A situational approach for the definition and tailoring of a data-driven software evolution method

Autor: Anna Perini, Jolita Ralyté, Alberto Abelló, Angelo Susi, Marc Oriol, Alberto Siena, David Ameller, Xavier Franch, Jesus Gorronogoitia, Sergi Nadal, Norbert Seyff
Přispěvatelé: Universitat Politècnica de Catalunya. Departament d'Enginyeria de Serveis i Sistemes d'Informació, Universitat Politècnica de Catalunya. inSSIDE - integrated Software, Service, Information and Data Engineering
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Zdroj: UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
Recercat. Dipósit de la Recerca de Catalunya
instname
Advanced Information Systems Engineering ISBN: 9783319915623
CAiSE
DOI: 10.1007/978-3-319-91563-0_37
Popis: Successful software evolution heavily depends on the selection of the right features to be included in the next release. Such selection is difficult, and companies often report bad experiences about user acceptance. To overcome this challenge, there is an increasing number of approaches that propose intensive use of data to drive evolution. This trend has motivated the SUPERSEDE method, which proposes the collection and analysis of user feedback and monitoring data as the baseline to elicit and prioritize requirements, which are then used to plan the next release. However, every company may be interested in tailoring this method depending on factors like project size, scope, etc. In order to provide a systematic approach, we propose the use of Situational Method Engineering to describe SUPERSEDE and guide its tailoring to a particular context.
Databáze: OpenAIRE