APIUaaS: a reference architecture for facilitating API usage from a data analytics perspective. Issue 5 (1st October 2019)

• Record Type: Journal Article
• Authors: Zhao, Jitong; Liu, Yan
• Is Part Of: IET software. Volume 13:Issue 5(2019)
• Page Start: 466
• Page End: 478
• Publication Date: 2019-10-01
• Subjects: data analysis -- data mining -- application program interfaces -- source code (software) -- recommender systems -- cloud computing -- pattern clustering -- software architecture; reference architecture -- data analytics perspective -- source code examples -- software developers -- application programming interfaces -- multiple sources -- source code mining -- recommendation systems -- APIUaaS -- semiautomatic data analytics -- global-level architectural concerns -- API queries -- data sources layer -- API elements -- data model & code assets layer -- ranking algorithms -- API usage services layer -- usage patterns -- API usage as a service -- API code examples -- code example candidates -- recommendation phase -- API usages mining -- clustering algorithm -- ranking algorithm -- knowledge discover & intelligent model layer; Computer software -- Periodicals; Software engineering -- Periodicals; 005.1
• DOI: 10.1049/iet-sen.2018.5355
• Languages: English
• ISSNs: 1751-8806

Abstract

Abstract : Source code examples are key resources for software developers to learn application programming interfaces (APIs) and to understand corresponding usage patterns. Developers usually have to utilise, evaluate and understand code examples from multiple sources, which involve heavy manually processing efforts. To reduce such efforts, there has been growing interest in developing source code mining and recommendation systems. This study proposes API usage as a service (APIUaaS), a reference architecture for facilitating API usage, which allows infrastructures to be built for recommending proper API code examples based on semi‐automatic data analytics. This reference architecture contains five logical layers and six global‐level architectural concerns. API queries are accepted from programmers, and corresponding code example candidates are extracted from the data sources layer. The detailed structural links between API elements and source codes are captured and stored in the data model & code assets layer. During the recommendation phase, API usages mining, clustering and ranking algorithms are enabled in the knowledge discover & intelligent model layer. Services such as code assist and bug detection are assembled in the API usage services layer. Finally, the authors evaluate APIUaaS from three perspectives: rationality, feasibility, and usability.