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dc.contributor.authorKoçi, Rediana
dc.contributor.authorFranch Gutiérrez, Javier
dc.contributor.authorJovanovic, Petar
dc.contributor.authorAbelló Gamazo, Alberto
dc.contributor.otherUniversitat Politècnica de Catalunya. Doctorat en Computació
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria de Serveis i Sistemes d'Informació
dc.contributor.otherFacultat d'Informàtica de Barcelona
dc.identifier.citationKoçi, R. [et al.]. A data-driven approach to measure the usability of Web APIs. A: Euromicro Conference on Software Engineering and Advanced Applications. "46th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2020: 26-28 August 2020, Kranj, Slovenia: proceedings". Institute of Electrical and Electronics Engineers (IEEE), 2020, p. 64-71. ISBN 978-1-7281-9532-2. DOI 10.1109/SEAA51224.2020.00021.
dc.description.abstractApplication 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.
dc.description.sponsorshipThis work is supported by GENESIS project, funded by the Spanish Ministerio de Ciencia e Innovacion under project TIN2016-79269-R.
dc.format.extent8 p.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subjectÀrees temàtiques de la UPC::Informàtica::Enginyeria del software
dc.subject.lcshApplication program interfaces (Computer software)
dc.subject.lcshUser interfaces (Computer systems)
dc.subject.otherAPI usability
dc.subject.otherAPI logs
dc.subject.otherLog mining
dc.subject.otherWeb API
dc.titleA data-driven approach to measure the usability of Web APIs
dc.typeConference report
dc.subject.lemacInterfícies de programació d'aplicacions (Programari)
dc.subject.lemacInterfícies d'usuari (Informàtica)
dc.contributor.groupUniversitat Politècnica de Catalunya. inSSIDE - integrated Software, Service, Information and Data Engineering
dc.description.peerreviewedPeer Reviewed
dc.rights.accessOpen Access
dc.description.versionPostprint (author's final draft)
local.citation.authorKoçi, R.; Franch, X.; Jovanovic, P.; Abelló, A.
local.citation.contributorEuromicro Conference on Software Engineering and Advanced Applications
local.citation.publicationName46th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2020: 26-28 August 2020, Kranj, Slovenia: proceedings

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