Open source software ecosystems: A Systematic mapping

Open source software has witnessed an exponential growth in the last two decades and it is playing an increasingly important role in many companies and organizations leading to the formation of open source software ecosystems. In this paper we present a quality model that will allow the evaluation of those ecosystems in terms of their relevant quality characteristics such as health or activeness. To design this quality model we started by analysing the quality measures found during the execution of a systematic literature review on open source software ecosystems and, then, we classified and reorganized the set of measures in order to build a solid quality model.

In Open Source Software (OSS) development community supported by spontaneous volunteers, technical capabilities, hunger for fame and the satisfaction of contribution are said to be motivating factor for participation. In that community, vendors always play auxiliary roles, and integrate the result of OSS into their business activities. However, in the Eclipse OSS community, the main role of OSS development activities is taken over by vendors. The relationship between individuals and vendors is reversed. Therefore, it becomes important to maintain the motivation of the development community, promote innovation and link the activities to the profit of vendors. In other words, management of co-creation and competition are being conducted at the same time. This paper tries to clarify internal and external structures in an OSS ecosystem led by vendors considering the Eclipse community as one particular case. Also it constructs a co-creation model to promote sustainable development for an OSS ecosystem.

Software ecosystems have gained a lot of attention in recent times. Industry and developers gather around technologies and collaborate to their advancement; when the boundaries of such an effort go beyond certain amount of projects, we are witnessing the appearance of Free/Libre and Open Source Software (FLOSS) ecosystems. In this chapter, we explore two aspects that contribute to a healthy ecosystem, related to the attraction (and detraction) and the death of ecosystems. To function and survive, ecosystems need to attract people, get them onboarded, and retain them. In Section One, we explore possibilities with provocative research questions for attracting and detracting contributors (and users): the lifeblood of FLOSS ecosystems. Then, in the Section Two, we focus on the death of systems, exploring some presumed to be dead systems and their state in the afterlife.

Cyber security is a rapidly developing field and open-source software (OSS) is being led by a collaborative community and a transparent nature. This research intends to make a theoretical framework highlighting the symbiosis of community engagement models, governance models, and the security of open-source ecosystems. The significant purposes aim to investigate how community engagement affects open source software development, analyze the deployment of the governance systems in widely used open source projects, and create the theoretical model that brings the cybersecurity processes in those practices. The literature survey covers existing research on open-source software development, community engagement, governance models, and cybersecurity practices within the OSS ecosystem. Through literature review the basic concepts are investigated using conceptual analysis to determine which principles and mechanisms the Community Model Engagement and Governance models operate, influencing the security of Open Source Software. Open-source project policy recommendations are the foundation for the security of communities where members fully contribute to better governance. This includes developing a fundamental conceptual analysis to lay out the framework's principles and operation (mechanisms). This contributes to the overall development of the theoretical framework. This research expects to develop a standardized theoretical framework that tackles the community engagement-governance models-security software link from new and insightful perspectives. Practical policy recommendations to protect OSS projects will be presented to solve the cybersecurity problem easily and immediately. This study aims to add to the academic and practical discussions that focus on human and organizational components' critical roles in securing open-source software. The discussion of theoretical aspects gives this platform a unique angle that fits well into the technical approach while improving the understanding of a legally open cybersecurity community

In nature ecosystems, animal life-spans are determined by genes and some other biological characteristics. Similarly, the software project life-spans are related to some internal or external characteristics. Analyzing the relations between these characteristics and the project life-span, may help developers, investors, and contributors to control the development cycle of the software project. The paper provides an insight on the project life-span for a free open source software ecosystem. The statistical analysis of some project characteristics in GitHub is presented, and we find that the choices of programming languages, the number of files, the label format of the project, and the relevant membership expressions can impact the life-span of a project. Based on these discovered characteristics, we also propose a prediction model to estimate the project life-span in open source software ecosystems. These results may help developers reschedule the project in open source software ecosystem.

In this paper we review the use of plug-in architectures as a technological platform for software ecosystems. Our observation is that the software community has viewed and used plug-ins as powerful extension mechanisms offering a wide range of quality properties. Looking beyond such low level technical interpretation, we argue that pluggable systems should be perceived and treated as a higher level architectural pattern for the development of sustainable software ecosystem. In order to back our perspective, we offer a detail documentation of the plug-in architecture along with technical documentation of a widely used plug-in based software ecosystems, namely, Apache web server, as a guideline for building new open source software ecosystems.

Movies of human induced pluripotent stem cell (hiPSC)-derived engineered cardiac tissue (microbundles) contain abundant information about structural and functional maturity. However, extracting these data in a reproducible and high-throughput manner remains a major challenge. Furthermore, it is not straightforward to make direct quantitative comparisons across the multiple in vitro experimental platforms employed to fabricate these tissues. Here, we present “MicroBundlePillarTrack,” an open-source optical flow-based package developed in Python to track the deflection of pillars in cardiac microbundles grown on experimental platforms with two different pillar designs (“Type 1” and “Type 2” design). Our software is able to automatically segment the pillars, track their displacements, and output time-dependent metrics for contractility analysis, including beating amplitude and rate, contractile force, and tissue stress. Because this software is fully automated, it will allow for both faster and more reproducible analyses of larger datasets and it will enable more reliable cross-platform comparisons as compared to existing approaches that require manual steps and are tailored to a specific experimental platform. To complement this open-source software, we share a dataset of 1,540 brightfield example movies on which we have tested our software. Through sharing this data and software, our goal is to directly enable quantitative comparisons across labs, and facilitate future collective progress via the biomedical engineering open-source data and software ecosystem.

Is Open Source About Innovation? How Interactions with the Open Source Community Impact on the Innovative Performances of Entrepreneurial Ventures

The development of machine learning (ML) systems in high-stakes domains has amplified concerns about fairness, prompting the creation of fairness toolkits offering metrics and mitigation techniques. Open-source software (OSS) ecosystems, a critical driver of AI innovation, present a unique opportunity to study the practical adoption of these toolkits. This paper aims to empirically characterize the adoption of fairness toolkits in OSS ML projects by investigating for what purposes they are used and how their usage evolves over time. We conducted a mining study on GitHub repositories related to real-world ML projects that integrate fairness toolkits such as AIF360 and Fairlearn . Starting from 1,096 candidate repositories, we applied systematic filtering to identify a final dataset of 20 relevant ML projects (comprising 5,777 total commits). We analyzed toolkit usage by examining invoked APIs and commit histories to uncover patterns of adoption and evolution. Our findings reveal that fairness toolkits are predominantly used for diagnostic purposes, with analytic components integrated early in the project lifecycle and rarely modified thereafter. In contrast, mitigation techniques are infrequently adopted, tend to appear later, and exhibit short, unstable lifespans. Our results show that the adoption of fairness toolkits in OSS ML projects is limited and often restricted to initial diagnostic phases, with active mitigation practices remaining rare. These findings highlight the need for improved support to foster more sustained and effective integration of fairness practices within open-source development.

In this study, we estimate the effect of “online following,” a basic form of online social interaction, on members’ contributions in open source software (OSS) communities, using a unique longitudinal data set containing information on over 4 million OSS developers and their social interactions over 7 years. We find that obtaining new followers in the previous month has a significant positive effect on developers’ level of contribution in the current month. The effect carries over to the next month although the marginal effect decreases. We further find that the effect of new followers on their contribution level is much stronger for freelancers than those with company affiliation. In contrast to the previous literature that posited the existence of non-monetary incentives for developers who contribute to the OSS communities, our result suggests the existence of incentives that are tied to future monetary rewards for developers on these platforms. Our findings have important implications for the OSS platforms as well as the OSS community. OSS platform designers may consult our results to learn about the social features that affect members’ contribution. We also encourage OSS community to use the “following” feature more prominently on OSS platforms to incentivize higher contribution levels to the projects.

Purpose– This paper aims to add to the understanding of knowledge sharing in online communities through an investigation of the relationship between individual participant’s motivations and management in open source software (OSS) communities. Drawing on a review of literature concerning knowledge sharing in organisations, the factors that motivate participants to share their knowledge in OSS communities, and the management of such communities, it is hypothesised that the quality of management influences the extent to which the motivations of members actually result in knowledge sharing.Design/methodology/approach– To test the hypothesis, quantitative data were collected through an online questionnaire survey of OSS web developers with the aim of gathering respondents’ opinions concerning knowledge sharing, motivations to share knowledge and satisfaction with the management of OSS projects. Factor analysis, descriptive analysis, correlation analysis and regression analysis were used to explore the survey data.Findings– The analysis of the data reveals that the individual participant’s satisfaction with the management of an OSS project is an important factor influencing the extent of their personal contribution to a community.Originality/value– Little attention has been devoted to understanding the impact of management in OSS communities. Focused on OSS developers specialising in web development, the findings of this paper offer an important original contribution to understanding the connections between individual members’ satisfaction with management and their motivations to contribute to an OSS project. The findings reveal that motivations to share knowledge in online communities are influenced by the quality of management. Consequently, the findings suggest that appropriate management can enhance knowledge sharing in OSS projects and online communities, and organisations more generally.

Towards Engineering Free/Libre Open Source Software (FLOSS) Ecosystems for Impact and Sustainability

An Open Source Software (OSS) project is unlikely to be successful unless there is an accompanied community that provides the platform for developers and users to collaborate. Members of such communities are volunteers whose motivation to participate and contribute is of essential importance to the success of OSS projects. In this paper, we aim to create an understanding of what motivates people to participate in OSS communities. We theorize that learning is one of the motivational forces. Our theory is grounded in the learning theory of Legitimate Peripheral Participation, and is supported by analyzing the social structure of OSS communities and the co-evolution between OSS systems and communities. We also discuss practical implications of our theory for creating and maintaining sustainable OSS communities as well as for software engineering research and education.

User contributions are crucial to the success of open source software (OSS) communities. As users conduct frequent interactions between each other, their contribution behaviour may receive the social influence from other members. Drawing on the social influence theory, this research examined user contributions in OSS communities. The results indicated that contribution intention is significantly affected by social identity, which includes cognitive, affective and evaluative identity. In addition, the researchers found that the subjective norm has a negative effect on contribution intention. The results imply that service providers need to enhance user identification with the community in order to facilitate their contribution in OSS communities.

A developer's popularity plays a crucial role in their success within open source software (OSS) communities and their access to sponsorship opportunities. This study seeks to answer the question: which signals have the most predictive power for popularity and sponsorship volume on social coding platforms? Using algorithm-supported abductive theory generation supplemented by qualitative insights from observations and interviews, we arrive at a theory of peer evaluation in OSS communities. We examine a large number of signals and categorize them. The two categories are signaling via self-disclosure through profile signals and signaling via contribution quantity and quality through behavioral signals. The large amount of data available to us allows us to use machine learning techniques to arrive at top-ranking predictors within each category. We generate our theory by finding robust patterns and test our theory using a hold-out sample. Our findings indicate that easily observable credibility-enhancing and approachability-related developer profile signals hold greater predictive importance in shaping popularity. However, harder to observe and more complex behavioral signals show greater predictive importance for sponsorship volume. These results signify that OSS social coding platforms are not meritocratic, as developer self-disclosure significantly influences popularity. In contrast, sponsorship decisions, due to their high cost and irreversibility, depend on within-platform contribution-related signals. This research contributes to a deeper understanding of popularity and sponsorship within peer-to-peer followership networks in OSS communities. Through our research, platforms are better informed about the predictors of popularity and sponsorship and can introduce measures to enhance the meritocratic nature of these communities. Developers who seek influence and sponsorship on the platform can be more strategic about information disclosure and their contributions.