Minghui Zhou

What make long term contributors: willingness and opportunity in OSS community

To survive and succeed, software projects need to attract and retain contributors. We model the individuals chances to become a valuable contributor through her capacity, willingness, and the opportunity to contribute at the time of joining. Using issue tracking data of Mozilla and Gnome, we find that the probability for a new joiner to become a Long Term Contributor (LTC) is associated with her willingness and environment. Specifically, during their first month, future LTCs tend to be more active and show more community-oriented attitude than other joiners. Joiners who start by commenting on instead of reporting an issue or ones who succeed to get at least one reported issue to be fixed, more than double their odds of becoming an LTC. The micro-climate with a productive and clustered peer group increases the odds. On the contrary, the macro-climate with high project popularity and the micro-climate with low attention from peers reduce the odds. This implies that the interaction between individuals attitude and projects climate are associated with the odds that an individual would become a valuable contributor or disengage from the project. Our findings may provide a basis for empirical approaches to design a better community architecture and to improve the experience of contributors.

Developer fluency: achieving true mastery in software projects

Outsourcing and offshoring lead to a rapid influx of new developers in software projects. That, in turn, manifests in lower productivity and project delays. To address this common problem we study how the developers become fluent in software projects. We found that developer productivity in terms of number of tasks per month increases with project tenure and plateaus within a few months in three small and medium projects and it takes up to 12 months in a large project. When adjusted for the task difficulty, developer productivity did not plateau but continued to increase over the entire three year measurement interval. We also discovered that tasks vary according to their importance(centrality) to a project. The increase in task centrality along four dimensions: customer, system-wide, team, and future impact was approximately linear over the entire period. By studying developer fluency we contribute by determining dimensions along which developer expertise is acquired, finding ways to measure them, and quantifying the trajectories of developer learning.

Does the initial environment impact the future of developers

Software developers need to develop technical and social skills to be successful in large projects. We model the relative sociality of developer as a ratio between the size of her communication network and the number of tasks she participates in. We obtain both measures from the problem tracking systems. We use her workflow peer network to represent her social learning, and the issues she has worked on to represent her technical learning. Using three open source and three traditional projects we investigate how the project environment reflected by the sociality measure at the time a developer joins, affects her future participation. We find: a) the probability that a new developer will become one of long-term and productive developers is highest when the project sociality is low; b) times of high sociality are associated with a higher intensity of new contributors joining the project; c) there are significant differences between the social learning trajectories of the developers who join in low and in high sociality environments; d) the open source and commercial projects exhibit different nature in the relationship between developers tenure and the projects environment at the time she joins. These findings point out the importance of the initial environment in determining the future of the developers and may lead to better training and learning strategies in software organizations.

Service Selection Approach Considering the Trustworthiness of QoS Data: Service Selection Approach Considering the Trustworthiness of QoS Data

As the number of web services with the similar function is increasing, QoS-based service selection at runtime has become an important research topic. The existing QoS-based services selection approaches always assume that the QoS data coming from service providers and users are effective and trustworthy, which is actually impossible in reality. This paper proposes a service selection approach considering the trustworthiness of QoS data, which classifies and computes the QoS attributes according to the source of QoS data. For the QoS attributes whose data come from service providers, the statistics of past runtime data to revise the providers’ QoS data are used. For the QoS attributes whose data come from users, feedback similarity to weigh users’ QoS data is used. Furthermore, an implementation framework and a set of experiments are given, which show that this approach can effectively weaken the influence of untrustworthy QoS data on the services selection, thus can strengthen the accuracy of the service selection.

A multi-property trust model for reconfiguring component software

While component software continues to grow in size and complexity, it becomes increasingly difficult to ensure qualities for component services, especially at run-time. This paper focuses on a framework on middleware for dynamic re-configuration of components of different qualities from the view of trust. Firstly, a trust management model is built, in which the management framework and measurement model are presented. Secondly, the reconfiguration algorithm is described based on the model. Thirdly, the trust management is implemented as a kind of public services and some tools on a J2EE-compliant middleware platform, i.e., PKUAS. Finally, the related work is discussed and compared with our research.

Patterns of folder use and project popularity: a case study of github repositories

Context: Every software development project uses folders to organize software artifacts. Goal: We would like to understand how folders are used and what ramifications different uses may have. Method: In this paper we study the frequency of folders used by 140k Github projects and use regression analysis to model how folder use is related to project popularity, i.e., the extent of forking. Results: We find that the standard folders, such as document, testing, and examples, are not only among the most frequently used, but their presence in a project is associated with increased chances that a projects code will be forked (i.e., used by others) and an increased number of forks. Conclusions: This preliminary study of folder use suggests opportunities to quantify (and improve) file organization practices based on folder use patterns of large collections of repositories.

Impact of Triage: A Study of Mozilla and Gnome

Triage is of great interest in software projects because it has the potential to reduce developer effort by involving a broader base of non-developer contributors to filter and augment reported issues. Using issue tracking data and interviews with experienced contributors we investigate ways to quantify the impact of triagers on reducing the number of issues developers need to resolve in two OSS projects: Mozilla and Gnome. We find the primary impact of triagers to involve issue filtering, filling missing information, and determining the relevant product. While triagers were good at filtering invalid issues and as accurate as developers in filling in missing issue attributes, they had more difficulty accurately pinpointing the relevant product. We expect that this work will highlight the importance of issue triage in software projects and will help design further studies on understanding and improving triage practices.

Inflow and Retention in OSS Communities with Commercial Involvement: A Case Study of Three Hybrid Projects

Motivation: Open-source projects are often supported by companies, but such involvement often affects the robust contributor inflow needed to sustain the project and sometimes prompts key contributors to leave. To capture user innovation and to maintain quality of software and productivity of teams, these projects need to attract and retain contributors. Aim: We want to understand and quantify how inflow and retention are shaped by policies and actions of companies in three application server projects. Method: We identified three hybrid projects implementing the same JavaEE specification and used published literature, online materials, and interviews to quantify actions and policies companies used to get involved. We collected project repository data, analyzed affiliation history of project participants, and used generalized linear models and survival analysis to measure contributor inflow and retention. Results: We identified coherent groups of policies and actions undertaken by sponsoring companies as three models of community involvement and quantified tradeoffs between the inflow and retention each model provides. We found that full control mechanisms and high intensity of commercial involvement were associated with a decrease of external inflow and with improved retention. However, a shared control mechanism was associated with increased external inflow contemporaneously with the increase of commercial involvement. Implications: Inspired by a natural experiment, our methods enabled us to quantify aspects of the balance between community and private interests in open- source software projects and provide clear implications for the structure of future open-source communities.

Product assignment recommender

Effectiveness of software development process depends on the accuracy of data in supporting tools. In particular, a customer issue assigned to a wrong product team takes much longer to resolve (negatively affecting user-perceived quality) and wastes developer effort. In Open Source Software (OSS) and in commercial projects values in issue-tracking systems (ITS) or Customer Relationship Management (CRM) systems are often assigned by non-developers for whom the assignment task is difficult. We propose PAR (Product Assignment Recommender) to estimate the odds that a value in the ITS is incorrect. PAR learns from the past activities in ITS and performs prediction using a logistic regression model. Our demonstrations show how PAR helps developers to focus on fixing real problems, and how it can be used to improve data accuracy in ITS by crowd-sourcing non-developers to verify and correct low-accuracy data. http://youtu.be/IuykbzSTj8s

Towards a Well Structured and Dynamic Application Server

In recent years, Java Enterprise Edition (Java EE) technologies keep expanding with more and more features. The customization of application server is becoming multifarious owing to different environments and domains. And delivering a continuous evolving application server is more frequent and costly. However, current application servers cannot meet such requirements, due to their inexplicit module boundary, insufficient lifecycle management and relatively absent dependency management. In this paper, we propose an approach to make an application server well structured and dynamic. Guided by this approach, we implemented a prototype, namely PKUAS II. The evaluations show that a flexible, customizable and dynamic application server can be developed without an adverse effect on the performance.