Identifying Developer Engagement in Open-Source Software Blockchain Projects through Factor Analysis

The ubiquity of GitHub for software developers to coordinate software development in a community platform has resulted in a rich source of public data. Blockchain teams put open-source code as a founding principle since the release of Bitcoin and nearly all blockchain-based projects have code visible on GitHub. Developer engagement is known to be important to the health and viability of open-source software, yet has varying definitions and no standard method of measuring what constitutes engagement. This work uses exploratory factor analysis to identify dimensions that represent engagement in a community of open-source developers. We find that a latent factor composed of pull-requests, commits, comments, and authors based on a monthly average of the previous three months is a representation of Developer Engagement. A secondary factor consists of stars, forks, and total authors. Cross validation of the dataset is carried out with good support for the model

Towards a Structural Equation Model of Open Source Blockchain Software Health

The widespread use of GitHub among software developers as a communal platform for coordinating software development has led to an abundant supply of publicly accessible data. Ever since the inception of Bitcoin, blockchain teams have incorporated the concept of open source code as a fundamental principle, thus making the majority of blockchain-based projects' code and version control data available for analysis. We define health in open source software projects to be a combination of the concepts of sustainability, robustness, and niche occupation. Sustainability is further divided into interest and engagement. This work uses exploratory factor analysis to identify latent constructs that are representative of general public interest or popularity in software, and software robustness within open source blockchain projects. We find that interest is a combination of stars, forks, and text mentions in the GitHub repository, while a second factor for robustness is composed of a criticality score, time since last updated, numerical rank, and geographic distribution. Cross validation of the dataset is carried out with good support for the model. A structural model of software health is proposed such that general interest positively influences developer engagement, which, in turn, positively predicts software robustness. The implications of structural equation modelling in the context of software engineering and next steps are discussed.Comment: 26 pages, 6 figure

The 13th Southern Hemisphere Conference on the Teaching and Learning of Undergraduate Mathematics and Statistics

Ngā mihi aroha ki ngā tangata katoa and warm greetings to you all. Welcome to Herenga Delta 2021, the Thirteenth Southern Hemisphere Conference on the Teaching and Learning of Undergraduate Mathematics and Statistics. It has been ten years since the Volcanic Delta Conference in Rotorua, and we are excited to have the Delta community return to Aotearoa New Zealand, if not in person, then by virtual means. Although the limits imposed by the pandemic mean that most of this year’s 2021 participants are unable to set foot in Tāmaki Makaurau Auckland, this has certainly not stopped interest in this event. Participants have been invited to draw on the concept of herenga, in Te Reo Māori usually a mooring place where people from afar come to share their knowledge and experiences. Although many of the participants are still some distance away, the submissions that have been sent in will continue to stimulate discussion on mathematics and statistics undergraduate education in the Delta tradition. The conference invited papers, abstracts and posters, working within the initial themes of Values and Variables. The range of submissions is diverse, and will provide participants with many opportunities to engage, discuss, and network with colleagues across the Delta community. The publications for this thirteenth Delta Conference include publications in the International Journal of Mathematical Education in Science and Technology, iJMEST, (available at https://www.tandfonline.com/journals/tmes20/collections/Herenga-Delta-2021), the Conference Proceedings, and the Programme (which has created some interesting challenges around time-zones), by the Local Organizing Committee. Papers in the iJMEST issue and the Proceedings were peer reviewed by at least two reviewers per paper. Of the ten submissions to the Proceedings, three were accepted. We are pleased to now be at the business end of the conference and hope that this event will carry on the special atmosphere of the many Deltas which have preceded this one. We hope that you will enjoy this conference, the virtual and social experiences that accompany it, and take the opportunity to contribute to further enhancing mathematics and statistics undergraduate education. Ngā manaakitanga, Phil Kane (The University of Auckland | Waipapa Taumata Rau) on behalf of the Local Organising Committ

Numerical Modelling of Staged Combustion Aft-injected Hybrid Rocket Motors

The staged combustion aft-injected hybrid (SCAIH) rocket motor is a promising design for the future of hybrid rocket propulsion. Advances in computational fluid dynamics and scientific computing have made computational modelling an effective tool in design and development. The focus of this thesis is the numerical modelling of the SCAIH rocket motor in a turbulent combustion, high-speed, reactive flow accounting for solid soot transport and radiative heat transfer. The SCAIH motor has a shear coaxial injector with liquid oxygen injected centrally at sub-critical conditions: 150K, 150m/s (Mach≈0.9), and a gas-generator gas-solid mixture of one-third carbon soot by mass injected in the annual opening at 1175K, and 460m/s (Mach≈0.6). Flow conditions in the near injector region and the flame anchoring mechanism are of particular interest. Overall, the flow is shown to exhibit instabilities and the flame is shown to anchor directly on the injector faceplate with temperatures in excess of 2700K.MAS

A Taxonomy of Blockchain Consensus Methods

For a blockchain, consensus is the foundation protocol that enables cryptocurrencies such as Bitcoin to maintain state. Additionally, to ensure safety and liveness for a publicly accessible and verifiable ledger, fault tolerance must be robust. However, there appears to be a degree of misunderstanding about how consensus is applied across blockchains. To assist researchers considering variations between them, this study presents a rational classification of consensus methods applied to current blockchains. The study provides a survey of 19 methods classified by the scarce resource they employ: clock-cycles, bits, tokens, votes, time, and biometrics. Blockchain implementations are split between consensus algorithms requiring proof of resource and those that use majority voting to update the ledger