão que naturalmente surge diz respeito à sua relevância. Diante desse questionamento, esse trabalho busca investigar se a pesquisa em Engenharia de Software, focada particularmente no modelo Open-Source, produz resultados considerados relevantes na percepção dos usuários. Para investigar a relevância percebida da literatura disponível nós conduzimos dois Surveys: um na Universidade de Brasília (UnB), em que nós convidamos os estudantes a avaliar a relevância de ideias e resultados contidos em sumários construídos a partir de trabalhos de pesquisa publicados em um período de dez anos, e outro com profissionais e pesquisadores que contribuem de alguma forma com as comunidades Open-Source, onde a relevância de artigos publicados em um período de cinco anos foi avaliada com base na leitura do título e resumo originais dos trabalhos. Dessa forma, é possível apresentar um feedback dos estudantes, profissionais e pesquisadores, possibilitando o discernimento de questões de pesquisa que são consideradas relevantes e consequentemente passíveis de serem disseminadas dentro da comunidade Open-Source e acadêmica. Durante a investigação da relevância dos trabalhos selecionados, a abordagem proposta considerou duas questões: Uma sobre o escopo dos trabalhos identificados e outra sobre a relevância percebida desses trabalhos. Para a primeira questão, foram conduzidos dois mapeamentos sistemáticos da literatura em bases distintas, os quais revelaram um conjunto de trabalhos compostos por uma grande diversidade de resultados. Utilizando sumários elaborados a partir desses trabalhos para o primeiro Survey e os próprios resumos para o segundo, foram então aplicados os Surveys aos estudantes, profissionais e pesquisadores. Nossos achados representam um cenário muito favorável para a pesquisa voltada ao modelo open source, indicando que 77.01% dos estudantes consideram os trabalhos relevantes e que 80.56% dos pesquisadores e desenvolvedores também consideraram os trabalhos como relevantes.The number of Software Engineering research papers has grown significantly over the last few years, especially those related to the open source model. Naturally, this fact raises the question of whether the research on these areas are considered to be relevant or not. This paper aims at accessing the perspective of the open source community as well as the perspective of undergraduate students regarding the relevance of the open source research. To answer about the relevance of available work, two questions were addressed: one about the scope of the studies and another about the perceived quality of these works. For the first one, two Systematic Literature Mappings were performed, each for a different survey to be conducted, revealing two set of works composed by a great diversity of results. Using these identified works, two different surveys were conducted, one with developers and researchers from several open source communities around the world and another at University of Brasília (UnB) where undergraduate students of Computer Science and related courses were invited to rate the relevance of the selected research papers. Both surveys revealed a very positive outlook on the relevance of this research area, where 77.01% of the students and 80.56% of the the open source practitioners rated the works as relevant. With these results, in addition to providing an overview of the current open source research scenario, it is also possible to give feedback from the open source community and students, providing a way to produce useful and, consequently, more disseminated works among open source practitioners

Open source software GitHub ecosystem: a SEM approach

Open source software (OSS) is a collaborative effort. Getting affordable high-quality software with less probability of errors or fails is not far away. Thousands of open-source projects (termed repos) are alternatives to proprietary software development. More than two-thirds of companies are contributing to open source. Open source technologies like OpenStack, Docker and KVM are being used to build the next generation of digital infrastructure. An iconic example of OSS is 'GitHub' - a successful social site. GitHub is a hosting platform that host repositories (repos) based on the Git version control system. GitHub is a knowledge-based workspace. It has several features that facilitate user communication and work integration. Through this thesis I employ data extracted from GitHub, and seek to better understand the OSS ecosystem, and to what extent each of its deployed elements affects the successful development of the OSS ecosystem. In addition, I investigate a repo's growth over different time periods to test the changing behavior of the repo. From our observations developers do not follow one development methodology when developing, and growing their project, and such developers tend to cherry-pick from differing available software methodologies. GitHub API remains the main OSS location engaged to extract the metadata for this thesis's research. This extraction process is time-consuming - due to restrictive access limitations (even with authentication). I apply Structure Equation Modelling (termed SEM) to investigate the relative path relationships between the GitHub- deployed OSS elements, and I determine the path strength contributions of each element to determine the OSS repo's activity level. SEM is a multivariate statistical analysis technique used to analyze structural relationships. This technique is the combination of factor analysis and multiple regression analysis. It is used to analyze the structural relationship between measured variables and/or latent constructs. This thesis bridges the research gap around longitude OSS studies. It engages large sample-size OSS repo metadata sets, data-quality control, and multiple programming language comparisons. Querying GitHub is not direct (nor simple) yet querying for all valid repos remains important - as sometimes illegal, or unrepresentative outlier repos (which may even be quite popular) do arise, and these then need to be removed from each initial OSS's language-specific metadata set. Eight top GitHub programming languages, (selected as the most forked repos) are separately engaged in this thesis's research. This thesis observes these eight metadata sets of GitHub repos. Over time, it measures the different repo contributions of the deployed elements of each metadata set. The number of stars-provided to the repo delivers a weaker contribution to its software development processes. Sometimes forks work against the repo's progress by generating very minor negative total effects into its commit (activity) level, and by sometimes diluting the focus of the repo's software development strategies. Here, a fork may generate new ideas, create a new repo, and then draw some original repo developers off into this new software development direction, thus retarding the original repo's commit (activity) level progression. Multiple intermittent and minor version releases exert lesser GitHub JavaScript repo commit (or activity) changes because they often involve only slight OSS improvements, and because they only require minimal commit/commits contributions. More commit(s) also bring more changes to documentation, and again the GitHub OSS repo's commit (activity) level rises. There are both direct and indirect drivers of the repo's OSS activity. Pulls and commits are the strongest drivers. This suggests creating higher levels of pull requests is likely a preferred prime target consideration for the repo creator's core team of developers. This study offers a big data direction for future work. It allows for the deployment of more sophisticated statistical comparison techniques. It offers further indications around the internal and broad relationships that likely exist between GitHub's OSS big data. Its data extraction ideas suggest a link through to business/consumer consumption, and possibly how these may be connected using improved repo search algorithms that release individual business value components

Modeling User-Affected Software Properties for Open Source Software Supply Chains

Background: Open Source Software development community relies heavily on users of the software and contributors outside of the core developers to produce top-quality software and provide long-term support. However, the relationship between a software and its contributors in terms of exactly how they are related through dependencies and how the users of a software affect many of its properties are not very well understood. Aim: My research covers a number of aspects related to answering the overarching question of modeling the software properties affected by users and the supply chain structure of software ecosystems, viz. 1) Understanding how software usage affect its perceived quality; 2) Estimating the effects of indirect usage (e.g. dependent packages) on software popularity; 3) Investigating the patch submission and issue creation patterns of external contributors; 4) Examining how the patch acceptance probability is related to the contributors\u27 characteristics. 5) A related topic, the identification of bots that commit code, aimed at improving the accuracy of these and other similar studies was also investigated. Methodology: Most of the Research Questions are addressed by studying the NPM ecosystem, with data from various sources like the World of Code, GHTorrent, and the GiHub API. Different supervised and unsupervised machine learning models, including Regression, Random Forest, Bayesian Networks, and clustering, were used to answer appropriate questions. Results: 1) Software usage affects its perceived quality even after accounting for code complexity measures. 2) The number of dependents and dependencies of a software were observed to be able to predict the change in its popularity with good accuracy. 3) Users interact (contribute issues or patches) primarily with their direct dependencies, and rarely with transitive dependencies. 4) A user\u27s earlier interaction with the repository to which they are contributing a patch, and their familiarity with related topics were important predictors impacting the chance of a pull request getting accepted. 5) Developed BIMAN, a systematic methodology for identifying bots. Conclusion: Different aspects of how users and their characteristics affect different software properties were analyzed, which should lead to a better understanding of the complex interaction between software developers and users/ contributors