Healthy or Not: A Way to Predict Ecosystem Health in GitHub

With the development of open source community, through the interaction of developers, the collaborative development of software, and the sharing of software tools, the formation of open source software ecosystem has matured. Natural ecosystems provide ecological services on which human beings depend. Maintaining a healthy natural ecosystem is a necessity for the sustainable development of mankind. Similarly, maintaining a healthy ecosystem of open source software is also a prerequisite for the sustainable development of open source communities, such as GitHub. This paper takes GitHub as an example to analyze the health condition of open source ecosystem and, also, it is a research area in Symmetry. Firstly, the paper presents the healthy definition of GitHub open source ecosystem health and, then, according to the main components of natural ecosystem health, the paper proposes the health indicators and health indicators evaluation method. Based on the above, the GitHub ecosystem health prediction method is proposed. By analyzing the projects and data collected in GitHub, it is found that, using the proposed evaluation indicators and method, we can analyze the healthy development trend of the GitHub ecosystem and contribute to the stability of ecosystem development

QuESo: A quality model for open source software ecosystems

© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Open source software has witnessed an exponential growth in the last two decades and it is playing an increasingly important role in many companies and organizations leading to the formation of open source software ecosystems. In this paper we present a quality model that will allow the evaluation of those ecosystems in terms of their relevant quality characteristics such as health or activeness. To design this quality model we started by analysing the quality measures found during the execution of a systematic literature review on open source software ecosystems and, then, we classified and reorganized the set of measures in order to build a solid quality model.Peer ReviewedPostprint (author's final draft

Empirical research on the evaluation model and method of sustainability of the open source ecosystem

The development of open source brings new thinking and production modes to software engineering and computer science, and establishes a software development method and ecological environment in which groups participate. Regardless of investors, developers, participants, and managers, they are most concerned about whether the Open Source Ecosystem can be sustainable to ensure that the ecosystem they choose will serve users for a long time. Moreover, the most important quality of the software ecosystem is sustainability, and it is also a research area in Symmetry. Therefore, it is significant to assess the sustainability of the Open Source Ecosystem. However, the current measurement of the sustainability of the Open Source Ecosystem lacks universal measurement indicators, as well as a method and a model. Therefore, this paper constructs an Evaluation Indicators System, which consists of three levels: The target level, the guideline level and the evaluation level, and takes openness, stability, activity, and extensibility as measurement indicators. On this basis, a weight calculation method, based on information contribution values and a Sustainability Assessment Model, is proposed. The models and methods are used to analyze the factors affecting the sustainability of Stack Overflow (SO) ecosystem. Through the analysis, we find that every indicator in the SO ecosystem is partaking in different development trends. The development trend of a single indicator does not represent the sustainable development trend of the whole ecosystem. It is necessary to consider all of the indicators to judge that ecosystem’s sustainability. The research on the sustainability of the Open Source Ecosystem is helpful for judging software health, measuring development efficiency and adjusting organizational structure. It also provides a reference for researchers who study the sustainability of software engineering

Identification-method research for open-source software ecosystems

In recent years, open-source software (OSS) development has grown, with many developers around the world working on different OSS projects. A variety of open-source software ecosystems have emerged, for instance, GitHub, StackOverflow, and SourceForge. One of the most typical social-programming and code-hosting sites, GitHub, has amassed numerous open-source-software projects and developers in the same virtual collaboration platform. Since GitHub itself is a large open-source community, it hosts a collection of software projects that are developed together and coevolve. The great challenge here is how to identify the relationship between these projects, i.e., project relevance. Software-ecosystem identification is the basis of other studies in the ecosystem. Therefore, how to extract useful information in GitHub and identify software ecosystems is particularly important, and it is also a research area in symmetry. In this paper, a Topic-based Project Knowledge Metrics Framework (TPKMF) is proposed. By collecting the multisource dataset of an open-source ecosystem, project-relevance analysis of the open-source software is carried out on the basis of software-ecosystem identification. Then, we used our Spectral Clustering algorithm based on Core Project (CP-SC) to identify software-ecosystem projects and further identify software ecosystems. We verified that most software ecosystems usually contain a core software project, and most other projects are associated with it. Furthermore, we analyzed the characteristics of the ecosystem, and we also found that interactive information has greater impact on project relevance. Finally, we summarize the Topic-based Project Knowledge Metrics Framework

Suitability of pesticide risk indicators for less developed countries: a comparison

Pesticide risk indicators provide simple support in the assessment of environmental and health risks from pesticide use, and can therefore inform policies to foster a sustainable interaction of agriculture with the environment. For their relative simplicity, indicators may be particularly useful under conditions of limited data availability and resources, such as in Less Developed Countries (LDCs). However, indicator complexity can vary significantly, in particular between those that rely on an exposure–toxicity ratio (ETR) and those that do not. In addition, pesticide risk indicators are usually developed for Western contexts, which might cause incorrect estimation in LDCs. This study investigated the appropriateness of seven pesticide risk indicators for use in LDCs, with reference to smallholding agriculture in Colombia. Seven farm-level indicators, among which 3 relied on an ETR (POCER, EPRIP, PIRI) and 4 on a non-ETR approach (EIQ, PestScreen, OHRI, Dosemeci et al., 2002), were calculated and then compared by means of the Spearman rank correlation test. Indicators were also compared with respect to key indicator characteristics, i.e. user friendliness and ability to represent the system under study. The comparison of the indicators in terms of the total environmental risk suggests that the indicators not relying on an ETR approach cannot be used as a reliable proxy for more complex, i.e. ETR, indicators. ETR indicators, when user-friendly, show a comparative advantage over non-ETR in best combining the need for a relatively simple tool to be used in contexts of limited data availability and resources, and for a reliable estimation of environmental risk. Non-ETR indicators remain useful and accessible tools to discriminate between different pesticides prior to application. Concerning the human health risk, simple algorithms seem more appropriate for assessing human health risk in LDCs. However, further research on health risk indicators and their validation under LDC conditions is needed

Sustainability Children\u27s Book

As human driven climate change continues to alter our planet, persuading the general public to adopt sustainable living practices has become increasingly important. Storytelling has long been a part of human culture, and recent studies have emphasized the power of storytelling to influence the audience as a means of changing behavior. This project attempted to teach sustainable principles to primary school children through the creation of a scientific children’s book. The book communicated the maxim of “reduce, reuse, recycle” by tracing a fictitious story of a town where children frequently buy new toys and throw the old toys away. The book explores the supply chain of toys and the market forces of supply and demand, focusing on the consumer’s responsibility to not over-consume, i.e “reduce”. It also presents the concept of “reusing” and “recycling” as alternatives to disposal of old toys. The book was evaluated for age appropriate language and concepts for K-5 students and adjusted to meet educational standards. It was then tested by reading it to a classroom of 2nd grade students. A discussion with the students following the reading showed that they understood the theme of the book and how they could apply it to their own lives. The project also included a life cycle analysis (LCA) of a stuffed animal, a representative toy from the story. The LCA showed that the largest contributors to the stuffed animal’s impacts were the production of cotton used for its outer layer and the electricity used in its assembly. It also showed the impacts most damaging to human health were chiefly a result of the fossil fuels used to provide process energy

Multimedia Assessment of Pollutant Pathways in the Environment, European Scale Model (MAPPE-EUROPE)

The report documents the structure, functions and algorithms used for the modeling of pollutant pathways in air, soil sediments and surface and sea water at the European continental scale. The algorithms are implemented in an extension for ESRI ArcGIS 9.2 a popular geographic information system (GIS) software widely used within the European Commission and in the research, environmental assessment, planning communities. The software is called MAPPE after Multimedia Assessment of Pollutant Pathways in Environment of Europe; the acronym is also the Italian word to denote maps. The purpose of the software is to provide a user-friendly way to convey the wealth of geographic data available to model the fluxes and concentrations of chemical pollutants emitted by industrial activities and other point emissions, and widespread use within households, urban environments or agriculture. The intended use is for organic contaminants such as pesticides, pharmaceuticals, VOCs, and other industrial chemicals. The output of the model, i.e. maps of concentration and chemical fluxes, can be used for the screening of hot spots at continental scale, the assessment of risk for human health and ecosystems, the evaluation of policies and scenarios with reference to the ¿big picture¿ of the continental scale. However this does not avoid the need to use more detailed, site specific assessment procedures for single problems, but provides a tool for decision support in contexts such as the management of priority substances of concern for soil, water and air quality, the control of effects of environmental pollution on human health and ecosystems, and the sustainable management of agro-chemicals, etc. by making available a geographic representation available of the consequences of emissions to air, soil and water compartments.JRC.DDG.H.5-Rural, water and ecosystem resource