A large-scale empirical study on Java library migrations: prevalence, trends, and rationales

He, Hao; He, Runzhi; Gu, Haiqiao; Zhou, Minghui

doi:10.1145/3468264.3468571

Cited by 33 publications

(5 citation statements)

References 63 publications

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“…GitHub and Open source software as sources for mining software development data Data mining on GitHub or Open source repositories has been used to create evolving project data sets for intelligent/empirical software engineering [108,109], for example, for Eclipse Modelling Framework metamodels formation [110,111] anomaly detection [112] or identification of migration reasons [113].…”

Section: Covid-19 Influence On Software Engineeringmentioning

confidence: 99%

The Use of AI in Software Engineering: Synthetic Knowledge Synthesis of Recent Research Literature

Kokol

2024

Preprint

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Artificial intelligence (AI) has witnessed an exponential increase in its use in various applications. Recently, the academic community started to research and inject new AI-based approaches to provide solutions to traditional software engineering problems. However, a comprehensive and holistic understanding of the current status is missing. To close the above gap, synthetic knowledge synthesis was used to induce a research landscape of the contemporary research literature on the use of AI in software engineering. The synthesis resulted in 15 research categories and five themes, namely natural language processing in software engineering, use of artificial intelligence in the management of software development life cycle, use of machine learning in fault/defect prediction and effort estimation, employment of deep learning in intelligent software engineering and code management, and mining software repositories to improve software quality. The most productive country was China (n=2042), followed by the United States (n=1193), India (n=934), Germany (n=445), and Canada (n=381). A high percentage (n=47.4%) of papers were funded, showing a strong interest in this research topic. The convergence of AI and software engineering can significantly reduce needed resources, improve quality, increase user experience, and improve the well-being of software developers.

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Section: Covid-19 Influence On Software Engineeringmentioning

confidence: 99%

The Use of AI in Software Engineering: Synthetic Knowledge Synthesis of Recent Research Literature

Kokol

2024

Preprint

View full text Add to dashboard Cite

show abstract

“…GitHub and open source software as sources for mining software development data Data mining in GitHub or open source repositories has been used to create evolving project datasets for intelligent/empirical software engineering, for example, for Eclipse Modelling Framework metamodels formation, anomaly detection or identification of migration reasons [93].…”

Section: Covid-19 Influence On Software Engineeringmentioning

confidence: 99%

The Use of AI in Software Engineering: A Synthetic Knowledge Synthesis of the Recent Research Literature

Kokol

2024

Information

View full text Add to dashboard Cite

Artificial intelligence (AI) has witnessed an exponential increase in use in various applications. Recently, the academic community started to research and inject new AI-based approaches to provide solutions to traditional software-engineering problems. However, a comprehensive and holistic understanding of the current status needs to be included. To close the above gap, synthetic knowledge synthesis was used to induce the research landscape of the contemporary research literature on the use of AI in software engineering. The synthesis resulted in 15 research categories and 5 themes—namely, natural language processing in software engineering, use of artificial intelligence in the management of the software development life cycle, use of machine learning in fault/defect prediction and effort estimation, employment of deep learning in intelligent software engineering and code management, and mining software repositories to improve software quality. The most productive country was China (n = 2042), followed by the United States (n = 1193), India (n = 934), Germany (n = 445), and Canada (n = 381). A high percentage (n = 47.4%) of papers were funded, showing the strong interest in this research topic. The convergence of AI and software engineering can significantly reduce the required resources, improve the quality, enhance the user experience, and improve the well-being of software developers.

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“…Kula et al [39] revealed that affected developers are not likely to respond to a security advisory for Maven libraries, while Wang et al [63] revealed that developers need convincing and fine-grained information for the migration decision. Most recently, He et al [30] proposed a framework for quantifying dependency changes and library migrations based on version control data using Java projects.…”

Section: Background and Related Workmentioning

confidence: 99%

Giving Back: Contributions Congruent to Library Dependency Changes in a Software Ecosystem

Wattanakriengkrai

Wang

Kula

et al. 2023

IIEEE Trans. Software Eng.

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The widespread adoption of third-party libraries for contemporary software development has led to the creation of large inter-dependency networks, where sustainability issues of a single library can have widespread network effects. Maintainers of these libraries are often overworked, relying on the contributions of volunteers to sustain these libraries. To understand these contributions, in this work, we leverage socio-technical techniques to introduce and formalise dependency-contribution congruence (DC congruence) at both ecosystem and library level, i.e., to understand the degree and origins of contributions congruent to dependency changes, analyze whether they contribute to library dormancy (i.e., a lack of activity), and investigate similarities between these congruent contributions compared to typical contributions. We conduct a large-scale empirical study to measure the DC congruence for the npm ecosystem using 1.7 million issues, 970 thousand pull requests (PRs), and over 5.3 million commits belonging to 107,242 npm libraries. We find that the most congruent contributions originate from contributors who can only submit (not commit) to both a client and a library. At the project level, we find that DC congruence shares an inverse relationship with the likelihood that a library becomes dormant. Specifically, a library is less likely to become dormant if the contributions are congruent with upgrading dependencies. Finally, by comparing the source code of contributions, we find statistical differences in the file path and added lines in the source code of congruent contributions when compared to typical contributions. Our work has implications to encourage dependency contributions, especially to support library maintainers in sustaining their projects.

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A large-scale empirical study on Java library migrations: prevalence, trends, and rationales

Cited by 33 publications

References 63 publications

The Use of AI in Software Engineering: Synthetic Knowledge Synthesis of Recent Research Literature

The Use of AI in Software Engineering: Synthetic Knowledge Synthesis of Recent Research Literature

The Use of AI in Software Engineering: A Synthetic Knowledge Synthesis of the Recent Research Literature

Giving Back: Contributions Congruent to Library Dependency Changes in a Software Ecosystem

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