CAPIRS: COVID-19-Based Application Programming Interface Recommendation System for the Developers

Muhammad Sajid Nawaz, Saif Ur Rehman Khan (), Bashir Ahmad (), Javed Iqbal () and Inayat-ur-Rehman ()
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Muhammad Sajid Nawaz: Department of Computer Science, COMSATS University Islamabad (CUI), Islamabad, Pakistan
Saif Ur Rehman Khan: Department of Computer Science, COMSATS University Islamabad (CUI), Islamabad, Pakistan
Bashir Ahmad: Department of Computer Science, Qurtuba University, Dera Ismail Khan, Pakistan
Javed Iqbal: Department of Computer Science, COMSATS University Islamabad (CUI), Islamabad, Pakistan
Inayat-ur-Rehman: Department of Computer Science, COMSATS University Islamabad (CUI), Islamabad, Pakistan

Journal of Information & Knowledge Management (JIKM), 2022, vol. 21, issue Supp01, 1-30

Abstract: Context: From the past few years, Application Programming Interface (API) is widely used for mobile- and web-based application developments. Software developers can integrate third-party services into their projects to achieve their development goals efficiently using APIs; however, with the rapid increase in the number of APIs, the manual selection of Mashup-oriented API is becoming more difficult for the developer. Objective: In the COVID-19 pandemic, everyone wants an update about the latest Standard Operating Procedures (SOPs) and the latest information on COVID-19. Additionally, a software developer wants to develop an application that provides the SOPs and latest information of COVID-19; a developer can add these functionalities into an application using COVID-19-based APIs. Moreover, the current work aims at proposing a COVID-19-based API recommendation system for the developers. Method: In this study, we propose a COVID-19-based API recommendation system for developers. The recommendation system takes a developer query as input and recommends top-3 APIs and supported features, which help the developer during software development. Furthermore, the proposed COVID-19-based API recommendation system ensures the maximum participation of the developers by validating the recommended APIs and recommendation system from the expert developers using research questionnaires. Results: Additionally, the proposed COVID-19-based API recommendation system’s output is validated by expert developers and evaluated on 120 expert developers’ queries. In addition, experiment results show that single value decomposition achieves better prediction. Conclusion: We conclude that it is significantly important to recommend APIs along with supported features to the developer for project development, and future work is needed to take more developer’s queries also to build Integrated Development Environment for the developers.

Keywords: Application Programming Interface; COVID-19; recommendation system; machine learning; expert developers (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1142/S0219649222400044

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