## 2 Related Work
### Complexity  
From the point of view of complexity, [PERSON] et al. describe the complexity metrics that can be found in the specialty literature in the last five years and study how a process can be maintained at a lower complexity to be able to keep it as simple as possible [18]. The authors describe the business process modeling languages that are usually used by different organizations to be competitive, such as the business process execution language, showing the reason behind the business transaction. [PERSON] et al. state that metrics can give us a view of the ability of the software to work properly and identify the level of success or failure. The first is the Cardoso metrics, such as the control flow complexity, which is similar to the cyclomatic complexity, but with differentiated semantics of nodes. Then, there is the interface complexity, which is based on incoming and outgoing data flows. Another one is the Vaderfeesten metric (cross-connectivity metric) based on cognitive complexity; this type of metric is used for error prediction. The idea behind this metric is that, if a process model has high cross connectivity, it is not vulnerable to a high number of errors. [PERSON] et al. propose a new formula that calculates the complexity of a business process model [7]. The Yaqin metric is a sum of other complexity metrics, based on AND, OR, XOR branch complexities, cyclic complexity, depth complexity, etc. The authors applied this formula to different business processes and conducted various experiments to validate it and find its effectiveness. The Yaqin formula returns a higher value if the model is more complex. As a result, the authors state that the complexity metric increases based on the number of elements of the business process. Based on the result, they conclude that this metric is proved to be more sensitive and precise due to the multitude of parameters involved. A classical metric that is also relevant to our study is cyclomatic complexity, which is widely used by software developers. However, [PERSON] notices the insensitiveness of the metric with linear sequences of statements [6] and, as a result, cyclomatic complexity has the value 1 for a linear sequence of any length. Another problem regarding this metric is the inconsistency when used for modularized software; no other aspects of modularity are considered but the addition of extra modules and duplicate code. [PERSON] uses the equations of the cyclomatic complexity and applies them to different flow graphs obtained from simple programs' source code to calculate their complexity [19]. The intention is to navigate all the parts of the program at least one time during the execution of the test. The conclusion is that the absence of cohesion implies a high level of complexity. [PERSON] et al. describe similarity metrics that find node matching by comparing labels and attributes of the process, structural similarity, and behavior similarity [20]. These metrics are used by companies that have repositories of more than five hundred process models. The authors identify the need for a search technique that can check if a new model is similar to the ones that are already present in the repositories. They also make the difference between syntactic and structural similarities alongside a practical example. [PERSON] et al. also review existing methods for measuring complexity [21]. The complexity of a process determines the probability of an error, so there is a clear need for a quantitative indication of program complexity. This is similar for software and for a business process, as the latter is the enablement of the former. An aspect that also matters is the semantics, which may be different from one process graph to another. [PERSON] et al. state that such metrics have advantages such as not requiring rigorous analysis of the process, identifying errors, and reducing the effort to maintain the process. There is also scientific literature in regard to the assignment of weights to a task for businesses process computation.