  Model composition plays a central role in many software engineering
activities such as evolving models to add new features and reconciling
conflicting design models developed in parallel by different development teams.
As model composition is usually an error-prone and effort-consuming task, its
potential benefits, such as gains in productivity can be compromised. However,
there is no empirical knowledge nowadays about the effort required to compose
design models. Only feedbacks of model composition evangelists are available,
and they often diverge. Consequently, developers are unable to conduct any
cost-effectiveness analysis as well as identify, predict, or reduce composition
effort. The inability of evaluating composition effort is due to three key
problems. First, the current evaluation frameworks do not consider fundamental
concepts in model composition such as conflicts and inconsistencies. Second,
researchers and developers do not know what factors can influence the
composition effort in practice. Third, practical knowledge about how such
influential factors may affect the developers' effort is severely lacking. In
this context, the contributions of this thesis are threefold: (i) a quality
model for supporting the evaluation of model composition effort, (ii) practical
knowledge, derived from a family of quantitative and qualitative empirical
studies, about model composition effort and its influential factors, and (iii)
insight about how to evaluate model composition efforts and tame the side
effects of such influential factors.
