Context. Software systems, becoming larger and more complex day-by-day, have resulted in software development processes to become more complex to understand and manage. Many companies have started to adapt distributed software engineering practices that would allow them to work in distributed teams at different organizations and/or geographical locations. For example, model-driven engineering methods are being used in such global software engineering projects. Among the activities in model-based software development, consistency checking is one of the widely known ones. Consistency checking is concerned with consistent models; in particular, having a consistent group of multiple models for a whole system, e.g., multiple models produced by distributed teams. Objectives. This thesis aims to find out how ‘Global Consistency Checking (GCC)’ can be utilized for exploring inconsistency problems between distributed models; particularly among UML class diagram relationships (in terms of consistency), as well as how GCC can be scaled with large number of models and relationships. Thereby, these inconsistencies are also aimed to incrementally resolve in our approach. Methods. We made a review in distributed software development domain and model management, in particular, methods of consistency checking between ‘Distributed Models (DM)’. Next, we conducted two case studies in two problem domains in order to apply our ‘consistency checking methodology’. We concurrently constructed and implemented new consistency rules, most of which are gathered from literatures and brainstorming with our coordinators. Generally, the method contains implementing different models of the case studies with a tool support and trying to figure out overlaps, merging models and checking the merged model against the consistency rules, and evaluating the results of GCC. We mainly addressed issues focused on consistency checking of individual models and the mapping between them e.g., pair-wise consistency checking (PCC), which are incapable of fully addressing problems against any consistency rules encountered in distributed environments. Results. We have identified seven types of inconsistency, which are divided in two groups named ‘Global inconsistency’ and ‘Pair-wise inconsistency’. In the first case study, we have 94 global inconsistencies and 73 pair-wise. In the second one, 14 global and 25 pair-wise inconsistencies are resulted. During ‘Resolution approach’, we followed six steps as a ‘systematic procedure’ for resolving these inconsistencies and constructed new merged model in each iteration. The initial merged model (inconsistent model) as an input for the first step has 1267 elements, and the consistent merged model (the output) from the sixth step has 686 elements. ‘time duration’ and ‘required effort’ for checking consistency against each ‘consistency rule’ were recorded, analyzed and illustrated in Sections 4.1.5 and 4.2.4. Conclusions. We concluded that GCC enables us to explore the inconsistencies, inclusive of resolving them and therefore, refining the relationships between different models, which are difficult to detect by e.g., a pair-wise method. The most important issues are: The number of model comparisons conducted by PCC, The inability of PCC for identifying some inconsistencies, Model relationships refinement and classification based on PCC approach will not lead to a final consistent DM, whereas, GCC guarantees it. Consistency rules application, inconsistency identification and resolving them could be generalized to any UML class diagram model representing a problem domain within the fields of consistency checking in software engineering.