facebookresearch / BalancingGroups
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 69 units with 1,109 lines of code in units (71.8% of code).
    • 0 very complex units (0 lines of code)
    • 0 complex units (0 lines of code)
    • 1 medium complex units (45 lines of code)
    • 9 simple units (329 lines of code)
    • 59 very simple units (735 lines of code)
0% | 0% | 4% | 29% | 66%
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% | 4% | 29% | 66%
Conditional Complexity per Logical Component
primary logical decomposition
51+
26-50
11-25
6-10
1-5
ROOT0% | 0% | 4% | 29% | 66%
Most Complex Units
Top 20 most complex units
Unit# linesMcCabe index# params
45 11 3
72 10 2
def get_loaders()
in datasets.py
 41 8 5
59 8 1
def subsample_()
in datasets.py
 20 7 2
21 7 4
def __init__()
in datasets.py
 30 6 5
38 6 1
35 6 3
13 6 1
def update()
in models.py
 16 5 6
def accuracy()
in models.py
 21 5 2
def download_and_extract()
in setup_datasets.py
 16 5 3
51 5 1
def get_ploting_params()
in plot_toy_scatter.py
 29 5 1
24 4 3
def init_model_()
in models.py
 47 4 3
17 4 6
def generate_metadata_celeba()
in setup_datasets.py
 15 4 1
56 4 3