amazon-research / progressive-coordinate-transforms
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 287 units with 4,701 lines of code in units (82.5% of code).
    • 0 very complex units (0 lines of code)
    • 2 complex units (194 lines of code)
    • 12 medium complex units (778 lines of code)
    • 27 simple units (1,058 lines of code)
    • 246 very simple units (2,671 lines of code)
0% | 4% | 16% | 22% | 56%
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
cpp0% | 17% | 41% | 12% | 28%
py0% | 0% | 8% | 25% | 65%
h0% | 0% | 0% | 0% | 100%
Conditional Complexity per Logical Component
primary logical decomposition
51+
26-50
11-25
6-10
1-5
tools/kitti_eval0% | 17% | 41% | 11% | 29%
lib/losses0% | 0% | 43% | 47% | 9%
tools/data_prepare0% | 0% | 19% | 36% | 43%
tools/waymo0% | 0% | 19% | 16% | 63%
lib/helpers0% | 0% | 0% | 43% | 56%
lib/datasets0% | 0% | 0% | 46% | 53%
lib/utils0% | 0% | 0% | 18% | 81%
lib/backbones0% | 0% | 0% | 0% | 100%
lib/models0% | 0% | 0% | 0% | 100%
tools0% | 0% | 0% | 0% | 100%
lib/extensions0% | 0% | 0% | 0% | 100%
Most Complex Units
Top 20 most complex units
Unit# linesMcCabe index# params
tPrData computeStatistics()
in tools/kitti_eval/evaluate_object_3d_offline_ap11.cpp
 97 46 8
tPrData computeStatistics()
in tools/kitti_eval/evaluate_object_3d_offline_ap40.cpp
 97 46 8
void cleanData()
in tools/kitti_eval/evaluate_object_3d_offline_ap11.cpp
 42 21 8
bool eval()
in tools/kitti_eval/evaluate_object_3d_offline_ap11.cpp
 92 21 3
void cleanData()
in tools/kitti_eval/evaluate_object_3d_offline_ap40.cpp
 42 21 8
bool eval()
in tools/kitti_eval/evaluate_object_3d_offline_ap40.cpp
 92 21 3
def save_label()
in tools/waymo/converter.py
 68 17 4
def get_loss()
in lib/losses/patchnet_loss.py
 111 15 11
def save_calib()
in tools/waymo/converter.py
 32 14 4
vector loadDetections()
in tools/kitti_eval/evaluate_object_3d_offline_ap11.cpp
 38 13 6
vector loadDetections()
in tools/kitti_eval/evaluate_object_3d_offline_ap40.cpp
 38 13 6
def extract_patch_data_val_detection()
in tools/data_prepare/patch_data_prepare_val.py
 105 12 4
bool eval_class()
in tools/kitti_eval/evaluate_object_3d_offline_ap11.cpp
 59 11 7
bool eval_class()
in tools/kitti_eval/evaluate_object_3d_offline_ap40.cpp
 59 11 7
def __getitem__()
in lib/datasets/patch_dataset.py
 45 10 2
def build_dataloader()
in lib/helpers/data_builder.py
 78 10 3
def test_one_epoch()
in lib/helpers/tester_helper.py
 66 10 1
def get_obj_level()
in lib/utils/kitti/object3d.py
 14 10 1
def get_boxes_from_txt()
in tools/waymo/waymo_eval.py
 44 10 5
def extract_patch_data()
in tools/data_prepare/patch_data_prepare_val.py
 106 10 5