aws-samples / detecting-data-drift-in-nlp-using-amazon-sagemaker-custom-model-monitor
Conditional Complexity

The distribution of complexity of units (measured with McCabe index).

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 10 units with 250 lines of code in units (63.0% of code).
    • 0 very complex units (0 lines of code)
    • 0 complex units (0 lines of code)
    • 1 medium complex units (84 lines of code)
    • 3 simple units (77 lines of code)
    • 6 very simple units (89 lines of code)
0% | 0% | 33% | 30% | 35%
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
py0% | 0% | 33% | 30% | 35%
Conditional Complexity per Logical Component
primary logical decomposition
51+
26-50
11-25
6-10
1-5
code0% | 0% | 41% | 38% | 19%
docker0% | 0% | 0% | 0% | 100%
Most Complex Units
Top 10 most complex units
Unit# linesMcCabe index# params
def train()
in code/train_deploy.py
 84 15 1
def input_fn()
in code/train_deploy.py
 23 10 2
def _get_train_data_loader()
in code/train_deploy.py
 29 7 3
def _get_test_data_loader()
in code/train_deploy.py
 25 6 2
def test()
in code/train_deploy.py
 15 2 3
def model_fn()
in code/train_deploy.py
 7 2 1
def predict_fn()
in code/train_deploy.py
 14 2 2
def get_environment()
in docker/evaluation.py
 41 2 0
def flat_accuracy()
in code/train_deploy.py
 4 1 2
def download_embeddings_file()
in docker/evaluation.py
 8 1 0