OSS Projects Research Articles

Comparing Developer Attraction and Turnover in OSS vs. OSS4SG Projects: An MSR Study

Open source for social good (OSS4SG) projects are projects whose overarching goal focuses on solving a societal issue and driving positive change. Despite the societal importance of such projects and their alignment with the open-source ideology at its very core, there is a clear lack of understanding of the unique characteristics and operational dynamics of OSS4SG projects. In this work, we use Mining Software Repository (MSR) techniques to empirically investigate the community dynamics and project characteristics of OSS4SG projects compared to OSS projects. We leveraged the GitHub API and GraphQL to mine a dataset of 290 projects (199 OSS4SG, 91 OSS) and answer our main research questions: RQ1: How stable are OSS4SG compared to OSS in terms of newcomers and leavers? RQ2: To what extent do turnover and retention of contributors change over time for OSS vs OSS4SG? Namely, we studied and compared the rates at which contributors joined and left OSS and OSS4SG projects at different stages of life (early, mid, late). We classified projects as attractive (high join rate and low leave rate), unattractive (low join rate and high leave rate), stable (low join rate and low leave rate), and unstable (high join rate and high leave rate). Our results show that the majority of OSS4SG projects (60%) are stable, while the majority of OSS projects (74%) are unstable. Our results also show that OSS4SG retains more of their contributors and has less turnover. Looking at the join and leave rates for projects across different life stages, we found that the difference is significant when all stages of life and considered together. However, the difference is far less significant in the late stage of the project's lifespan, indicating that, as they mature, OSS becomes more similar to OSS4SG in terms of community dynamics.

Free open source communities sustainability: Does it make a difference in software quality?

ContextFree and Open Source Software (FOSS) communities’ ability to stay viable and productive over time is pivotal for society as they maintain the building blocks that digital infrastructure, products, and services depend on. Sustainability may, however, be characterized from multiple aspects, and less is known how these aspects interplay and impact community outputs, and software quality specifically.ObjectiveThis study, therefore, aims to empirically explore how the different aspects of FOSS sustainability impact software quality.Method16 sustainability metrics across four categories were sampled and applied to a set of 217 OSS projects sourced from the Apache Software Foundation Incubator program. The impact of a decline in the sustainability metrics was analyzed against eight software quality metrics using Bayesian data analysis, which incorporates probability distributions to represent the regression coefficients and intercepts.ResultsFindings suggest that selected sustainability metrics do not significantly affect defect density or code coverage. However, a positive impact of community age was observed on specific code quality metrics, such as risk complexity, number of very large files, and code duplication percentage. Interestingly, findings show that even when communities are experiencing sustainability, certain code quality metrics are negatively impacted.ConclusionFindings imply that code quality practices are not consistently linked to sustainability, and defect management and prevention may be prioritized over the former. Results suggest that growth, resulting in a more complex and large codebase, combined with a probable lack of understanding of code quality standards, may explain the degradation in certain aspects of code quality.

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.

"Nip it in the Bud": Moderation Strategies in Open Source Software Projects and the Role of Bots

Much of our modern digital infrastructure relies critically upon open sourced software. The communities responsible for building this cyberinfrastructure require maintenance and moderation, which is often supported by volunteer efforts. Moderation, as a non-technical form of labor, is a necessary but often overlooked task that maintainers undertake to sustain the community around an OSS project. This study examines the various structures and norms that support community moderation, describes the strategies moderators use to mitigate conflicts, and assesses how bots can play a role in assisting these processes. We interviewed 14 practitioners to uncover existing moderation practices and ways that automation can provide assistance. Our main contributions include a characterization of moderated content in OSS projects, moderation techniques, as well as perceptions of and recommendations for improving the automation of moderation tasks. We hope that these findings will inform the implementation of more effective moderation practices in open source communities.

A resilience‐based framework for assessing the evolution of open source software projects

AbstractOpen source software (OSS) has been developing for more than two decades. It originated as a movement with the introduction of the first free/libre OSS operating system, became a popular trend among the developer community, led to enterprise solutions widely embraced by the global market, and began garnering attention from significant players in the software industry (such as IBM's acquisition of RedHat). Throughout the years, numerous software assessment models have been suggested, some of which were created specifically for OSS projects. Most of these assessment models focus on software quality and maintainability. Some models are taking under consideration health aspects of OSS projects. Despite the multitude of these models, there is yet to be a universally accepted model for assessing OSS projects. In this work, we aim to adapt the City Resilience Framework (CRF) for use in OSS projects to establish a strong theoretical foundation for OSS evaluation focusing on the project's resilience as it evolves over time. We would like to highlight that our goal with the proposed assessment model is not to compare two OSS solutions with each other, in terms of resilience, or even do a resilience ranking between the available OSS tools. We are aiming to investigate resilience of an OSS project as it evolves and identify possible opportunities of improvements in the four dimensions we are defining. These dimensions are as follows: source code, business and legal, integration and reuse, and social (community). The CRF is a framework that was introduced to measure urban resilience and most specifically how cities' resilience is changing as they evolve. We believe that a software evaluation model that focuses on resilience can complement the pre‐existing models based on software quality and software health. Although concepts that are related to resilience, like sustainability or viability, already appear in literature, to our best knowledge, there is no OSS assessment model that evaluates the resilience of an OSS project. We argue that cities and OSS projects are both dynamically evolving systems with similar characteristics. The proposed framework utilizes both quantitative and qualitative indicators, which is viewed as an advantage. Lastly, we would like to emphasize that the framework has been tested on the enterprise software domain as part of this study, evaluating five major versions of six OSS projects, Laravel, Composer, PHPMyAdmin, OKApi, PatternalPHP, and PHPExcel, the first three of which are intuitively considered resilient and the three latter nonresilient, to provide a preliminary validation of the models' ability to distinguish between resilient and not resilient projects.

Engine change at 80MPH: OSS projects as laboratories for participatory governance transformation

Engine change at 80MPH: OSS projects as laboratories for participatory governance transformation

Off to a Good Start: Dynamic Contribution Patterns and Technical Success in an OSS Newcomer’s Early Career

Attracting and retaining newcomers are critical aspects for OSS projects, as such projects rely on newcomers’ sustainable contributions. Considerable effort has been made to help newcomers by identifying and overcoming the barriers during the onboarding process. However, most newcomers eventually fail and drop out of their projects even after successful onboarding. Meanwhile, it has been long known that individuals’ early career stages profoundly impact their long-term career success. However, newcomers’ early careers are less investigated in SE research. In this paper, we sought to develop an empirical understanding of the relationships between newcomers’ dynamic contribution patterns in their early careers and their technical success. To achieve this goal, we compiled a dataset of newcomers’ contribution data from 54 large OSS projects under three different ecosystems and analyzed it with time series analysis and other statistical analysis techniques. Our analyses yield rich findings. The correlations between several contribution patterns and technical success were identified. In general, being consistent and persistent in newcomers’ early careers is positively associated with their technical success. While these correlations generally hold in all three ecosystems, we observed some differences in detailed contribution patterns correlated with technical success across ecosystems. In addition, we performed a case study to investigate whether another type of contributions, i.e., documentation contribution, could potentially have positive correlations with newcomers’ technical success. We discussed the implications and summarized practical recommendations to OSS newcomers. The insights gained from this work demonstrated the necessity of extending the focus of research and practice to newcomers’ early careers and hence shed light on future research in this direction.

Exploring factors affecting developer abandonment of open source software projects

AbstractOpen Source Software (OSS) projects have long been studied to understand the need of community support for their growth and survival. However, there has been limited research on developers' abandonment, though it is found to have detrimental effect on quality and sustainability of OSS projects. This paper examines the impact of developer and project‐related factors on developer abandonment in OSS projects. Factors include developer attributes: experience, role, coding language, and joining date, and project attributes: change complexity and sentiments in commit logs. The findings are (1) for developer experience, core/non‐core member, and joining date; there exists a pattern of developers abandoning the projects. (2) There is no definite answer for coding language. (3) It does not relate to the change profile of a project except a few indicators. Sentiments can also not be linked. These results provide OSS community and researchers with useful insights on developer abandonment and the factors influencing it or not.

An in‐depth study of the effects of methods on the dataset selection of public development projects

Public development projects (PDPs) and documented public development projects (DPDPs) are two types of projects that can provide valuable information on how developers and users participate in OSS projects. However, it is hard for researchers to effectively select PDPs and DPDPs due to the lack of specific project selection methods for these two types of projects. To address this problem, a standard dataset was labelled and the base line methods (i.e. selecting projects according to a single feature like star number) under 60 configurations and the machine learning methods under 18 configurations were tested to identify the best configurations in precision and F-measure for selecting PDPs and DPDPs. The results show that (1) to select PDPs or DPDPs with a high precision, the base line method is the best with precision of 0.877 (PDPs) and 0.831 (DPDPs); (2) to select PDPs or DPDPs with a high F-measure, the machine learning methods are the best, with F-measure of 0.817 (PDPs) and 0.789 (DPDPs); (3) existing sample selection strategies can be combined with the machine learning methods, and the precision of selecting PDPs can be increased by 6.39%–41.33% and the precision of selecting DPDPs can be can be increased by 35.50%–269.02%.

The Long Road Ahead: Ongoing Challenges in Contributing to Large OSS Organizations and What to Do

Open source communities hosted in large foundations operate in a complex socio-technical ecosystem, which includes a heterogeneous mix of projects and stakeholders. Previous work has thus far investigated the challenges faced in OSS communities from the point of view of specific stakeholders, primarily at the level of individual projects. None have yet studied the challenges faced within a large, federated open source organization. In this paper, we aim to bridge this gap to identify ongoing challenges contributors face in a mature OSS organization. To do so, we surveyed 624 contributors at the Apache Software Foundation (ASF) and ran 11 semi-structured follow up interviews. We validated our findings through member checking with the interviewees as well as the ASF Diversity and Inclusion (D&I) committee. The contributions of this paper include: (1) an empirically-evidenced conceptual model of the 88 challenges that contributors face in a mature OSS foundation and (2) a set of 48 community-recommended strategies for alleviating these challenges. Our results show that even well-established and mature organizations still face a variety of individual and project-specific challenges and that it is difficult to design a comprehensive set of processes and guidelines to match the needs and expectations of a diverse and large federated community. Our conceptual challenges model and associated strategies to mitigate them can provide guidance to other OSS foundations and projects helping them in building better support processes and tools to create a successful, thriving community of contributors.

What makes the right OSS contributor tick? Treatments to motivate high-skilled developers

We study how OSS project owners can manage their repositories so as to motivate particularly high-skilled coders to exert continuous effort after joining a project. Drawing on literature from personnel economics, we lay out how coders’ skill level affects their selection for a focal project in the first place. In turn, we theorize how project-specific norms and quality aspirations that developers learn about after joining an OSS project represent treatments that varyingly entice developers to contribute more code conditional on their skill level. Based on a custom-tailored dataset merging GitHub and Stack Overflow data for almost 50,000 contributor-project-month observations, we find that repository owners are able to motivate their most talented volunteer contributors when they (1) show no visible commercial orientation while managing their projects, (2) show generosity in accepting external contributions, and (3) provide fast feedback. We discuss implications for research and practice in the fields of community-based organizations like OSS as well as personnel economics.

Network structure and requirements crowdsourcing for OSS projects

Network structure and requirements crowdsourcing for OSS projects

Industrial and OSS developers\u2019 profiles: a family of experiments to evaluate a pioneering neuro-linguistic method for preferred representational systems automatic detection

Software projects use mailing lists as the primary tool for collaboration and coordination. Mailing lists can be an important source for extracting behavioral patterns in the software development. A new approach for that is the use of Neurolinguistic theory to determine what is the Preferred Representational cognitive System (PRS) of software engineers in that specific context. Different resources and cognitive channels are used by developers in order to achieve software understanding. An important question on this matter is: What types of representational systems are preferred by software engineers? This paper presents a psychometrically based neurolinguistic method to identify the PRS of software developers. Experimental evaluation of the approach was carried out in three experiments to assess the Preferred Representational System of developers at Industrial and OSS (Apache server and Postgresql) mailing lists. For the OSS projects, the results showed that the PRS scores of the top-committers clearly differ from the general population of the projects. For industry, the experiment showed that the developers indeed have a PRS. Finally, for both scenarios, the qualitative analysis also indicated that the PRS scores obtained are aligned with the developers’ profiles, considering that alignment is essential to effective communication within the team and enhances the development process due to a better software comprehension.

Changes in emergent software development routines: The moderation effects of routine diversity

Research into the role of routine change has been conducted in relatively stable and structured organizational settings. This study extends the current understanding of routine change to more fluid organizational forms. Drawing on the literature in organizational routines and routine change, we develop and test a model that captures the dynamic relationships among routine change, routine diversity, and project performance in the context of open-source software development. By sequence-mining the digital trace data of OSS projects, we show that routine change reduces project popularity; however, this effect is mitigated as routine diversity increases. Thus, routine diversity provides a coping mechanism for participants to adapt to changing routines. This study reveals the dynamics in open-source development routines and their effects on project popularity, which can apply to various other fluid organizational forms.

OSS Effort Expense Optimization Based on Wiener Process Model and GA

Various open source software are managed by using several bug tracking systems. In particular, the open source software extends to the cloud service and edge computing. Recently, OSF Edge Computing Group is launched by OpenStack. There are big data behind the internet services such as cloud and edge computing. Then, it is important to consider the impact of big data in order to assess the reliability of open source software. Various optimal software release problems have been proposed by specific researchers. In the typical optimal software release problems, the cost parameters are defined as the known parameter. However, it is difficult to decide the cost parameter because of the uncertainty. The purpose of our research is to estimate the effort parameters included in our models. In this paper, we propose an estimation method of effort parameter by using the genetic algorithm. Then, we show the estimation method in section 3. Moreover, we analyze actual data to show numerical examples for the estimation method of effort parameter. As the research results, we found that the OSS managers would be able to comprehend the human resources required before the OSS project in advance by using our method.

A Data Extraction Algorithm from Open Source Software Project Repositories for Building Duration Estimation Models: Case Study of Github

Software project estimation is important for allocating resources and planning a reasonable work schedule. Estimation models are typically built using data from completed projects. While organizations have their historical data repositories, it is difficult to obtaintheir collaboration due to privacy and competitive concerns. To overcome the issue of public access to private data repositories this study proposes an algorithm to extract sufficient data from the GitHub repository for building duration estimation models. More specifically, this study extracts and analyses historical data on WordPress projects to estimate OSS project duration using commits as an independent variable as well as an improved classification of contributors based on the number of active days for each contributor within a release period. The results indicate that duration estimation models using data from OSS repositories perform well and partially solves the problem of lack of data encountered in empirical research in software engineering.

Social network analysis of open source software: A review and categorisation

Context: As companies have become large users of Open Source Software , it is important that they feel comfortable in their Open Source strategies. One of the critical differences between Open Source and Proprietary Software is the communication networks . Objective: This paper tries to set a base for understanding how open source teams are structured and how they change. This is vital to understanding Open Source Software Communities. Method: The paper looks into previous research on Social Network Analysis of Open Source Software, using a systematic literature review. Papers were gathered from Scopus, IEEEXplore and ACM Digital Library, and used or discarded based on predetermined inclusion and exclusion criteria. Research which focuses on the success factors of Open Source Software through Network Analysis is also examined. Results: A subjective categorisation is established for the papers: Structure, Lifecycle and Communication. It was found that the structure of a project has a large bearing on project success, with developers having previously worked together being indicative of project success. Other structure indicators of success are having a small but structured hierarchy, a diverse user and developer base, and project prominence. However, it was found that information on how these structures appear and evolve over time is lacking, and future research into temporal data models to determine project success information is suggested. Conclusions: A categorisation of existing research on Social Network Analysis is provided as a basis for further research. Further work into the lifecycle of OSS projects through Social Network Analysis of temporal project information is suggested.

Investigating the vulnerability fixing process in OSS projects: Peculiarities and challenges

Although vulnerabilities can be considered and treated as bugs, they present numerous peculiarities compared to other types of bugs (canonical bugs in the remainder of the paper). A vulnerability adds functionality to a system, as it allows an adversary to misuse or abuse the system, while a canonical bug is an incomplete or incorrect implementation of a requirement, and thus degrades the functionality of the system. This difference can affect the fixing process of vulnerabilities. By mining the repositories of 6 open source projects, we characterize the differences in the fixing process between vulnerabilities and canonical bugs, highlighting critical issues which could represent challenges for future research. Results of our study demonstrate that: (i) more re-assignments (than the ones observed in canonical bugs) are required for finding the developers able to handle vulnerability-related bugs, (ii) developers’ security-related skills should be profiled, to improve the efficiency of the security bug assignment tasks, and, consequently, reduce the re-assignments, and (iii) vulnerabilities require more effort, contributors and time to define the fixing strategy but smaller time to fix than canonical bugs.

Applying a Usability Technique in the LibreOffice Writer Project


 
 
 As a result of the growth of non-developer users of OSS applications, usability has over the last ten years begun to attract the interest of the OSS community. The OSS community has some special characteristics which are an obstacle to the direct adoption of many usability techniques as specified in the HCI field. The aim of this research is to adapt and evaluate the feasibility of applying the Personas usability technique to one OSS project from the viewpoint of the development team. The applied research method was a case study of the following OSS project LibreOffice-Writer. We formalized the application procedure of the adapted usability technique. We found that either there were no procedures for adopting usability technique in OSS or they were not fully systematized. Additionally, we identified the adverse conditions that are an obstacle to their adoption in OSS and propose the special adaptations required to overcome the obstacles. To avoid some of the adverse conditions, we created web artefacts (e.g. wiki) that are very popular in the OSS field. Additionally, we found that there are obstacles to the application of the technique. Despite these obstacles, it is feasible to apply the adapted Personas technique in OSS project.
 
 

Redundancy, Context, and Preference: An Empirical Study of Duplicate Pull Requests in OSS Projects

OSS projects are being developed by globally distributed contributors, who often collaborate through the pull-based model today. While this model lowers the barrier to entry for OSS developers by synthesizing, automating and optimizing the contribution process, coordination among an increasing number of contributors remains as a challenge due to the asynchronous and self-organized nature of distributed development. In particular, duplicate contributions, where multiple different contributors unintentionally submit duplicate pull requests to achieve the same goal, are an elusive problem that may waste effort in automated testing, code review and software maintenance. While the issue of duplicate pull requests has been highlighted, to what extent duplicate pull requests affect the development in OSS communities has not been well investigated. In this paper, we conduct a mixed-approach study to bridge this gap. Based on a comprehensive dataset constructed from 26 popular GitHub projects, we obtain the following findings: (a) Duplicate pull requests result in redundant human and computing resources, exerting a significant impact on the contribution and evaluation process. (b) Contributors’ inappropriate working patterns and the drawbacks of their collaborating environment might result in duplicate pull requests. (c) Compared to non-duplicate pull requests, duplicate pull requests have significantly different features, e.g., being submitted by inexperienced contributors, being fixing bugs, touching cold files, and solving tracked issues. (d) Integrators choosing between duplicate pull requests prefer to accept those with early submission time, accurate and high-quality implementation, broad coverage, test code, high maturity, deep discussion, and active response. Finally, actionable suggestions and implications are proposed for OSS practitioners.