understandBPMN1.1.1 package

Calculator of Understandability Metrics for BPMN

cognitive_weight

Cognitive weights

connectivity_level_between_pools

The connectivity level between pools

connector_heterogeneity

Connector heterogeneity

connector_mismatch

Connector mismatch

control_flow_complexity

Control flow complexity

coupling_metric

Coupling metric

create_internal_doc

A function for creating internal documents

cyclicity

Cyclicity

create_path_and_repetition_log

Path and repetition log

cross_connectivity

Cross Connectivity

activity_multiple_times_executed

activity sometimes multiple times executed

activity_names_repetitions

activity names repetitions

avg_connector_degree

Average connector degree

calculate_metrics

A calculation function for all metrics

coefficient_network_connectivity

Coefficient of network connectivity

cyclomatic_metric

Cyclomatic metric of McCabe

density_process_model

Density

depth

Depth

diameter

Diameter

direct_parallel_relations

Direct and parallel relations

filtered_path_log_parallel

Filter path log with only traces containing the parallel gateway toget...

max_connector_degree

Maximum connector degree

n_data_objects

Data Objects

n_duplicate_tasks

Duplicate tasks

n_empty_sequence_flows

Empty sequence flows

n_message_flows

Number of message flows

n_pools

Number of pools

n_swimlanes

Number of swimlanes

separability

Separability

sequentiality

Sequentiality

size_process_model

Size

some_traces_without_activity

activity sometimes not in traces

structuredness

Structuredness

task_names

Task names

token_split

Token Split

traces_contain_relation

Relation in traces

understandBPMN

understandBPMN - understandability metrics for BPMN models

Calculate several understandability metrics of BPMN models. BPMN stands for business process modelling notation and is a language for expressing business processes into business process diagrams. Examples of these understandability metrics are: average connector degree, maximum connector degree, sequentiality, cyclicity, diameter, depth, token split, control flow complexity, connector mismatch, connector heterogeneity, separability, structuredness and cross connectivity. See R documentation and paper on metric implementation included in this package for more information concerning the metrics.

  • Maintainer: Gert Janssenswillen
  • License: MIT + file LICENSE
  • Last published: 2019-09-27