Analysis and Detection of Information Types of Open Source Software Issue Discussions

Most modern Issue Tracking Systems (ITSs) for open source software (OSS) projects allow users to add comments to issues. Over time, these comments accumulate into discussion threads embedded with rich information about the software project, which can potentially satisfy the diverse needs of OSS stakeholders. However, discovering and retrieving relevant information from the discussion threads is a challenging task, especially when the discussions are lengthy and the number of issues in ITSs are vast. In this paper, we address this challenge by identifying the information types presented in OSS issue discussions. Through qualitative content analysis of 15 complex issue threads across three projects hosted on GitHub, we uncovered 16 information types and created a labeled corpus containing 4656 sentences. Our investigation of supervised, automated classification techniques indicated that, when prior knowledge about the issue is available, Random Forest can effectively detect most sentence types using conversational features such as the sentence length and its position. When classifying sentences from new issues, Logistic Regression can yield satisfactory performance using textual features for certain information types, while falling short on others. Our work represents a nontrivial first step towards tools and techniques for identifying and obtaining the rich information recorded in the ITSs to support various software engineering activities and to satisfy the diverse needs of OSS stakeholders.Comment: 41st ACM/IEEE International Conference on Software Engineering (ICSE2019

Towards a Theory of Software Development Expertise

Software development includes diverse tasks such as implementing new features, analyzing requirements, and fixing bugs. Being an expert in those tasks requires a certain set of skills, knowledge, and experience. Several studies investigated individual aspects of software development expertise, but what is missing is a comprehensive theory. We present a first conceptual theory of software development expertise that is grounded in data from a mixed-methods survey with 335 software developers and in literature on expertise and expert performance. Our theory currently focuses on programming, but already provides valuable insights for researchers, developers, and employers. The theory describes important properties of software development expertise and which factors foster or hinder its formation, including how developers' performance may decline over time. Moreover, our quantitative results show that developers' expertise self-assessments are context-dependent and that experience is not necessarily related to expertise.Comment: 14 pages, 5 figures, 26th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2018), ACM, 201

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

Going farther together:the impact of social capital on sustained participation in open source

Sustained participation by contributors in open-source software is critical to the survival of open-source projects and can provide career advancement benefits to individual contributors. However, not all contributors reap the benefits of open-source participation fully, with prior work showing that women are particularly underrepresented and at higher risk of disengagement. While many barriers to participation in open-source have been documented in the literature, relatively little is known about how the social networks that open-source contributors form impact their chances of long-term engagement. In this paper we report on a mixed-methods empirical study of the role of social capital (i.e., the resources people can gain from their social connections) for sustained participation by women and men in open-source GitHub projects. After combining survival analysis on a large, longitudinal data set with insights derived from a user survey, we confirm that while social capital is beneficial for prolonged engagement for both genders, women are at disadvantage in teams lacking diversity in expertise.\u3cbr/\u3

Using GitHub in Large Software Engineering Classes: An Exploratory Case Study

GitHub has been recently used in Software Engineering (SE) classes to facilitate col- laboration in student team projects. The underlying tenet is that the technical and social feature of GitHub can help students to communicate and collaborate more effectively as a team as well as help teachers to evaluate individual student contribution more objectively. To shed more light on this, in this case study, we explore the benefits and drawbacks of using GitHub in SE classes. Our study is conducted in a software engineering class of 91 students divided into 18 teams. Our research method includes an entry and an exit surveys and a qualitative analysis of students’ commit behavior throughout the period of the project. Our findings show that a) enforcing GitHub in SE classes can be an effective approach for enhancing students’ skills in configuration management and version control, and b) despite the steep learning curve, most teams managed to optimize their commit behavior over time. In terms of student evaluation, our analysis exposed the risks of using GitHub for individual effort assessment. The work in this paper provides several valuable insights for researchers and makes several recommendations for practitioners (teachers) about integrating GitHub in SE classes

An Introduction to Software Ecosystems

This chapter defines and presents different kinds of software ecosystems. The focus is on the development, tooling and analytics aspects of software ecosystems, i.e., communities of software developers and the interconnected software components (e.g., projects, libraries, packages, repositories, plug-ins, apps) they are developing and maintaining. The technical and social dependencies between these developers and software components form a socio-technical dependency network, and the dynamics of this network change over time. We classify and provide several examples of such ecosystems. The chapter also introduces and clarifies the relevant terms needed to understand and analyse these ecosystems, as well as the techniques and research methods that can be used to analyse different aspects of these ecosystems.Comment: Preprint of chapter "An Introduction to Software Ecosystems" by Tom Mens and Coen De Roover, published in the book "Software Ecosystems: Tooling and Analytics" (eds. T. Mens, C. De Roover, A. Cleve), 2023, ISBN 978-3-031-36059-6, reproduced with permission of Springer. The final authenticated version of the book and this chapter is available online at: https://doi.org/10.1007/978-3-031-36060-