facebookresearch / Imppres
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 13 units with 124 lines of code in units (0.5% of code).
    • 0 very complex units (0 lines of code)
    • 0 complex units (0 lines of code)
    • 1 medium complex units (40 lines of code)
    • 2 simple units (26 lines of code)
    • 10 very simple units (58 lines of code)
0% | 0% | 32% | 20% | 46%
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% | 32% | 20% | 46%
Conditional Complexity per Logical Component
primary logical decomposition
51+
26-50
11-25
6-10
1-5
results0% | 0% | 32% | 20% | 46%
Most Complex Units
Top 13 most complex units
Unit# linesMcCabe index# params
def finely_summarize_data_to_table()
in results/summarize_presupposition_results.py
 40 16 4
def correct_prediction()
in results/summarize_presupposition_results.py
 11 10 1
def filter_paradigm()
in results/summarize_presupposition_results.py
 15 6 1
def split_into_paradigms()
in results/summarize_presupposition_results.py
 13 4 1
def unify_results()
in results/summarize_presupposition_results.py
 8 3 2
def accuracy()
in results/summarize_presupposition_results.py
 9 3 1
def get_basic_prsp()
in results/summarize_presupposition_results.py
 3 3 1
def save_csv()
in results/summarize_presupposition_results.py
 6 3 2
def get_controls_contradictions()
in results/summarize_presupposition_results.py
 3 2 1
def get_by_filter()
in results/summarize_presupposition_results.py
 5 2 3
def aggregate_data()
in results/summarize_presupposition_results.py
 3 2 2
def filter_entire_dataset()
in results/summarize_presupposition_results.py
 5 2 1
def get_controls()
in results/summarize_presupposition_results.py
 3 1 1