The GRADE decision canvas for classification and reflection on architecture decisionsShow others and affiliations
2017 (English)In: ENASE 2017 - Proceedings of the 12th International Conference on Evaluation of Novel Approaches to Software Engineering, SciTePress , 2017, p. 187-194Conference paper, Published paper (Refereed)
Abstract [en]
This paper introduces a decision canvas for capturing architecture decisions in software and systems engineering. The canvas leverages a dedicated taxonomy, denoted GRADE, meant for establishing the basics of the vocabulary for assessing and choosing architectural assets in the development of software-intensive systems. The canvas serves as a template for practitioners to discuss and document architecture decisions, i.e., capture, understand and communicate decisions among decision-makers and to others. It also serves as a way to reflect on past decision-making activities devoted to both tentative and concluding decisions in the development of software-intensive systems. The canvas has been assessed by means of preliminary internal and external evaluations with four scenarios. The results are promising as the canvas fulfills its intended objectives while satisfying most of the needs of the subjects participating in the evaluation. © 2017 by SCITEPRESS - Science and Technology Publications, Lda. All Rights Reserved.
Place, publisher, year, edition, pages
SciTePress , 2017. p. 187-194
Keywords [en]
Architecture knowledge, Decision canvas, Decision documentation, Decision template, Software engineering, Decision making, Software architecture, Architecture decisions, Decision makers, Document architecture, Software and systems engineerings, Software intensive systems, Software design
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:bth-15051DOI: 10.5220/0006301301870194ISI: 000700313100017Scopus ID: 2-s2.0-85025451151ISBN: 9789897582509 (print)OAI: oai:DiVA.org:bth-15051DiVA, id: diva2:1135013
Conference
12th International Conference on Evaluation of Novel Approaches to Software Engineering, ENASE, Porto
Projects
ORION project
Funder
Knowledge Foundation, 201402182017-08-222017-08-222022-11-30Bibliographically approved