## 2 Literature
### What Are the Methods to Evaluate a Process Model?
Evaluation, metrics and quality dimension are a few terms used to showcase the variation in features of a process model. To obtain a clear understanding of the definition of a metric we looked towards the ISO org [43], which says that a metric is a quantifiable measure used to assess the performance of an object relative to a scale. In process modelling, process graphs are the main objects of measurement generated from  
Figure 1: Selection procedure for broad-spectrum study. the data. Likewise, we should aim to evaluate the model and not the event log. It was determined that any generated model has to satisfy a specific set of requirements and criteria to classify as fit-for-purpose. A model can be considered of high quality only when it is fit-for-purpose. Utilising global characteristics from the event log and the process graphs yields insight into the model's viability for purpose [44; 45; 46; 47]. Additionally, quality dimensions can be used to measure traits of the model. These dimensions are differentiated based on their constituting attributes from the process model and the resulting quality shown as in the CPMQF framework [48]. **Query 2:**_Perceiving methods and approaches to evaluate a process model._ The query is answered by splitting the analysis into two major categories. _Syntax-based evaluation_: This category involves using attributes of the process model that are directly extractable and do not require additional features for calculation (e.g., lines of code, number of nodes, number of elements, number of connections, etc.) _Characteristics-based evaluation_: These are defined terminologies that exhibit behaviour extracted from the process model (e.g., understandability, simplicity, modifiability, comparability, complexity etc.) **Query 3:**_Scrutinising criterion to qualify as a metric._ This query elaborates the conditions for a dimension to be termed a metric. To understand how metrics were established and accepted, we have turned towards works that certified and created criteria for researchers to propose their evaluatory metrics. It involved articles including [29; 30; 31; 32], where there are specific conditions that a metric has to satisfy to qualify as a quality measure. The ideal information for query 3 is present in frameworks, guidelines and standards. The following are five of the most widely used guidelines for process modelling metrics:  
1. _Guidelines for business process modelling (2000) (GoM)_[49]: This is one of the first foundational guidelines and frameworks developed to create an approach to measure the qualities of process models;
2. _The 7 PMG (2010)_[30]: A revised and pinpointed version of conditions that a quality dimension or a measure should aim to fulfill in order to generate a process model of good quality;
3. _Pragmatic guidelines for business process modelling (2014)_[29]: A detailed approach to understand the logical and model generation part of quality definition;
4. _Quality assessment strategy (2017)_[50]: A quality assessment strategy proposed to create evaluation criteria to assess new models;
5. _Process modelling guidelines (2018)_[31]: This is a systematic literature review and experiment showcasing the various metrics, summarised using an internal relevance. Other frameworks and regulations mentioned along with these works are CPMQF [48], SEQUAL [51; 52], CMQF [53], GoM [49], SIQ [54], BPMQ [55] Frameworks and the ISO standard (ISO 25010:2011) [43]. Overall, from the broad spectrum study, it was found that process models are evaluated based on particular attributes. These attributes vary between the syntax features of process models and properties of the event log itself. According to the search, the ideal way to evaluate a process model is to perform calculations between the model and its respective event log. These calculations are founded upon the _Basic Three_ features (i.e., _Unique ID, Activity and Time Stamp_) [56].