aliyun / cflue - 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).

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Conditional Complexity Overall

There are 41 units with 910 lines of code in units (94.8% of code).

0 very complex units (0 lines of code)
2 complex units (240 lines of code)
4 medium complex units (198 lines of code)
5 simple units (140 lines of code)
30 very simple units (332 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 41 most complex units

Unit	# lines	McCabe index	# params
def industry_classification_result_process() in utils/compute_score.py	129	36	1
def industry_classification_result_process_single() in utils/compute_score.py	111	34	1
def compute_text_classification() in utils/compute_score.py	46	20	1
def compute_extraction() in utils/compute_score.py	66	18	1
def eval_ability() in exec_knowledge_eval.py	58	14	1
def decode_re_content() in utils/compute_score.py	28	11	1
def financial_extract_result_process() in utils/compute_score.py	29	9	1
def financial_extract_result_process_single() in utils/compute_score.py	27	8	1
def industry_classification_result_process1() in utils/compute_score.py	17	7	1
def compute_text_generation() in utils/compute_score.py	35	6	1
def compute_finqa() in utils/compute_score.py	32	6	1
def get_num_infos() in utils/compute_score.py	12	4	2
def cal_f1() in utils/compute_score.py	11	4	2
def eval_application() in exec_application_eval.py	21	4	1
def compute_nmt_zh2en() in utils/compute_score.py	25	3	2
def compute_nmt_en2zh() in utils/compute_score.py	25	3	2
def extract_re_expr() in utils/compute_score.py	10	3	3
def extract_re_exprs() in utils/compute_score.py	7	3	3
def process_industry_classification_output() in utils/compute_score.py	9	3	1
def main() in utils/compute_score.py	60	3	2
def load_dataset() in utils/dataset.py	7	3	1
def extract_multi_choice() in utils/extract_choice.py	15	3	2
def pad_list() in utils/compute_score.py	7	2	4
def output_adj() in utils/compute_score.py	5	2	1
def cal_financial_extract_score() in utils/compute_score.py	9	2	1
def format_one_example() in utils/format_example.py	7	2	1
def format_multi_example() in utils/format_example.py	7	2	1
def load_models_tokenizer() in evaluator/evaluator.py	12	1	1
def load_llama_models_tokenizer() in evaluator/evaluator.py	8	1	1
def tokenizer_en() in utils/compute_score.py	2	1	1
def acc_score() in utils/compute_score.py	4	1	2
def f1_score() in utils/compute_score.py	4	1	2
def bleu_score() in utils/compute_score.py	8	1	2
def bert_score() in utils/compute_score.py	4	1	2
def rouge_score() in utils/compute_score.py	9	1	2
def strip() in utils/compute_score.py	6	1	2
def cal_industry_classification_score() in utils/compute_score.py	9	1	1
def load_knowledge() in utils/dataset.py	3	1	0
def load_application() in utils/dataset.py	3	1	0
def extract_one_choice() in utils/extract_choice.py	2	1	2
def get_application_score() in exec_application_eval.py	21	1	1