Open source oriented cross-platform survey

IF 3.8 2区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

Information and Software Technology Pub Date : 2025-03-17 DOI:10.1016/j.infsof.2025.107704

Simeng Yao , Xunhui Zhang , Yang Zhang , Tao Wang

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引用次数: 0

Abstract

Context:

Open-source software development has become a widely adopted approach to software creation. However, developers’ activities extend beyond social coding platforms (e.g., GitHub), encompassing social Q&A platforms (e.g., StackOverflow) and social media platforms (e.g., Twitter). Therefore, cross-platform research is essential for a deeper understanding of the nature of software development activities.

Objective:

This paper focuses on open-source platforms and systematically summarizes relevant cross-platform research. It aims to assess the current state of cross-platform research and provide insights into the challenges and future developments in this field.

Method:

This paper reviews 69 cross-platform research papers related to open-source software from 2013 to 2024, with a focus on several key areas, including platform interconnections, research themes, experimental design methods, challenges and research opportunities.

Results:

Through the analysis of 69 papers, we found that cross-platform research primarily involves platforms such as social coding, social Q&A, and social media. Researchers typically rely on information traces, including user personal info, technical info, project/post/bug report metadata, interaction info, to facilitate connections between platforms. Cross-platform research in the open-source domain mainly focuses on problem classification and feature extraction. The predominant research methods include data-driven approaches, qualitative studies, modeling and machine learning, and tool development and implementation. Despite these advancements, common challenges remain, such as subjective evaluation bias in manual data classification, insufficient data source coverage, and inaccurate data recognition. Future research opportunities may focus on increasing the diversity of data sources, improving data recognition accuracy, optimizing data classification methods, and clarifying user skill requirements.

Conclusions:

Based on our findings, we propose six future directions for cross-platform research in the open-source domain and provide corresponding recommendations for developers, researchers, and service/tool providers.

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背景：开源软件开发已成为一种广泛采用的软件创建方法。然而，开发人员的活动已超出了社交编码平台（如 GitHub）的范围，还包括社交问答平台（如 StackOverflow）和社交媒体平台（如 Twitter）。因此，跨平台研究对于深入了解软件开发活动的本质至关重要。目的：本文以开源平台为重点，系统总结了相关的跨平台研究。方法：本文综述了 2013 年至 2024 年期间与开源软件相关的 69 篇跨平台研究论文，重点关注平台间的相互联系、研究主题、实验设计方法、挑战和研究机遇等几个关键领域。结果：通过对 69 篇论文的分析，我们发现跨平台研究主要涉及社交编码、社交问答和社交媒体等平台。研究人员通常依靠信息痕迹（包括用户个人信息、技术信息、项目/帖子/错误报告元数据、交互信息）来促进平台间的联系。开源领域的跨平台研究主要集中在问题分类和特征提取方面。主要研究方法包括数据驱动方法、定性研究、建模和机器学习以及工具开发和实施。尽管取得了这些进展，但仍存在一些共同的挑战，如人工数据分类中的主观评价偏差、数据源覆盖不足以及数据识别不准确等。未来的研究机会可能集中在增加数据源的多样性、提高数据识别准确性、优化数据分类方法以及明确用户技能要求等方面。结论：基于我们的研究结果，我们提出了开源领域跨平台研究的六个未来方向，并为开发人员、研究人员和服务/工具提供商提供了相应的建议。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Information and Software Technology 工程技术-计算机：软件工程

CiteScore

9.10

自引率

7.70%

发文量

164

审稿时长

9.6 weeks

期刊介绍： Information and Software Technology is the international archival journal focusing on research and experience that contributes to the improvement of software development practices. The journal''s scope includes methods and techniques to better engineer software and manage its development. Articles submitted for review should have a clear component of software engineering or address ways to improve the engineering and management of software development. Areas covered by the journal include: • Software management, quality and metrics, • Software processes, • Software architecture, modelling, specification, design and programming • Functional and non-functional software requirements • Software testing and verification & validation • Empirical studies of all aspects of engineering and managing software development Short Communications is a new section dedicated to short papers addressing new ideas, controversial opinions, "Negative" results and much more. Read the Guide for authors for more information. The journal encourages and welcomes submissions of systematic literature studies (reviews and maps) within the scope of the journal. Information and Software Technology is the premiere outlet for systematic literature studies in software engineering.