## 4 Application and Results
### Phase 5-Discovering Similarities of the Methodologies
* **Cluster 12:** Cluster 12 is composed of 3 methodologies that consider three to four steps, all ending on ExpUse. Two have just before considered MathPhy and ConcPhy. * **Cluster 13:** Cluster 13 has 3 two-step methodologies that all end on MathUser. Two of the three start on ConcUser, while the last one starts on the conceptual model of the process domain (ConcProc)
* **Cluster 14:** Cluster 14 is composed of only one methodology. It is the longest with 17 steps and highly iterative, and it has already been identified in the previous phase. * **Cluster 15:** The last cluster is formed of 3 methodologies that all consider ConcPhys while being no more than two steps long. Several emerging patterns resulting from cluster analysis and data processing are the following:  
* **Clusters with one-step methodologies:** The clusters n\({}^{\circ}\)1, 3, 5, and 9 are part of this first family. The research articles present in those methodologies do not propose a true methodology, since they focus only on one part of the design work. The high number of methodologies could be explained by the fact that the algorithm has tried to group together methodologies that were heavily focused on one model of the engineering design meta-model: the 1 st cluster revolves around the conceptual domain of the user model (ConCUser), the 3 rd cluster is focused on the experimental model of the user domain (ExpeUser), the 5 th cluster is interested in the conceptual model of the functional domain (ConFunc), and the 9 th cluster is composed only of one-step methodologies that consider the mathematical model of the physical domain (MathPhys). * **Clusters with two to five steps:** The 4 th, 6 th, 12 th, 13 th, and 15 th clusters are part of the second family. This family of clusters shows similarities to existing methodologies;  
Figure 6: Representation of the 15 clusters using a multilayer representation. for example, the 4 th cluster is similar to the UCD methodologies: the methodologies developed in this cluster start by learning about the users but also working on the specifications the end product should have. Finally, a product is developed and is tested. The 6 th cluster is more likely to represent one sprint in the context of a SCRUM framework [40]; this small part of a project allows the final product to be more suited to the command instead of basing the whole process on one version of the product. The 15 th cluster is similar because the methodologies found in this cluster propose a user interface without testing it. These small iterations can also be found in the 13 th cluster, although it is more oriented toward MathUser. The 12 th cluster, however, was more likely to experiment with the end users instead of testing a product. * **Clusters with only one methodology:** These clusters form the third family. The clusters with only one methodology (the 7 th, 11 th, and 14 th clusters detailed in Section 3.6 are populated with long methodologies that show specific approaches while retaining aspects of UCD methodologies: the users are usually a focus of interest at the start, and an experiment is conducted at the end of the methodology. These methodologies being conducted in different contexts, and requiring a different number and types of iterations, are in the end very different, which is why the algorithm has ranked them into different clusters. The 2 nd cluster is of similar shape, but of medium length, which has allowed us to group together two similar methodologies. * **Exceptions or original methodologies:** The 8 th and 10 th clusters are methodologies that are exceptions, in the sense that they are mainly focused on the conceptual model without testing the solution proposed. In this sense, they hardly follow an existing methodology. * **Identification of single-step methodologies**: 75.8% (132 of 174) of the methodologies are single-step methodologies. These articles include interventions in a general topic such as a mode of interaction or a specific study of digital adoptions in certain regions.