Open source software GitHub ecosystem: a SEM approach

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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.

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Analysis of the development of open GIS software and QGIS system
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Abstract. Open source software could emerge thanks to the development of the Internet, development tools, and computer literacy in general. The most attractive parameter of open source GIS software is a free license. The rapid pace of development, attracting developers from all over the world and high modularity stimulate the innovative nature of open source software. Here, the introduction of new technologies does not meet with opposition, but rather welcomes. These circumstances, as well as elucidation of the functional capabilities of such GIS, become very important in the search for means of providing the educational process with modern GIS software, which is traditionally an expensive proprietary software. Goal: Analysis of up-to-date GIS software protection and visual accessibility of the QGIS system in the first place with studying geoinformation systems.Quantum GIS (QGIS) is an open source software (GIS) geographic information system (GIS). Open software is one of the most interesting technological phenomena of the present, owing to its rapid growth in the development of the Internet, development tools and computer literacy in general. The key role in the creation, development and support of open source software is played, as a rule, by the community of developers forming around individual software products: commercial companies, groups of enthusiasts or research organizations. The term open source was proposed by Bruce Perens, one of the key leaders in the Open Source and Free Software movement, cofounder with Eric Raymind in 1998 of the Open Source Initiative (OSI), an open source software development organization that promotes and provides technical open source support. This open source term is used by OSI to determine whether a software license complies with open source standards. The main features of open source software as defined include free distribution, accessible source code, permission to modify this source code. At the same time, even successful open source software products require companies on the market ready to provide technical support and advice on issues related to the selected products. However, the number of companies providing support services for open source GIS software is still relatively small.

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Open source software ecosystems: A Systematic mapping
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  • Oscar Hernán Franco Bedoya

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For a firm in an open source software (OSS) ecosystem, the requirements engineering (RE) process is rather multifaceted. Apart from its typical RE process, there is a competing process, external to the firm and inherent to the firm’s ecosystem. When trying to impose an agenda in competition with other firms, and aiming to align internal product planning with the ecosystem’s RE process, firms need to consider who and how influential the other stakeholders are, and what their agendas are. The aim of the presented research is to help firms identify and analyze stakeholders in OSS ecosystems, in terms of their influence and interactions, to create awareness of their agendas, their collaborators, and how they invest their resources. To arrive at a solution artifact, we applied a design science research approach where we base artifact design on the literature and earlier work. A stakeholder influence analysis (SIA) method is proposed and demonstrated in terms of applicability and utility through a case study on the Apache Hadoop OSS ecosystem. SIA uses social network constructs to measure the stakeholders’ influence and interactions and considers the special characteristics of OSS RE to help firms structure their stakeholder analysis processes in relation to an OSS ecosystem. SIA adds a strategic aspect to the stakeholder analysis process by addressing the concepts of influence and interactions, which are important to consider while acting in collaborative and meritocratic RE cultures of OSS ecosystems.

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Technology plays a crucial role in the management of natural resources in agricultural production. Free and open-source software and sensor technology solutions have the potential to promote more sustainable agricultural production. The goal of this rapid review is to find exclusively free and open-source software for precision agriculture, available in different electronic databases, with emphasis on their characteristics and application formats, aiming at promoting sustainable agricultural production. A thorough search of the Google Scholar, GitHub, and GitLab electronic databases was performed for this purpose. Studies reporting and/or repositories containing up-to-date software were considered for this review. The various software packages were evaluated based on their characteristics and application formats. The search identified a total of 21 free and open-source software packages designed specifically for precision agriculture. Most of the identified software was shown to be extensible and customizable, while taking into account factors such as transparency, speed, and security, although some limitations were observed in terms of repository management and source control. This rapid review suggests that free and open-source software and sensor technology solutions play an important role in the management of natural resources in sustainable agricultural production, and highlights the main technological approaches towards this goal. Finally, while this review performs a preliminary assessment of existing free and open source solutions, additional research is needed to evaluate their effectiveness and usability in different scenarios, as well as their relevance in terms of environmental and economic impact on agricultural production.

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Reliability in open source software
  • Jan 1, 2014
  • PubMed
  • Najeeb Ullah

The Nem1-Spo7 complex in the yeast <i>Saccharomyces cerevisiae</i> is a protein phosphatase required for the nuclear/endoplasmic reticulum membrane localization of Pah1, a phosphatidate phosphatase that produces diacylglycerol for triacylglycerol synthesis at the expense of phospholipid synthesis. In a previous study, we showed that the protein phosphatase is subject to phosphorylation by protein kinase A (PKA). Here, we demonstrate that Nem1-Spo7 is regulated through its phosphorylation by protein kinase C (PKC), which plays multiple roles, including the regulation of lipid synthesis and cell wall integrity. Phosphorylation analyses of Nem1-Spo7 and its synthetic peptides indicate that both subunits of the complex are <i>bona fide</i> PKC substrates. Site-directed mutagenesis of <i>NEM1</i> and <i>SPO7</i>, coupled with phosphopeptide mapping and immunoblotting with a phosphoserine-specific PKC substrate antibody, revealed that Ser-201 in Nem1 and Ser-22/Ser-28 in Spo7 are major PKC target sites of phosphorylation. Activity analysis of mutant Nem1-Spo7 complexes indicates that the PKC phosphorylation of Nem1 exerts a stimulatory effect, but the phosphorylation of Spo7 has no effect. Lipid-labeling analysis of cells expressing the phosphorylation-deficient alleles of <i>NEM1</i> and <i>SPO7</i> indicates that the stimulation of the Nem1-Spo7 activity has the effect of increasing triacylglycerol synthesis. Prephosphorylation of Nem1-Spo7 by PKC inhibits the PKA phosphorylation of Nem1, whereas prephosphorylation of the phosphatase complex by PKA inhibits the PKC phosphorylation of Spo7. Collectively, this work advances the understanding of the Nem1-Spo7 regulation by phosphorylation and its impact on lipid synthesis.

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Economic savings for scientific free and open source technology: A review
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Both the free and open source software (FOSS) as well as the distributed digital manufacturing of free and open source hardware (FOSH) has shown particular promise among scientists for developing custom scientific tools. Early research found substantial economic savings for these technologies, but as the open source design paradigm has grown by orders of magnitude it is possible that the savings observed in the early work was isolated to special cases. Today there are examples of open source technology for science in the vast majority of disciplines and several resources dedicated specifically to publishing them. Do the tremendous economic savings observed earlier hold today? To answer that question, this study evaluates free and open source technologies in the two repositories compared to proprietary functionally-equivalent tools as a function of their use of Arduino-based electronics, RepRap-class 3-D printing, as well as the combination of the two. The results of the review find overwhelming evidence for a wide range of scientific tools, that open source technologies provide economic savings of 87% compared to equivalent or lesser proprietary tools. These economic savings increased slightly to 89% for those that used Arduino technology and even more to 92% for those that used RepRap-class 3-D printing. Combining both Arduino and 3-D printing the savings averaged 94% for free and open source tools over commercial equivalents. The results provide strong evidence for financial support of open source hardware and software development for the sciences. Given the overwhelming economic advantages of free and open source technologies, it appears financially responsible to divert funding of proprietary scientific tools and their development in favor of FOSH. Policies were outlined that provide nations with a template for strategically harvesting the opportunities provided by the free and open source paradigm.

  • Research Article
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Competition between Free Open Source, Commercial Open Source and Proprietary Software
  • Jan 1, 2013
  • Journal of Communications
  • Mingqing Xing

This paper investigates competition between open source and proprietary software. Open source software is divided into two types: free open source and commercial open source. Free open source software can be available from the not-for-profit community, and Commercial open source software is software product based on free open source software. The usability of both free and commercial open source software is assumed to be inferior to proprietary software. It finds that: (i) when commercial open source vendor faces competition from proprietary software and free open source software, it may still be able to obtain profits; (ii) commercial open source vendor's pricing (resp. share or profit) may still be much lower (resp. less) than that of proprietary vendor even if its software functionality is not inferior to proprietary software; (iii) commercial open source vendor's pricing and profit may not increase as its software usability increases; (iv) proprietary software's price decreases with the usability of commercial open source software. Index Terms—proprietary software, open source software, price competition, software features, software usability

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