2026-04-13T06:57:03Zhttps://recercat.cat/oai/request

oai:recercat.cat:2117/3416292026-01-21T09:41:10Zcom_2072_1033col_2072_452950

urn:hdl:2117/341629 A data-driven approach to measure the usability of Web APIs Koçi, Rediana Franch Gutiérrez, Javier Jovanovic, Petar Abelló Gamazo, Alberto Àrees temàtiques de la UPC::Informàtica::Enginyeria del software Application program interfaces (Computer software) User interfaces (Computer systems) API usability API logs Log mining Web API Interfícies de programació d'aplicacions (Programari) Interfícies d'usuari (Informàtica) Application Programming Interfaces (APIs) are means of communication between applications, hence they can be seen as user interfaces, just with different kind of users, i.e., software or computers. However, the very first consumers of the APIs are humans, namely programmers. Based on the available documentation and the ``ease of use'' perception (sometimes led by corporate decisions and/or restrictions) they decide to use or not a specific API. In this paper, we propose a data-driven approach to measure web API usability, expressed through the predicted error rate. Following the reviewed state of the art in API usability, we identify a set of usability attributes, and for each of them we propose indicators that web API providers should refer to when developing usable web APIs. Our focus in this paper is on those indicators that can be quantified using the API logs, which indeed reflect the actual behaviour of programmers. Next, we define metrics for the aforementioned indicators, and exemplify them in our use case, applying them on the logs from the web API of District Health Information System (DHIS2) used at World Health Organization (WHO). Using these metrics as features, we build a classifier model to predict the error rate of API endpoints. Besides finding usability issues, we also drill down into the usage logs and investigate the potential causes of these errors. This work is supported by GENESIS project, funded by the Spanish Ministerio de Ciencia e Innovacion under project TIN2016-79269-R. Peer Reviewed Postprint (author's final draft) 2020 Conference report https://ieeexplore.ieee.org/abstract/document/9226284 info:eu-repo/grantAgreement/MINECO/1PE/TIN2016-79269-R Open Access Institute of Electrical and Electronics Engineers (IEEE)