apache / otava - 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).

Learn more...

Conditional Complexity Overall

There are 200 units with 2,024 lines of code in units (68.6% of code).

0 very complex units (0 lines of code)
3 complex units (351 lines of code)
9 medium complex units (409 lines of code)
17 simple units (343 lines of code)
171 very simple units (921 lines of code)

Legend:

51+

26-50

11-25

6-10

1-5

Alternative Visuals

3D view of all units

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 50 most complex units

Unit	# lines	McCabe index	# params
def script_main() in otava/main.py	184	39	2
def fetch_data() in otava/importer.py	85	36	3
def fetch_data() in otava/importer.py	82	27	3
def fetch_data() in otava/importer.py	64	23	3
def fetch_data() in otava/importer.py	59	23	3
def update_grafana_annotations() in otava/main.py	65	17	3
def load_config_from() in otava/config.py	72	16	1
def split() in otava/analysis.py	31	15	5
def create_dispatches() in otava/slack.py	33	12	1
def append() in otava/series.py	46	12	4
def data_selector_from_args() in otava/main.py	23	11	1
def _validate_append() in otava/series.py	16	11	4
def merge_dicts() in otava/util.py	18	10	2
def remove_common_prefix() in otava/util.py	12	8	2
def __dates_change_points_summary() in otava/slack.py	25	8	3
def remove_grafana_annotations() in otava/main.py	22	8	3
def validate() in otava/main.py	24	8	1
def to_json() in otava/series.py	22	8	1
def get() in otava/importer.py	15	7	2
def fill_missing() in otava/analysis.py	11	7	1
def from_json() in otava/series.py	47	7	2
def __format_log_annotated() in otava/report.py	25	7	2
def __format_regressions_only() in otava/report.py	27	7	2
def list_tests() in otava/main.py	12	6	2
def load_tests() in otava/config.py	16	6	2
def load_test_groups() in otava/config.py	16	6	3
def compare() in otava/analysis.py	14	6	3
def get_back_links() in otava/attributes.py	17	6	2
def compress_target_paths() in otava/graphite.py	20	6	1
def resolution() in otava/util.py	10	5	1
def analysis_options_from_args() in otava/main.py	11	5	1
def find_window() in otava/analysis.py	4	5	2
def get_stable_range() in otava/series.py	12	5	3
def fetch_metric_paths() in otava/graphite.py	16	5	3
def sliding_window() in otava/util.py	8	4	2
def interpolate() in otava/util.py	16	4	3
def __get_tags() in otava/importer.py	11	4	2
def fetch_all_metric_names() in otava/importer.py	7	4	2
def fetch_all_attribute_names() in otava/importer.py	7	4	2
def get_selection_description() in otava/data_selector.py	5	4	1
def get_tests() in otava/main.py	13	4	2
def load_config() in otava/config.py	13	4	0
def fetch_data() in otava/graphite.py	26	4	3
def produce_report() in otava/report.py	10	4	3
def merge_sorted() in otava/util.py	8	3	1
def insert_multiple() in otava/util.py	9	3	3
def parse_datetime() in otava/util.py	7	3	1
def delete_annotations() in otava/grafana.py	9	3	2
def create_annotations() in otava/grafana.py	11	3	2
def __init_report_dispatch() in otava/slack.py	7	3	1