Open Source Software Development Research Articles

Mutation Testing in Practice: Insights From Open-Source Software Developers

Mutation Testing in Practice: Insights From Open-Source Software Developers

Characterizing Developers' Linguistic Behaviors in Open Source Development across Their Social Statuses

Open Source Software (OSS) development has attracted numerous developers. As a typical complex sociotechnical system, an OSS project often forms a hierarchical social structure where a few developers are elite while the rest are non-elite. Differences in social status may result in distinct language use behaviors in interpersonal communication. Characterizing such behaviors is critical for supporting efficient and effective communication among developers with different social statuses. This study empirically compared elite and non-elite developers' language behaviors in their communication. We compiled a corpus of - 216,000 discourses collected from 20 large projects on GitHub. We investigated the linguistic differences in three aspects, namely, linguistic styles and characters, main concerns, and sentence patterns. Our findings reveal that elite and non-elite developers showed different linguistic patterns and had different concerns in their discourses. Their discourses also reflect the variation of the main focuses in the development process. Furthermore, elite and non-elite developers exhibited noticeable patterns in their linguistic behaviors in accordance with their roles and corresponding divisions of labor in the production process, no matter which semantic contexts. These findings provide implications for supporting communication that crosses social statuses in OSS development.

Gradients of Brain Organization: Smooth Sailing from Methods Development to User Community.

Multimodal neuroimaging grants a powerful in vivo window into the structure and function of the human brain. Recent methodological and conceptual advances have enabled investigations of the interplay between large-scale spatial trends - or gradients - in brain structure and function, offering a framework to unify principles of brain organization across multiple scales. Strong community enthusiasm for these techniques has been instrumental in their widespread adoption and implementation to answer key questions in neuroscience. Following a brief review of current literature on this framework, this perspective paper will highlight how pragmatic steps aiming to make gradient methods more accessible to the community propelled these techniques to the forefront of neuroscientific inquiry. More specifically, we will emphasize how interest for gradient methods was catalyzed by data sharing, open-source software development, as well as the organization of dedicated workshops led by a diverse team of early career researchers. To this end, we argue that the growing excitement for brain gradients is the result of coordinated and consistent efforts to build an inclusive community and can serve as a case in point for future innovations and conceptual advances in neuroinformatics. We close this perspective paper by discussing challenges for the continuous refinement of neuroscientific theory, methodological innovation, and real-world translation to maintain our collective progress towards integrated models of brain organization.

State‐of‐the‐practice in quality assurance in Java‐based open source software development

SummaryTo ensure the quality of software systems, software engineers can make use of a variety of quality assurance approaches, for example, software testing, modern code review, automated static analysis, and build automation. Each of these quality assurance practices have been studied in depth in isolation, but there is a clear knowledge gap when it comes to our understanding of how these approaches are being used in conjunction, or not. In our study, we broadly investigate whether and how these quality assurance approaches are being used in conjunction in the development of 1454 popular open source software projects on GitHub. Our study indicates that typically projects do not follow all quality assurance practices together with high intensity. In fact, we only observe weak correlation among some quality assurance practices. In general, our study provides a deeper understanding of how existing quality assurance approaches are currently being used in Java‐based open source software development. Besides, we specifically zoom in on the more mature projects in our dataset, and generally we observe that more mature projects are more intense in their application of the quality assurance practices, with more focus on their ASAT usage, and code reviewing, but no strong change in their CI usage.

The Entrainment of Task Allocation and Release Cycles in Open Source Software Development

In this study we identify a process of “entrainment” around open source software (OSS) development release cycles to capture patterns of self-organized task allocation among developers. We conducted an abductive, computationally intensive study of eight OSS projects, using relational event modeling to analyze 1,169,489 actions covering 93 major software releases. The process of entrainment that we identify involves three task allocation mechanisms: (1) developer-issue inertia, (2) developer contribution frequency, and (3) issue popularity. Our analysis demonstrates that these mechanisms and the phases of the release cycle entrain each other. Before a major release, developers engage in a concentrated mobilization phase, whereby they democratize development activity and increasingly allocate community contributions to the set of issues related to the release. After a major release, the extended cleanup phase garners a greater share of development work from recently highly active developers and dilutes the activity of these developers across a wider range of issues. Our theorizing suggests that major releases constitute important events around which OSS communities self-organize and we characterize how this occurs. Our research contributes to theorizing on organizing in OSS communities by explaining how self-organizing task allocation interacts with release cycles through the mechanism of entrainment. We also contribute to the literature on entrainment by showing how it may unfold in the context of online peer production communities such as OSS.

The Need to Develop Open Source Software Ecosystem: Library Professional’s Perspective

To stay ahead in the competition and to hold users to themselves, proprietary software and hardware vendors develop their closed ecosystems. Seamless interconnection of devices and easy inter-operability are thus implemented for a closed circle of users and provide a niggle free experience in using applications across devices and offer seamless data transfer across devices and applications. Microsoft, Apple, and Google are integrating this strategy on all their devices and products. It is the need of the hour, for open-source software proponents and developers to rise to the occasion to combat the monopolistic tendencies that hinder openness. Library professionals who have either adopted Open-Source Software (OSS) or information professionals who are on the verge of moving in the direction of OSS need to consider investing time, effort, and resources in developing and sustaining a counter movement with an alternate OSS ecosystem.

TeReKG: A temporal collaborative knowledge graph framework for software team recommendation

Successful software development requires a cohesive team with the right mix of technical skills and the ability to collaborate effectively. However, forming a software team that can execute tasks with precision and efficiency requires a deep understanding of each member’s competence, experience, and cooperation history. Previously, automated software team selection has evaluated technical skills, cohesion, and cooperation history. However, the previous method had some limitations. Particularly, local features directly calculated from team members were subjective to the researchers’ views, and the method ignored the temporal aspect of open-source software development. To overcome these limitations, this paper proposes a knowledge-graph software team recommendation framework called TeReKG. This framework encapsulates temporal collaboration patterns and uses a temporal knowledge graph to encode software collaboration history, technical abilities, task dependencies, and project structure. TeReKG was against state-of-the-art team recommendation algorithms using three popular open-source software projects: Moodle, Apache, and Atlassian. The evaluation results show that TeReKG outperforms the state-of-the-art baselines in both single-role and team recommendation tasks. These findings demonstrate that knowledge graph embedding can be effectively utilized in automated recommendation tasks in software engineering. Additionally, this highlights the potential for knowledge graphs to capture global information that can benefit various software development applications, including impact prediction of software repositories, code clone detection, and source code retrieval.

Blockchain Based Fund Raiser & Splitter for Open-source Project

Abstract: The advent of open-source software development has significantly transformed the tech industry, enabling global collaboration and innovation. However, sustainable funding remains a challenge for many open-source projects. In response to this challenge, we present a pioneering research and development endeavour: a Blockchain-Powered Open -Source Project Funding and Splitting Platform. This platform leverages blockchain technology to create a transparent, secure, and decentralized ecosystem where users can upload their open-source projects, donors can contribute funds, and contributions are automatically rewarded to project contributors based on their work. This paper outlines the comprehensive research and development journey of our blockchain-powered platform, discussing the architectural design, smart contract implementation, security considerations, and user experience. We also examine the impact of blockchain integration on open-source communities, the challenges encountered, and the potential for future expansion and adoption

Controlling Randomization in Astronomy Simulations

As the primary requirement, correctly implementing and controlling random number generation is vital for a range of scientific analyses and simulations across astronomy and planetary science. Beyond advice on how to set the seed, there is little guidance in the literature for how best to handle pseudo-random number generation in the current era of open-source astronomical software development. We present our methodology for implementing a pseudo-random number generation in astronomy simulations and software and share the short lines of python code that create the generator. Without sacrificing randomization at run time, our strategy ensures reproducibility on a per function/module basis for unit testing and for run time debugging where there may be multiple functions requiring lists of randomly generated values that occur before a specific function is executed.

An Open-Source Software Reliability Model Considering Learning Factors and Stochastically Introduced Faults

In recent years, software development models have undergone changes. In order to meet user needs and functional changes, open-source software continuously improves its software quality through successive releases. Due to the iterative development process of open-source software, open-source software testing also requires continuous learning to understand the changes in the software. Therefore, the fault detection process of open-source software involves a learning process. Additionally, the complexity and uncertainty of the open-source software development process also lead to stochastically introduced faults when troubleshooting in the open-source software debugging process. Considering the phenomenon of learning factors and the random introduction of faults during the testing process of open-source software, this paper proposes a reliability modeling method for open-source software that considers learning factors and the random introduction of faults. Least square estimation and maximal likelihood estimation are used to determine the model parameters. Four fault data sets from Apache open-source software projects are used to compare the model performances. Experimental results indicate that the proposed model is superior to other models. The proposed model can accurately predict the number of remaining faults in the open-source software and be used for actual open-source software reliability evaluation.

Agcounts: An R Package to Calculate ActiGraph Activity Counts From Portable Accelerometers

Portable accelerometers are used to capture physical activity in free-living individuals with the ActiGraph being one of the most widely used device brands in physical activity and health research. Recently, in February 2022, ActiGraph published their activity count algorithm and released a Python package for generating activity counts from raw acceleration data for five generations of ActiGraph devices. The nonproprietary derivation of the ActiGraph count improved the transparency and interpretation of accelerometer device-measured physical activity, but the Python release of the count algorithm does not integrate with packages developed by the physical activity research community using the R Statistical Programming Language. In this technical note, we describe our efforts to create an R-based translation of ActiGraph’s Python package with additional extensions to make data processing easier and faster for end users. We call the resulting R package agcounts and provide an inside look at its key functionalities and extensions while discussing its prospective impacts on collaborative open-source software development in physical behavior research. We recommend that device manufacturers follow ActiGraph’s lead by providing open-source access to their data processing algorithms and encourage physical activity researchers to contribute to the further development and refinement of agcounts and other open-source software.

Temporal Autoregressive Matrix Factorization for High-Dimensional Time Series Prediction of OSS.

Open-source software (OSS) plays an increasingly significant role in modern software development tendency, so accurate prediction of the future development of OSS has become an essential topic. The behavioral data of different open-source software are closely related to their development prospects. However, most of these behavioral data are typical high-dimensional time series data streams with noise and missing values. Hence, accurate prediction on such cluttered data requires the model to be highly scalable, which is not a property of traditional time series prediction models. To this end, we propose a temporal autoregressive matrix factorization (TAMF) framework that supports data-driven temporal learning and prediction. Specifically, we first construct a trend and period autoregressive model to extract trend and period features from OSS behavioral data, and then combine the regression model with a graph-based matrix factorization (MF) to complete the missing values by exploiting the correlations among the time series data. Finally, use the trained regression model to make predictions on the target data. This scheme ensures that TAMF can be applied to different types of high-dimensional time series data and thus has high versatility. We selected ten real developer behavior data from GitHub for case analysis. The experimental results show that TAMF has good scalability and prediction accuracy.

Roadmap for Simulating Quantum Circuits Utilising IBM’s Qiskit Library: Programming Approach

This paper explains the roadmap for running quantum circuit programs based on the Qiskit library in quantum simulators as well as real cloud-based IBM quantum computers. Qiskit is a free and open-source software development platform based on the Python programming language that is used in quantum programming. Qiskit acts as a link between quantum computing’s theoretical foundations and the practical aspects of programming and experimentation. It also allows users to experiment with and develop quantum algorithms, as well as simulate and execute them on simulators and real-world cloud-based quantum devices. It also simplifies the quantum programming process and allows a diverse range of people to participate in the exciting world of quantum computing. The paper, on the other hand, provides the mathematical foundation for analyzing quantum circuits and algorithms using linear algebra principles, as they provide the tools needed to describe and manipulate quantum states and operations. Furthermore, the paper shows quantum circuit design and implementation using real Qiskit codes.

DrogoFinder: An open-source graphical user interface for the identification of illicit drugs using infrared spectroscopy

The development of Free and Open-Source Software (FOSS) is being increasingly recognized as an indispensable resource for the development, validation, and replication of analytical methodologies and tools. In this context, the use of Attenuated Total Reflectance Infrared (ATR-IR) spectroscopy for the in-situ identification of drugs requires software for the treatment of spectroscopic data, including spectral quality controls, the subtraction of possible excipients, and the comparison with well-defined libraries that can be complex and limits its application on the field analysis by non-expert users. Here we describe a user-friendly FOSS for drug identification that can be operated in an intuitive way, including automatic features such as i) quality controls that warn the user from possible technical problems during spectrum acquisition (e.g. water vapour, contaminated background), ii) the subtraction of the contribution of excipients and other substances present on the sample, and iii) the creation of custom and updated cloud-based libraries to deal with the great number of new psychoactive substances (NPS) that are constantly being developed and introduced for their consume. The proposed application was tested by expert and non-expert users with spectra from 42 drug samples measured in situ in a music festival and 39 seized samples measured in a laboratory. Non-expert users were able to flag technical problems in the spectra and to perform excipient subtractions automatically, obtaining drug identifications that matched those ones obtained by reference methods and dedicated commercial software. We share both, the code, and a standalone Windows app to reach worldwide users and scientists interested in the identification of drugs.

A Systematic Analysis of Problems in Open Collaborative Data Engineering

Collaborative workflows are common in open-source software development. They reduce individual costs and improve the quality of work results. Open data shares many characteristics with open-source software, as it can be used, modified, and redistributed by anyone, for free. However, in contrast to open-source software engineering, collaborative data engineering on open data lacks a shared understanding of processes, methods, and tools. This article presents a systematic literature review of collaboration processes, methods, and tools in data engineering as performed by open data users. An additional interview study with practitioners confirms and enhances the findings and strengthens the resulting insights. We find an ecosystem with heterogeneous participants and no standardized processes, methods, and tools. Participants face a variety of technical and social challenges during their work. Our work provides a structured overview of collaboration systems in open collaborative data engineering, enabling further research. Additionally, we contribute preliminary guidelines for successful open collaborative data engineering projects and recommendations to increase its adoption for open data ecosystems.

The vital role of community in open source software development: A framework for assessment and ranking

AbstractOpen source software (OSS) follows a software development paradigm whereby self‐motivated volunteers scattered all around the globe contribute to the development in the form of code, documentation, feedback, feature recommendations, bug reporting, and bug resolution. These volunteers, commonly referred to as OSS project community, serve as the foundation of the OSS project, fostering its creation and sustenance and providing long‐term support. The quality and sustainability of the OSS project is reliant upon the development and structure of the self‐governing community. When a business organization plans to acquire an OSS solution, it not only takes into consideration the factors such as reliability, security, and scalability but also attaches significant importance to the likelihood of the OSS project being maintained and supported in the future so that it can rely on it as a stable and secure technology solution. Modern cloud‐based software hosting platforms, such as GitHub, offer a range of options for automatically and freely accessing the complete development history of millions of OSS projects. This easy availability of detailed development history has enabled researchers to analyze and draw quantitative and scientific inferences about the quality of an OSS project which generally involves assessing three aspects, namely, software product, development process, and project community. With focus on project community part, a Framework for Assessment and Ranking of OSS Community is being presented in the current research work, following a detailed examination of the largest source code hosting and project collaboration platform, GitHub. Technique for Order of Preference by Similarity to Ideal Solution from Multi‐Criteria Decision‐Making toolkit has been utilized for assessing the quality of the project community. The framework has been validated by applying it on nine OSS projects and comparing the results with the outcomes obtained through an existing OSS evaluation methodology. The comparative analysis demonstrated that the proposed framework aligns with the aforementioned evaluation methodology while offering an opportunity for in‐depth analysis on the dynamics of volunteer communities, which is lacking in previous evaluation methods. These insights can prove valuable for both potential adopters and project maintainers, aiding them in making informed strategic decisions.

All of the same breed? A networking perspective of private-collective innovation

Much research on open source software development has highlighted the best-of-both-worlds benefits generated by private and collective contributions from a broad base of developers. However, these studies have tended to overlook the heterogeneous nature of various developer groups including firm-sponsored developers. To unveil the behavioural differences between developer groups, we expand upon the private-collective innovation model using a networking approach, linking network closure and positional embeddedness with technical contribution. We tested our predictions using a lagged analysis based on communication and networking behaviours on the Linux kernel mailing-list in the production of the Linux operation system over a three-year period. Our findings support our predictions, showing that network closure has an adverse impact on technical contribution. Additionally, the relationship between positional embeddedness and technical contribution follows an inverted U-shape. In addition, high positional embeddedness counteracts the negative influence of extensive network closure on technical contribution. These effects are partly moderated by respective developer groups. Our model and results offer important theoretical and practical implications for community management within the framework of private-collective innovation.

Multicriteria Optimization of Software Development Platform Selection

The problem of multicriteria optimization of tech stack selection in a non-linear software development environment is formalized. Approaches to solving the problem based on the formation of a compromise area of local quality criteria, additive convolution of vector criteria and their scalarization are considered. An aggregate quality criterion of the software development platform is proposed. It allows taking into account the nonlinearities of the external environment in the framework of solving the problem of extremal control. The coordinates of the vector criteria are piecewise continuous functions A comparative analysis of various approaches to changing the software development tech stack in the face of significant disturbances in the development tools market has been carried out. The possibilities of boxed solutions, custom development and Open Source software development in ensuring information security of the software development environment are shown. The information stability of a software development project using Less Code tools is established and the advantages of technological solutions are shown. The analysis of the adequacy of the obtained solutions was carried out using the Open Source Less Code of the Jmix platform. The data of a comparative analysis of the budgets of the Less Code platform and custom software from vendors are given, which showed the benefits of using Open Source software development tools for long-term operation of the development platform.

Methodology for collective location fixing of observed emergencies by intersection/resection based on mobile telecomunication application with cartographic interface

In modern higher education, it is required not only to prepare students to perform work on finished tasks in the subject area they have studied. It is also necessary to prepare students for independent activities, in which students do not work on ready-made tasks, but, on the contrary, are looking for niches in business, in which they themselves can offer in the subject area they have mastered, business-demanded solutions. This is another area of activity, which also requires development while studying at a university. It can be defined as "entrepreneurial competencies of a student." In recent years, the direction "Startup as a Diploma" has been developing, in which a university graduate protects not conditional academic work, but a real technological project with business prospects, to which the students developing it have ownership rights. The creation and maintenance of such projects changes the relationship between student and teacher, for this activity it is necessary to change the traditional teaching methodology. As a task of teachers, we decided to do the following: Find a subject area related to IT development, in which, due to recent achievements, there are opportunities for fast, technically not very complex technological solutions available to students, with the help of which you can create popular solutions. The work proposes an open source software development project, within which students can, performing tasks that are feasible for themselves, create software applications that are in demand in practice, as well as develop development strategies for related business projects. The project is dedicated to solving the problem of determining the coordinates of observed objects and phenomena based on data entered simultaneously by several users in different places using household mobile devices without using special technological equipment such as theodolites or tacheometers. The authors developed a mobile application, the value of which lies in the fact that in the public field allows you to realize the monitoring potential of the population interested in preventing unwanted or dangerous events and preventing emergency situations; professional allows you to assess the quality of the navigation signal in conditions of possible targeted interference; in the educational aspect organize training in the methods of joint fixation of objects and target designation on educational geopolygons. Currently, the project is being developed by students of the Department of Data Analysis and Machine Learning of the Financial University under the Government of the Russian Federation and the Moscow State University of Geodesy and Cartography. This paper presents a description of the project, the proposed solution architecture. References to source code repositories are given. The results of the pilot versions of the software are given.

SUMMIT: Scaffolding Open Source Software Issue Discussion Through Summarization

Issue Tracking Systems (ITS) often support commenting on software issues, which creates a space for discussions centered around bug fixes and improvements to the software. For Open Source Software (OSS) projects, issue discussions serve as a crucial collaboration mechanism for diverse stakeholders. However, these discussions can become lengthy and entangled, making it hard to find relevant information and make further contributions. In this work, we study the use of summarization to aid users in collaboratively making sense of OSS issue discussion threads. Through an empirical investigation, we reveal a complex picture of how summarization is used by issue users in practice as a strategy to help develop and manage their discussions. Grounded on the different objectives served by the summaries and the outcome of our formative study with OSS stakeholders, we identified a set of guidelines to inform the design of collaborative summarization tools for OSS issue discussions. We then developed SUMMIT, a tool that allows issue users to collectively construct summaries of different types of information discussed, as well as a set of comments representing continuous conversations within the thread. To alleviate the manual effort involved, SUMMIT uses techniques that automatically detect information types and summarize texts to facilitate the generation of these summaries. A lab user study indicates that, as the users of SUMMIT, OSS stakeholders adopted different strategies to acquire information on issue threads. Furthermore, different features of SUMMIT effectively lowered the perceived difficulty of locating information from issue threads and enabled the users to prioritize their effort. Overall, our findings demonstrated the potential of SUMMIT, and the corresponding design guidelines, in supporting users to acquire information from lengthy discussions in ITSs. Our work sheds light on key design considerations and features when exploring crowd-based and machine-learning-enabled instruments for asynchronous collaboration on complex tasks such as OSS development.