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The future of API analytics

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Abstract

Reusing APIs can greatly expedite the software development process and reduce programming effort. To learn how to use APIs, developers often rely on API learning resources (such as API references and tutorials) that contain rich and valuable API knowledge. In recent years, numerous API analytic approaches have been presented to help developers mine API knowledge from API learning resources. While these approaches have shown promising results in various tasks, there are many opportunities in this area. In this paper, we discuss several possible future works on API analytics.

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Acknowledgements

We would like to thank anonymous reviewers for their insightful and constructive comments. This research was partially funded by the National Natural Science Foundation of China under Grant No. 62172235, Primary Research & Development Plan of Jiangsu Province under Grant Nos. BE2023025 and BE2023025-1, National Natural Science Foundation of China under Grant No. 62172209, and the Natural Science Research Project of Jiangsu Higher Education Institutions under Grant No. 22KJB520026.

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Authors and Affiliations

  1. School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, China

    Di Wu

  2. School of Big Data and Software Engineering, Chongqing University, Chongqing, China

    Hongyu Zhang

  3. The State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China

    Yang Feng

  4. School of Computer Science, Nanjing University of Posts and Telecommunications, Nanjing, China

    Zhenjiang Dong & Ying Sun

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  1. Di Wu
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  2. Hongyu Zhang
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  3. Yang Feng
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  4. Zhenjiang Dong
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  5. Ying Sun
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Di Wu and Hongyu Zhang wrote the main manuscript text. All authors reviewed the manuscript.

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Correspondence to Zhenjiang Dong.

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Wu, D., Zhang, H., Feng, Y. et al. The future of API analytics. Autom Softw Eng 31, 50 (2024). https://doi.org/10.1007/s10515-024-00442-z

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