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(SCC 2020) An Empirical Study of Web API Quality Formulation

About This Webinar

Abstract: This paper presents an empirical study on one of the popular web API repositories, www.programmableweb.com. The study is to ascertain the impact of the structure and formulation of external web API quality factors on the overall web API quality. The study is based on the hypothesis that, in such a multi-factor quality measurement, the structure and formulation of the quality factors can make a substantial difference in its quantification. Specifically, we employ statistical tools such as exploratory factor analysis, to determine the latent factors that contributes to web API quality. We subsequently determine the loading of each latent factors to propose a new quality model for web API quality computation.

Authors: Esi Adeborna (University of Massachusetts Lowell, USA); Kenneth K Fletcher (University of Massachusetts Boston, USA)

Email: esi_adeborna@student.uml.edu, kenneth.fletcher@umb.edu

Who can view: Everyone
Webinar Price: Free
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Esi Adeborna is a second year PhD student at the University of Massachusetts, Lowell and a full-time SAP technology consultant. Her doctoral research is in Quality Models for Web APIs, Gamification of Enterprise Resource Planning Systems and Algorithmic Biases in Machine Learning. She takes a multidisciplinary approach that encompasses the fields in sentiment analysis, service personalization and social sciences. She also holds a Master of Science in Information Technology and Master of Business Administration degree.
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