## 2 Literature
### Meta Review and Evolution  
The research questions RQ2 and RQ3 are addressed within this section. The meta-review provides a collective overview of process model measurement over the years and summarises the vast amount of metrics using a taxonomy. The practical part of RQ3 is extended into an experiment in Section 3. Early approaches for process model evaluation were solely based on software engineering techniques. However, standalone tools and software (e.g., ProFIT [57], PM4 PY [58] etc), are replacing these techniques. The current generation of metrics is established on the three basic attributes. In our work, we have focused on the quality dimensions of **understandability**, **complexity** and **interpretability**[59; 60; 61; 62]. We believe these qualities provide a balanced outlook on human assessment of the models. _The level of easiness in perceiving a model is called understandability. The amount of detail shown via the process model from the event log is called complexity. A combination of both complexity and understandability is termed as interpretability_[63; 64]. When trying to evaluate models, it seemed as though there was a non-stop supply of research works aimed at process model evaluation and quality analysis. Hence, a clear representation of viable metrics for process modelling is required. Even after obtaining an understanding and overview of the various metrics present in the community, there remains a small gap. Implementation and demonstration, it follows through by providing results to the community, which will further aid researchers in shaping the evaluatory phase of process modelling. We have covered the demo of our selected metrics in Section 3. The meta-review aims to answer the follow-up questions from RQ1 and create a taxonomy of metrics. Our search approach for the meta-review was rather unique. The results from our broad spectrum review were taken forward and used to create a search procedure that is more efficient than manual searches. The meta-review is a _review of reviews_. The goal is to create a taxonomy of all the metrics proposed within the field of process modelling. The taxonomy can be considered a crucial element for researchers who aim to work in conformance checking and evaluation of models, as it provides an explicit representation of the various metrics present. To create this taxonomy, literature reviews published through the years that summarise the most sought-after metrics were used as critical sources. The taxonomy is included in Appendix C. It lists all the metrics proposed between 1997 and 2023. An individual study of metrics was not performed, since it is tedious and might leave us with a bulk of information with broad relevance. Other issues such as metrics with different names but the same working principle, metrics with very distinct methods of evaluation (i.e., using non-universal features that might not be available in all datasets) and metrics with lengthy calculations or unverifiable performance were considered as possible instances that would exponentially increase the time and energy required to perform a study. Hence, review articles were selected as the source of metrics. As most review works explicitly mention the source of metrics, it makes them efficient sources to analyse. A motto was kept in mind when creating the meta-review, _\"i.e., to make sure that the proposed information will be useful to the community and not be an additional study weight\"_. **Search Procedure:** The literature search for the meta-review was far-reaching and compact. As our strategy was to use review articles, we were able to minimise the depth of each search term in exchange for a wider array of topics. This, in turn, allowed us to precisely find review articles that are in the sphere of process model assessment and not singular works. Similar to the broad spectrum review, we considered the risk of bias factor when creating the keyword search strategy; this resulted in an increased number of search terms.