Peer code review in open source communitiesusing reviewboard

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

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.

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.

Open source software communities have demonstrated that they can produce high quality results. The overall success of peer code review, commonly used in open source projects, has likely contributed strongly to this success. Code review is an emotionally loaded practice, with public exposure of reputation and ample opportunities for conflict. We set off to ask why code review works for open source communities, despite this inherent challenge. We interviewed 21 open source contributors from four communities and participated in meetings of ROS community devoted to implementation of the code review process. It appears that the hacker ethic is a key reason behind the success of code review in FOSS communities. It is built around the ethic of passion and the ethic of caring. Furthermore, we observed that tasks of code review are performed with strong intrinsic motivation, supported by many non-material extrinsic motivation mechanisms, such as desire to learn, to grow reputation, or to improve one's positioning on the job market. In the paper, we describe the study design, analyze the collected data and formulate 20 proposals for how what we know about hacker ethics and human and social aspects of code review, could be exploited to improve the effectiveness of the practice in software projects.

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.

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.

We conduct an extensive statistical analysis on the social networks of contributors in Open Source Software (OSS) communities using datasets collected from two most fast-growing OSS social interaction sites, Github.com and Ohloh.net. Our goal is to analyze the connectivity structure of the social networks of contributors and to investigate the effect of the different social ties structures on developers’ overall productivity to OSS projects. We, first, analyze the general structure of the social networks, e.g., graph distances and the degree distribution of the social networks. Our social network structure analysis confirms a power-law degree distribution and small-world characteristics. However, the degree mixing pattern shows that high degree nodes tend to connect more with low degree nodes suggesting a collaboration between experts and newbie developers. We further conduct the same analysis on affiliation networks and find that contributors tend to participate in projects of similar team sizes. Second, we study the correlation between various social factors (e.g., closeness and betweenness centrality, clustering coefficient and tie strength) and the productivity of the contributors in terms of the amount of contribution and commitment to OSS projects. The analysis is conducted under the contexts of global and local networks, where a global network analysis considers a developer’s connectivity in the whole OSS community network, whereas a local network analysis considers a developer’s connectivity within a team network that is affiliated to a project. The analysis demonstrates evident influence of the social factors on the developers’ overall productivity.KeywordsOpen source software (OSS)Social networkAffiliation networkGlobal network analysisLocal network analysisDegree of connectivityTies strength

Peer review is the standard process within academia for maintaining publication quality, but it is also widely employed in other settings, such as education and industry, for improving work quality and for generating actionable feedback to content authors. For example, in the software industry peer review of program source code—or peer code review—is a key technique for detecting bugs and maintaining coding standards. In a programming education context, although peer code review offers potential benefits to both code reviewers and code authors, individuals are typically less experienced, which presents a number of challenges. Some of these challenges are similar to those reported in the educational literature on peer review in other academic disciplines, but reviewing code presents unique difficulties. Better understanding these challenges and the conditions under which code review can be taught and implemented successfully in computer science courses is of value to the computing education community. In this work, we conduct a systematic review of the literature on peer code review in higher education to examine instructor motivations for conducting peer code review activities, how such activities have been implemented in practice, and the primary benefits and difficulties that have been reported. We initially identified 187 potential studies and analyzed 51 empirical studies pertinent to our goals. We report the most commonly cited benefits (e.g., the development of programming-related skills) and barriers (e.g., low student engagement), and we identify a wide variety of tools that have been used to facilitate the peer code review process. While we argue that more empirical work is needed to validate currently reported results related to learning outcomes, there is also a clear need to address the challenges around student motivation, which we believe could be an important avenue for future research.

PurposeOpen Source software companies (OSSCs) are confronted with institutional pressures from Open Source software (OSS) communities. They must find an acceptable balance between the expectations of these communities and their own business model. However, there are still few studies that try to analyse the OSSC business models. The purpose of this paper is to highlight OSSC typical business models by using rich empirical data.Design/methodology/approachThe methodology is based on a combination of quantitative analysis of a sample of 66 OSSCs and qualitative analysis of three typical situations resulting from that sample.FindingsThe quantitative study enables the authors to highlight three typical business models. The in-depth study of three typical cases enables the authors to specify these OSSC business models. The authors can distinguish four key dimensions: the relationship developed with the OSS communities, the strategic manoeuvres made, the key resources and competitive positioning.Research limitations/implicationsThe results indicate that it is possible for firms to accommodate both profit and non-profit logics using different strategic manoeuvres to position themselves with regard to the Open Source institutional environment. Such accommodation requires the development of key resources and the adoption of suitable competitive positioning.Practical implicationsThis study allows the authors to highlight two main practical contributions for OSSCs’ directors. First, the different manoeuvres identified may help them to ensure coherence between their strategic choices and the business model chosen. Second, the results can help OSSC founders identify value creation mechanisms more clearly by analysing four key variables.Originality/valueThis paper provides new insight about OSSCs business models. It aggregates four dimensions that provide a more “fine-grained” analysis of business models, while other studies often emphasise one dimension (usually the regime of appropriability).

In open source software (OSS) communities, existing leadership indicators are dominantly measured by code contribution or community influence. Recent studies on emergent leadership shed light on additional dimensions such as intellectual stimulation in collaborative communications. This paper aims to mine communication styles and identify emergent leadership behaviors in OSS communities, using issue comments data. We start with the construction of 6 categories of leadership behaviors based on existing leadership studies. Then, we manually label leadership behaviors in 10,000 issue comments from 10 OSS projects, and extract 304 heuristic linguistic patterns which represent different types of emergent leadership behaviors in flexible and concise manners. Next, an automated algorithm is developed to merge and consolidate different pattern sets extracted from multiple projects into a final pattern ranking list, which can be applied for the automatic leadership identification. The evaluation results show that iLead can achieve a median precision of 0.82 and recall of 0.78, outperforming ten machine/deep learning baselines. We argue that emergent leadership behaviors in issue discussion should be taken into consideration to broaden existing OSS leadership viewpoints.

We consider the team formation problem in open collaborative projects existing in large community setting such as the Open Source Software (OSS) community. Given a query specifying a set of required skills for an open project and an upper bound of team size, the goal is to find a team that maximizes the Degree of Acquaintance (DoA) and covers all the required skills in the query. We define the DoA in terms of the team graph connectivity and edge weights, corresponding to the local Clustering Coefficient for each team member and the strength of social ties between the team members, respectively. We perform a statistical analysis on historical data to show the importance of the connectivity and social tie strength to the overall productivity of the teams in open projects. We show that the problem defined is NP-hard and present three algorithms, namely, PSTA, STA and NFA, to solve the problem. We experiment the algorithms on a dataset from the OSS community. The results show the effectiveness of the proposed algorithms to find a well acquainted teams satisfying a given query.

Assessing User eXperience (UX) maturity is mandatory in the free and open-source software (FOSS) community to avoid wasting resources on projects that may fall short of expectations. Best practices suggest employing UX Capability Maturity Models (UXCMMs), which often specify an evolutionary plateau toward developing a UX-matured system and quantify organizational UX maturity into maturity levels ranging from no or ad hoc improvement to integrated continuous improvement. Numerous generically developed UXCMMs exist. However, none is created for the FOSS community, and less information is available to support their perfect match. Thus, raise suspicions if they have proper UX maturity influencing factors (UXMIFs) for the FOSS community or measure the right thing. The FOSS community differs from traditional software-developing communities and may have different dynamics and UXMIFs, necessitating unique and new methodologies for their discovery. This study, therefore, aims to identify the FOSS community’s UXMIFs and evaluate the community’s knowledge of UX maturity-related concepts. Its findings may help future researchers, practitioners, and other FOSS developers to develop UXCMMs exclusive to the FOSS community. The study’s design is both qualitative and quantitative. It adopted a systematic literature review, interviews, fuzzy Delphi Method, and thematic analysis to collect and analyze data and present the findings. The study’s sample included sixty-two active FOSS projects, fifteen FOSS stakeholders, and twelve UX experts. The outcome shows that 84% of UX experts agreed on the thirty-six FOSS’s UXMIFs with threshold d = 0.143 and crisp values greater than α-cut = 0.5. User feedback and adopted technologies were ranked first, while learnability and use speed were ranked last. Similarly, FOSS stakeholders have shown a shared understanding of UX maturity, connected concepts, and impacting factors.

Code review is of primary importance in modern software development. It is widely recognized that peer review is an efficient and effective practice for improving software quality and reducing defect proneness. For successful review process, peer reviewers should have a deep experience and knowledge with the code being reviewed, and familiar to work and collaborate together. However, one of the main challenging tasks in modern code review is to find the most appropriate reviewers for submitted code changes. So far, reviewers assignment is still a manual, costly and time-consuming task. In this paper, we introduce a search-based approach, namely RevRec, to provide decision-making support for code change submitters and/or reviewers assigners to identify most appropriate peer reviewers for their code changes. RevRec aims at finding reviewers to be assigned for a code change based on their expertise and collaboration in past reviews using genetic algorithm (GA). We evaluated our approach on a benchmark of three open-source software systems, Android, OpenStack, and Qt. Results indicate that RevRec accurately recommends code reviewers with up to 59% of precision and 74% of recall. Our experiments provide evidence that leveraging reviewers expertise from their prior reviews and the socio-technical aspects of the team work and collaboration is relevant in improving the performance of peer reviewers recommendation in modern code review.

Open source software (OSS) is a core part of virtually all software applications today. Due to the rapidly growing impact of OSS on society and the economy, the security aspect has attracted researchers' attention to investigate this distinctive phenomenon. Traditionally, research on OSS security has often focused on technical aspects of software development. We argue that these aspects are important, however, technical security practice considering different social aspects of OSS development will assure the effectiveness and efficiency of the implementation of the tool. To mitigate this research gap, in this empirical study, we explore the current security culture in the OSS development phenomenon using a survey instrument with six evaluation dimensions: attitude, behavior, competency, subjective norms, governance, and communication. By exploring the current security culture in OSS communities, we can start to understand the influence of security on participants' security behaviors and decision-making, so that we can make realistic and practical suggestions. In this paper, we present the measurements of security culture adopted in the study and discuss corresponding security issues that need to be addressed in OSS communities.