A Data-driven approach to improve the process of data-intensive API creation and evolution

Abelló Gamazo, Alberto; Ayala Martínez, Claudia Patricia; Farré Tost, Carles; Gómez Seoane, Cristina; Oriol Hilari, Marc; Romero Moral, Óscar

View/Open

CAiSE2017_Forum_Paper1.pdf (1,314Mb)

View Usage Statistics

Cita com:

Show full item record

Abelló Gamazo, Alberto

Ayala Martínez, Claudia Patricia

Farré Tost, Carles

Gómez Seoane, Cristina

Oriol Hilari, Marc

Romero Moral, Óscar

Document typeConference report

Defense date2017

PublisherCEUR-WS.org

Rights accessOpen Access

Abstract

The market of data-intensive Application Programming Interfaces (APIs) has recently experienced an exponential growth, but the creation and evolution of such APIs is still done ad-hoc, with little automated support and reported deficiencies. These drawbacks hinder the productivity of developers of those APIs and the services built on top of them. In this exploratory paper, we promote a data-driven approach to improve the automatization of data-intensive API creation and evolution. In a release cycle, data coming from API usage and developers will be gathered to compute several indicators whose analysis will guide the planning of the next release. This data will also help to generate complete documentation facilitating APIs adoption by third parties.

CitationAbelló, A., Ayala, C.P., Farré, C., Gómez, C., Oriol, M., Romero, O. A Data-driven approach to improve the process of data-intensive API creation and evolution. A: International Conference on Advanced Information Systems Engineering. "CAiSE-Forum-DC 2017: CAiSE 2017 Forum and Doctoral Consortium Papers: proceedings of the Forum and Doctoral Consortium Papers Presented at the 29th International Conference on Advanced Information Systems Engineering (CAiSE 2017): Essen, Germany, June 12-16, 2017". Essen: CEUR-WS.org, 2017, p. 1-8.

URIhttp://hdl.handle.net/2117/113036

ISBN1613-0073

Publisher versionhttp://ceur-ws.org/Vol-1848/CAiSE2017_Forum_Paper1.pdf

Collections

View Usage Statistics

Show full item record

Files	Description	Size	Format	View
CAiSE2017_Forum_Paper1.pdf		1,314Mb	PDF	View/Open

All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder

UPCommons. Global access to UPC knowledge

A Data-driven approach to improve the process of data-intensive API creation and evolution

View/Open

Browse