To succeed with the development of modern software, organizations must have the agility to adapt faster to constantly evolving environments to deliver more reliable and optimized solutions that can be adapted to the needs and environments of their stakeholders including users, customers, business, development, and IT. However, stakeholders do not have sufficient automated support for global decision making, considering the increasing variability of the solution space, the frequent lack of explicit representation of its associated variability and decision points, and the uncertainty of the impact of decisions on stakeholders and the solution space. This leads to an ad-hoc decision making process that is slow, error-prone, and often favors local knowledge over global, organization-wide objectives. The Multi-Plane Models and Data (MP-MODA) framework explicitly represents and manages variability, impacts, and decision points. It enables automation and tool support in aid of a multi-criteria decision making process involving different stakeholders within a feedback-driven software development process where feedback cycles aim to reduce uncertainty. We present the conceptual structure of the framework, discuss its potential benefits, and enumerate key challenges related to tool supported automation and analysis within MP-MODA.

Jörg Kienzle

McGill University, Canada

Canada

Benoit Combemale

University of Rennes; Inria; IRISA

France

Gunter Mussbacher

McGill University

Canada

Omar Alam

Trent University

Canada

Francis Bordeleau

École de Technologie Supérieure (ETS)

Canada

Lola Burgueño

University of Malaga

Spain

Gregor Engels

Paderborn University

Germany

Jessie Galasso-Carbonnel

Université de Montréal

Canada

Jean-Marc Jézéquel

Univ Rennes - IRISA

France

Bettina Kemme

McGill University, Canada

Sébastien Mosser

McMaster University

Canada

Houari Sahraoui

Université de Montréal

Canada

Maximilian Schiedermeier

McGill University

Canada

Eugene Syriani

Université de Montréal

Canada