Back to Search Start Over

Static Analysis for Improved Modularity of Procedural Web Application Programming Interfaces

Authors :
Alistair Barros
Chun Ouyang
Fuguo Wei
Source :
IEEE Access, Vol 8, Pp 128182-128199 (2020)
Publication Year :
2020
Publisher :
IEEE, 2020.

Abstract

Despite their rapid growth, the utilisation of application programming interfaces (APIs) poses challenges for companies under pressure to yield productive systems integration. APIs of larger systems tend to be large, complex and have reduced modularity and quality, which makes them cumbersome to comprehend and use. These challenges can be addressed by static API analysis that focuses on studying API code itself and deriving business entities and dependencies from operational signatures. However, existing techniques for static analysis of APIs face the challenges in deriving a sufficient coverage of business entity relationship types from implementation-oriented API operational signatures carrying limited semantic insights. The paper aims to address such problems by supporting static analysis techniques for APIs that improve their modularity. Our approach adopts an object-oriented paradigm where the concept of “object” is exemplified by the notion of business entity. It systematically applies interface analysis methods and techniques for eliciting knowledge of business entities and their attributes, for deriving the temporal order of calling operations across multiple business entities, and for learning and extracting various ways of invoking a service via APIs. The approach is implemented as an open-source tool and applied to a group of widely-deployed services in practice for validation. The research contributes to identifying key aspects of both the structure and behaviour of APIs, which will lead to building a simplified but comprehensive interface (presentation) layer to assist service users in understanding complex and overloaded interfaces as well as to facilitate efficient and effective service integration.

Details

Language :
English
ISSN :
21693536
Volume :
8
Database :
Directory of Open Access Journals
Journal :
IEEE Access
Publication Type :
Academic Journal
Accession number :
edsdoj.3e4f95e510a848c78563c0055cb01e81
Document Type :
article
Full Text :
https://doi.org/10.1109/ACCESS.2020.3008904