Collaborative Development Environment Research Articles

Community-Led Development and Participatory Design in Open Source: Empowering Collaboration for Sustainable Solutions

This whitepaper delves into the active role of community-led development (CLD) and participatory design (PD) in open source software, highlighting how these complementary approaches bring stakeholders from various backgrounds together to create a cooperative atmosphere for developing stable solutions. It emphasizes the importance of these methodologies in enabling communities to tackle real-world issues effectively and robustly, thus influencing the expansion of open-source development. Integrating CLD and PD within open-source projects fosters a more inclusive collaborative development environment, driving innovation and user-centric solutions. Through case studies like Kubernetes and Konveyor, it is evident that these methodologies significantly contribute to project success by enhancing adaptability, ensuring broad community engagement, and addressing diverse user needs. The findings underscore the vital role of these strategies in creating sustainable and resilient software solutions, highlighting their potential to transform the technology development landscape.

EASRAPP: An Open-Source Semiautomatic Python GUI-Based Application for Extraction and Analysis of Surface Ruptures in a Large Earthquake

Abstract Earthquake surface ruptures record the kinematics of the rupture behavior and rheology of the fault zone. General methods of acquiring coseismic surface ruptures, including the field geological survey and the visual interpretation of remote sensing images, are generally time consuming and challenging to obtain detailed features of surface ruptures. Here, we developed an open-source semiautomatic Python graphical user interface-based application named EASRAPP (An Application for Extraction and Analysis of Surface Ruptures). EASRAPP is a graphical Python application that provides an interactive, user-friendly framework for semiautomatically extracting and analyzing earthquake surface ruptures and associated quantitative parameters. It consists of four main modules for obtaining the region of interest for surface ruptures in a remote sensing image, extracting surface ruptures, editing the vector extraction results, and analyzing the width of the surface rupture zone and strikes of all surface ruptures. Moreover, some additional functions are available, including data structure conversion for vector and raster data, vector merging, raster mosaicing, and batch cropping from multiple large images to many small images. EASRAPP is written in Python 3, based on several open-source Python packages such as Tkinter, SciPy, and so forth. Because of its modular design, it is convenient to modify the code and add new functionalities to a collaborative development environment. Furthermore, the output of the editing module may serve as a machine learning or deep learning training dataset, and offer conditions for detailed kinematic analysis and acquiring accurate width of the active fault deformation zone. EASRAPP was tested on a single unmanned aerial vehicle image to demonstrate all modules and tools. In addition, EASRAPP was also applied to other drone and satellite images to extract surface ruptures from recent and historical earthquakes. Our results indicate that: (1) the tool can quickly extract the fine structures of surface fractures, (2) EASRAPP can be used to extract surface ruptures generated by historical events, and (3) it can be applied to high-resolution aerial and satellite images.

Seispy: Python Module for Batch Calculation and Postprocessing of Receiver Functions

Abstract Seispy is a graphical interface Python module for receiver function (RF) calculation and postprocessing in seismological research. Automated workflows of RF calculations facilitate processing large volume of different types of seismic data. The graphical user interface enables an intuitive and straightforward evaluation of RF quality. All parameters about the preprocessing for RF estimation can be adjusted based on user preference. Water-level frequency-domain deconvolution and iterative time-domain deconvolution for RF estimation are available in Seispy. The current version of Seispy contains five main modules for the postprocessing of RF, such as H-κ stacking, crustal anisotropic estimation, harmonic decomposition, and 2D and 3D common conversion point (CCP) stacking. The CCP stacking in the different application scenarios can be handled by a rich collection of modules, such as time-to-depth conversion, 2D or 3D CCP stacking, and adaptive station or bin selection for CCP stacking profiles in a dense seismic array or a linear seismic array. As a Python module, functions in the Seispy can be called easily in Python scripts for other purposes. The modular design allows new functionality to be added in a collaborative development environment. Licensed under GPLv3, Seispy allow users and developers to freely use, change, share, and distribute copies of the package.

Experiential Learning in Biomedical Engineering Education Using Wearable Devices: A Case Study in a Biomedical Signals and Systems Analysis Course

Biomedical engineering (BME) is one of the fastest-growing engineering fields worldwide. BME professionals are extensively employed in the health technology and healthcare industries. Hence, their education must prepare them to face the challenge of a rapidly evolving technological environment. Biomedical signals and systems analysis is essential to BME undergraduate education. Unfortunately, students often underestimate the importance of their courses as they do not perceive these courses’ practical applications in their future professional practice. In this study, we propose using blended learning spaces to develop new learning experiences in the context of a biomedical signals and systems analysis course to enhance students’ motivation and interest and the relevance of the materials learned. We created a learning experience based on wearable devices and cloud-based collaborative development environments such that the students turned daily-life scenarios into experiential learning spaces. Overall, our results suggest a positive impact on the students’ perceptions of their learning experience concerning relevance, motivation, and interest. Namely, the evidence shows a reduction in the variability of such perceptions. However, further research must confirm this potential impact. This confirmation is required given the monetary and time investment this pedagogical approach would require if it were to be implemented at a larger scale.

Towards an Interdisciplinary Development of IoT-Enhanced Business Processes

IoT-enhanced Business Processes make use of sensors and actuators to carry out the process tasks and achieve a specific goal. One of the most important difficulties in the development of IoT-enhanced BPs is the interdisciplinarity that is demanded by this type of project. Defining an interdisciplinary tool-supported development approach that facilitates the collaboration of different professionals, with a special focus on three main facets: business process requirements, interoperability between IoT devices and BPs, and low-level data processing. The study followed a Design Science Research methodology for information systems that consists of a 6-step process: (1) problem identification and motivation; (2) define the objectives for a solution; (3) design and development; (4) demonstration; (5) evaluation; and (6) communication. The paper presents an interdisciplinary development process to support the creation of IoT-enhanced BPs by applying the Separation of Concerns principle. A collaborative development environment is built to provide each professional with the tools required to accomplish her/his development responsibilities. The approach is successfully validated through a case-study evaluation. The evaluation allows to conclude that the proposed development process and the supporting development environment are effective to face the interdisciplinary nature of IoT-enhanced BPs.

Integrated Seismic Program (ISP): A New Python GUI-Based Software for Earthquake Seismology and Seismic Signal Processing

Abstract Integrated Seismic Program (ISP) is a graphical user interface designed to facilitate and provide a user-friendly framework for performing diverse common and advanced tasks in seismological research. ISP is composed of five main modules for earthquake location, time–frequency analysis and advanced signal processing, implementation of array techniques to estimate the slowness vector, seismic moment tensor inversion, and receiver function computation and analysis. In addition, several support tools are available, allowing the user to create an event database, download data from International Federation of Digital Seismograph Networks services, inspect the background noise, and compute synthetic seismograms. ISP is written in Python3, supported by several open-source and/or publicly available tools. Its modular design allows for new features to be added in a collaborative development environment.

A comprehensive framework and tool for supporting progressive learning of software development in an academic learning environment

AbstractThe use of technology‐enabled environments to facilitate online education has increasingly gained importance to promote learning. Tools like learning management systems, virtual laboratory platforms, online monitoring, and mentoring tools, all form a concrete technology bed for augmenting online education. However, successful use of these segregated tools is possible only through the implementation of a structured process or framework of usage of these tools for learning. In this paper, we propose a comprehensive framework for supporting progressive learning of software development by students. This framework provides guidelines for structuring individual and collaborative programming activities of students at various levels and is realized through the implementation of a tool named eGuru. This tool is used for managing, monitoring, mentoring, and facilitating collaborative programming activities of students and also provides a detailed user interface for facilitating the academic activities of teachers and lab instructors. Peers, alumni, and industry experts also play important roles in providing online mentoring using this tool. The execution structure proposed in the framework is effective not only for promoting online programming education but also creates a virtual environment analogous to the collaborative development environment existing in the software industry, and thus helps in preparing students for the future.

Intelligent Collaboration Technology of Software Developers Based on Data Driven

Software development highly depends on the group contribution of developers, so improving the cooperation efficiency of developers is an important issue to improve the efficiency and quality of software development. In recent years, it has become a hot topic in the field of software engineering to improve the intelligent level of software development by mining and using the knowledge contained in software big data. However, the research on software developers and their group collaboration methods has not yet formed systematic research results. Therefore, this paper takes the developer group as the research object, through in-depth analysis of the behavior history data of developers, studies the key technologies of intelligent cooperation, and develops the corresponding support environment based on this. This paper first analyzes and summarizes the related research work. Then, the capability feature model and collaboration relationship model of software developers are given, and the knowledge map of developers is constructed. Furthermore, based on the knowledge map of developers, the collaborative development method based on intelligent recommendation is introduced by taking two developer recommendation methods as examples. Based on the above key technologies, the corresponding supporting tools are developed, and the prototype system of intelligent collaborative development environment is constructed.

Knowledge-Sharing Strategies in Distributed Collaborative Product Development

Knowledge-sharing strategies are used across the industry as open innovation and distributed collaboration are becoming more popular to achieve technological competencies, faster time-to-market, competitiveness and growth. Sharing of knowledge can provide benefits to manufacturing and new product development (NPD) companies in improving their product quality and enhancing business potential. This paper examines the implementation of knowledge-sharing strategies in New Zealand aimed at bridging the physical locational issues to achieve collaborative benefits in NPD firms through an in-depth case study. The analysis of this only one, but interesting, case extends a holistic multi-mediation model by Pateli and Lioukas for the effect of functional involvement in a distributed collaborative product development environment. This study explores the external and internal knowledge transfer and how it affects early-stage, late-stage, and the overall product development process. Findings present a knowledge-sharing toolset that enhances innovation in all stages of product development overcoming the environmental factors to improve early and late-stage development through a two-way knowledge-transfer loop with distributed stakeholders. An encouraging management culture is found as key for transparent knowledge transfer across cross-functional teams. The organizational structure and management style play an important role for both external and internal distribution of knowledge.

A unified call to action from Australian nursing and midwifery leaders: ensuring that Black lives matter

Nurses and midwives of Australia now is the time for change! As powerfully placed, Indigenous and non-Indigenous nursing and midwifery professionals, together we can ensure an effective and robust Indigenous curriculum in our nursing and midwifery schools of education. Today, Australia finds itself in a shifting tide of social change, where the voices for better and safer health care ring out loud. Voices for justice, equity and equality reverberate across our cities, our streets, homes, and institutions of learning. It is a call for new songlines of reform. The need to embed meaningful Indigenous health curricula is stronger now than it ever was for Australian nursing and midwifery. It is essential that nursing and midwifery leadership continue to build an authentic collaborative environment for Indigenous curriculum development. Bipartisan alliance is imperative for all academic staff to be confident in their teaching and learning experiences with Indigenous health syllabus. This paper is a call out. Now is the time for Indigenous and non-Indigenous nurses and midwives to make a stand together, for justice and equity in our teaching, learning, and practice. Together we will dismantle systems, policy, and practices in health that oppress. The Black Lives Matter movement provides us with a ‘now window’ of accepted dialogue to build a better, culturally safe Australian nursing and midwifery workforce, ensuring that Black Lives Matter in all aspects of health care.

Prioritization Based Taxonomy of DevOps Challenges Using Fuzzy AHP Analysis

The DevOps (development and operations) is a collaborative software development environment which offers the continues development and deployment of quality software project within short time. The DevOps practices are not yet mature enough, and the software organizations hesitate to adopt it. This study aims: 1) to explore the DevOps challenges by conducting systematic literature review (SLR) and to get the insight of industry experts via questionnaire survey study and 2) to prioritize the investigated challenges using fuzzy analytical hierarchy process (FAHP). The study findings provide the set of critical challenges faced by the software organizations while adopting DevOps and a prioritization-based taxonomy of the DevOps challenges. The application of FAHP is novel in this research area as it assists in addressing the vagueness of practitioners concerning the influencing factors of DevOps. We believe that the finding of this study will serve as a body of knowledge for real world practitioners and researchers to revise and develop the new strategies for the successful implementation of DevOps practices in the software industry.

What We are Missing in Studies of Teacher Learning: A Call for Microgenetic, Interactional Analyses to Examine Teacher Learning Processes

Much of the work in the Learning Sciences and Computer-Supported Collaborated Learning communities have focused on understanding and designing for learning in collaborative spaces. This work utilizes methods such as Interaction Analysis and has attended to multiple dimensions and timescales of learning. It has redefined ideas about knowledge and competence and how they are acquired, thus providing important insights into the process of learning and the design of learning environments. However, we have not in the same way advanced our knowledge of teacher learning. Our understanding of the process and mechanism of teacher learning in in collaborative professional development (PD) environments is still quite thin. In this paper, we discuss how utilizing methods from Interaction Analysis, in particular, can offer insight into the process of teacher learning in these contexts. We illustrate how adopting a lens that shifts away from asking whether teachers are progressing toward a researcher-defined goal, toward one that asks how learning occurs in the moments of interaction, and the meaning it has for participants as they work to achieve PD goals, has the potential to shed new light on learning in teacher PD.

CREATION OF COLLABORATIVE DEVELOPMENT ENVIRONMENT IN THE SYSTEM OF DISTANCE LEARNING

The subject of the study in the article is methods and tools for the creation and implementation of distance learning systems (DLS). The interactive capabilities used in the distance education system, programs and information delivery systems allow for feedback, dialogue and ongoing support that are not possible in most traditional learning systems. The purpose of the article is to create a collaborative environment for developing software products in the system of distance learning by forming an interactive platform with the help of Sphere Engine, which provides the ability to debug the code in many programming languages. At the same time, the following tasks are solved: a review and comparison of existing systems of distance learning; analysis of the functional and features of the Sphere Engine platform; development of the integration algorithm of the service with the system Moodle. Methods: methods of information processing, methods and information technologies for the creation of electronic distance learning courses. Results. As a result of the review and comparison of existing distance learning systems and software verification tools, the tools that best meet the needs for collaborative development environments, namely the Moodle DLS and the Sphere Engine service, are selected. The analysis of the functional and features of the Sphere Engine platform is carried out: a diagram of the work of the api compilers of the service is shown, which illustrates the process of execution of the program from the moment of its sending to the results of execution; The concept of a pool script in graphical form is provided. A prototype collaborative development environment created in the form of a web application is created, the prototype architecture is described. An algorithm for integration of the Sphere Engine service with the Moodle system is developed. In detail, the stages of the integration algorithm are considered on the example of testing the work environment of the development of the course Web-technologies and web-design. Conclusions. An interactive module is created with the help of Sphere Engine, which allows you to perform laboratory work on programming disciplines and to carry out full control over their execution. Thus, the degree of automation of the educational process in institutions of higher education increases.

Exploring the teaching of culture in the foreign language classroom within the context of collaborative professional development: a critical participatory action research study

ABSTRACT This article describes the experience of French language teachers as they explored interculturality within a collaborative professional development environment. Participants studied how to design culture lessons for their classrooms through the lens of Intercultural Communicative Competence with the support of theoretical frameworks for intercultural learning. The findings underscore a need for teacher professional development that creates space for teachers to explore topics of interest in an in-depth and collaborative manner, that makes time for exploration of theoretical frameworks, and that models practical strategies for embedding interculturality in curricula. Furthermore, this study reveals that explicit examples of intercultural lessons taught while using the target language are needed in order for language teachers to gain confidence in this area.

Legacy, Rather Than Adequacy, Drives the Selection of Hydrological Models

AbstractThe findings of hydrological modeling studies depend on which model was used. Although hydrological model selection is a crucial step, experience suggests that hydrologists tend to stick to the model they have experience with, and rarely switch to competing models, although these models might be more adequate given the study objectives. To gain quantitative insights into model selection, we explored the use of seven rainfall‐runoff models based on the abstract of 1,529 peer‐reviewed papers published between 1991 and 2018. The models selected were the Hydrologiska Byråns Vattenbalansavdelning model (HBV), the Variable Infiltration Capacity model (VIC), the mesoscale Hydrological model (mHM), the TOPography‐based hydrologic model (TOPMODEL), the Precipitation Runoff Modelling System (PRMS), the Génie Rural model à 4 paramètres Journaliers (GR4J), and the Sacramento soil moisture accounting model. We provide quantitative evidence of regional preferences in model use across the world and demonstrate that specific models are consistently preferred by certain institutes. Model attachment is particularly strong. In ~74% of the studies, the model selected can be predicted solely based on the affiliation of the first author. The influence of adequacy on the model selection process is less clear. Our data reveal that each model is used across a wide range of purposes, landscapes, and temporal and spatial scales (i.e., as a model of everything and everywhere). Model intercomparisons can provide guidance for model selection and improve model adequacy, but they are still rare (because each model must usually be setup individually) and the insights they provide are currently limited (because they are rarely controlled experiments). We suggest that moving from fixed‐structure models to modular modeling frameworks (master templates for model generation) can overcome these issues, enable a more collaborative and responsive model development environment, and result in improved model adequacy.

Continuous Delivery: Building Trust in a Large-Scale, Complex Government Organization

For many software development teams, the first aspects that come to mind regarding continuous delivery (CD) are the operational challenges and competitive benefits. In the authors’ experience, CD was much more: it was a survival technique. This article presents how and why they applied CD in a large governmental project for the development of a collaborative development environment. They share the challenges they faced and the strategies they used to overcome them. The article concludes with a set of lessons learned that can be valuable for readers in a variety of situations. This article is part of a special issue on release engineering.

Data sets describing the circle of life in Ruby hosting, 2003–2016

Studying software repositories and hosting services can provide valuable insights into the behaviors of large groups of software developers and their projects. Traditionally, most analysis of metadata collected from software project hosting services has been conducted by specifying some short window of time, typically just a few years. To date, few - if any - studies have been built from data comprising the entirety of a hosting facility’s lifespan: from its birth to its death, and rebirth in another form. Thus, the first contribution of this paper is to present two data sets that support the historical analysis of over ten years of collected metadata from the now-defunct RubyForge project hosting site, as well as the follow-on successor to RubyForge, the RubyGems package (“gem”) hosting facility. The data sets and samples of usage demonstrated in this paper include: analyses of overall forge growth over time, presentation of data and analyses of project-level characteristics on both forges and their changes over time (for example in licenses, languages, and so on), and demonstration of how to use developer-level metadata (for example counts of new developers and calculation of developer-project density) to assess changes in person-level activity on both sites over time. Finally, because RubyForge was phased out and the gem-hosting portion of it was replaced by RubyGems, all the gems within RubyForge projects were transferred by project owners and by the site owners themselves into the RubyGems hosting facility. Thus, the data sets in this paper represent a unique opportunity to study projects as they moved from one ecosystem to another, and as such we show several methods for locating related projects between the two forges, and for building a cross-forge, longitudinal project history using information from both forges. These data sets and sample analyses in this paper will be relevant to researchers studying long-term software evolution, and distributed, hosted, or collaborative software development environments.

The appropriation of GitHub for curation

GitHub is a widely used online collaborative software development environment. In this paper, we describe curation projects as a new category of GitHub project that collects, evaluates, and preserves resources for software developers. We investigate: (1) what motivates software developers to curate resources; (2) why curation has occurred on GitHub; (3) how curated resources are used by software developers; and (4) how the GitHub platform could better support these practices. We conduct in-depth interviews with 16 software developers, each of whom hosts curation projects on GitHub. Our results suggest that the motivators that inspire software developers to curate resources on GitHub are similar to those that motivate them to participate in the development of open source projects. Convenient tools (e.g., Markdown syntax and Git version control system) and the opportunity to address professional needs of a large number of peers attract developers to engage in curation projects on GitHub. Benefits of curating on GitHub include learning opportunities, support for development work, and professional interaction. However, curation is limited by GitHub’s document structure, format, and a lack of key features, such as search. In light of this, we propose design possibilities to encourage and improve appropriations of GitHub for curation.

Building Your Own Big Data Analysis Infrastructure for Biodiversity Science

The size of biodiversity data sets, and the size of people’s questions around them, are outgrowing the capabilities of desktop applications, single computers, and single developers. Numerous articles in the corporate sector (Delgado 2016) have been written on how much time professionals spend manipulating and formatting large data sets compared to the time they spend on the important work of doing analysis and modeling. To efficiently move large research questions forward, the biodiversity domain needs to transition towards shared infrastructure with the goal of providing a mise en place for researchers to do research with large data. The GUODA (Global Unified Open Data Access) collaboration was formed to explore tools and use cases for this type of collaborative work on entire biodiversity data sets. Three key parts of that exploration have been: the software and hardware infrastructure needed to be able to work with hundreds of millions of records and terabytes of data quickly, removing the impediment of data formatting and preparation, and workflows centered around GitHub for interacting with peers in an open and collaborative manner. We will describe our experiences building an infrastructure based on Apache Mesos, Apache Spark, HDFS, Jupyter Notebooks, Jenkins, and Github. We will also enumerate what resources are needed to do things like join millions of records, visualize patterns in whole data sets like iDigBio and the Biodiversity Heritage Library, build graph structures of billions of nodes, analyze terabytes of images, and use natural language processing to explore gigabytes of text. In addition to the hardware and software, we will describe the kinds of skills needed by staff to design, build, and use this sort of infrastructure and highlight some experiences we have with training students. Our infrastructure is one of many that are possible. We hope that by showing the amount and type of work we have done to the wider community, other organizations can understand what they would need to speed up their research programs by developing their own collaborative computation and development environments.

How does developer interaction relate to software quality? an examination of product development data

Industrial software systems are being increasingly developed by large and distributed teams. Tools like collaborative development environments (CDE) are used to facilitate interaction between members of such teams, with the expectation that social factors around the interaction would facilitate team functioning. In this paper, we first identify typically social characteristics of interaction in a software development team: reachability, connection, association, and clustering. We then examine how these factors relate to the quality of software produced by a team, in terms of the number of defects, through an empirical study of 70+ teams, involving 900+ developers in total, spread across 30+ locations and 19 time-zones, working on 40,000+ units of work in the multi-version development of a major industrial product, spreading across more than five years. After controlling for known factors affecting large scale distributed development such as dependency, system age, developer expertise and experience, geographic dispersion, socio-technical congruence, and the number of files changed, we find statistically significant effects of connection and clustering on software quality. Higher levels of intra-team connection are found to relate to higher defect count, whereas more clustering relates to fewer defects. We examine the implications of these results for individual developers, project managers, and organizations.