azure / gpt-rag-orchestrator - Conditional Complexity

Intro

Conditional complexity (also called cyclomatic complexity) is a term used to measure the complexity of software. The term refers to the number of possible paths through a program function. A higher value ofter means higher maintenance and testing costs (infosecinstitute.com).
Conditional complexity is calculated by counting all conditions in the program that can affect the execution path (e.g. if statement, loops, switches, and/or operators, try and catch blocks...).
Conditional complexity is measured at the unit level (methods, functions...).
Units are classified in four categories based on the measured McCabe index: 1-5 (simple units), 6-10 (medium complex units), 11-25 (complex units), 26+ (very complex units).

Conditional Complexity Overall

Legend:

51+

26-50

11-25

6-10

1-5

Alternative Visuals

Conditional Complexity per Extension

51+

26-50

11-25

6-10

1-5

Conditional Complexity per Logical Component

primary logical decomposition

51+

26-50

11-25

6-10

1-5

Most Complex Units

Top 15 most complex units

Unit	# lines	McCabe index	# params
def get_chat_history_as_messages() in shared/util.py	20	14	4
def get_usage_tokens() in shared/util.py	10	10	2
def get_chat_history_as_text() in shared/util.py	9	5	3
def get_last_messages() in shared/util.py	6	5	2
def format_answer() in shared/util.py	10	4	2
def generate_security_ids() in orc/orchestrator.py	6	3	1
def truncate_to_max_tokens() in shared/util.py	7	3	3
def get_message() in shared/util.py	11	3	1
def optmize_messages() in shared/util.py	12	2	2
def replace_doc_ids_with_filepath() in shared/util.py	5	2	2
def escape_xml_characters() in shared/util.py	11	2	1
def get_list_from_string() in shared/util.py	4	2	1
def get_possitive_int_or_default() in shared/util.py	8	2	2
def number_of_tokens() in shared/util.py	5	1	2
def load_sk_plugin() in shared/util.py	7	1	2