## 5 Case Study of Applying the Proposed Scope Estimation Methodology
On the other hand, nouns depend mostly on the domain of the product and can differ significantly between the projects, thus leading to the occurrence of a larger number of noun synonyms not carrying a distinct meaning. Analysis of synonyms enabled identification of similar and/or overlapping Contexts. Team members aggregated contexts that had similar meaning. Before analysis, the requirements list had 44 contexts, and, after aggregation, the list contained 13 contexts. Examples of aggregated contexts are \"Search pet\" and \"Search for a pet\", \"Pet\" and \"Pet profile\", \"Add pet to system\" and \"Add pet\". After the analysis of synonyms, the identification of overlapping requirements was performed (Step S4 in Figure 2). The previously performed unification of terms enabled more accurate identification of requirement overlaps. In the OTAAT project, the Story map was chosen as the primary model. The grouping of requirements was carried out by Actor, also filtering the requirements by Context. During the overlap identification step, 11 requirements from Story Map model, 14 requirements from Use case models, 1 from  
Figure 12: Examples of UML Activity models for OTAAT project prepared during the requirements workshop. Class model, and 16 requirements from Activity models (in total 42 requirements) were identified as overlapping and were removed. For example, the requirements \"Manager can Review adopters in Application context\" (from the Use case model), \"Manager can Review applications in Application context\" (from another Use case model), and \"Manager can Review adopters information in Application context\" (from the Activity model) were identified as overlapping, and after team discussion, the last one of these requirements was selected as suitable and the other two were removed. In another example, the requirements \"Adopter can Schedule a meeting in Pet profile context\" (from Story map) and \"Adopter can Request a meeting in the shelter in Pet profile context\" (from the Activity model) were identified as overlapping, and the second one was removed as duplicate. \begin{table}
\begin{tabular}{c c c} \hline \hline  & \multicolumn{2}{c}{**Number of Models Prepared**} \\
**Source Model Type** & **by Team and Used** & **Number of Requirements** \\  & **in Transformation** & **Transformed from the Source** \\ \hline Story map & 1 & 47 \\ \hline UML Use case & 3 & 22 \\ \hline UML Class & 1 & 6 \\ \hline UML Activity & 9 & 58 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Numbers of requirements extracted from various source models. Figure 13: Using the estimation tool in the OTAAT project to import information from source models. The final list of requirements contained 91 requirements, of which 36 were transformed from the Story map, 8 were gathered from Use case models, 5 came from the Class model, and 42 were gathered from Activity models. Detailed results of the requirement transformation from different sources and reconciliation are presented in Table 3.  
The next and final step was the scope estimation (Step S5 in Figure 2). During this step, the whole team worked together, discussing each requirement. The requirement was given a level of clarity and an estimate of story points. The fragment of the requirements list with the provided estimates is visible in the screenshot of the scope estimation tool usage during the estimation step (Figure 14). The distribution of requirements according to the level of clarity and the number of story points is presented in Figure 15. The highest number of requirements is seen in the 3-5-8 story point categories and clarity levels 1 and 2, with a total of 61, which indicates a satisfactory status of requirements elicitation. The requirements are manageable, meaning not too large in story points, and a more detailed analysis is not required for most of the requirements.