apache / datasketches-experimentationConditional 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).

Learn more...

Conditional Complexity Overall

There are 236 units with 1,229 lines of code in units (76.8% of code).

0 very complex units (0 lines of code)
1 complex units (63 lines of code)
0 medium complex units (0 lines of code)
6 simple units (120 lines of code)
229 very simple units (1,046 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 50 most complex units

Unit	# lines	McCabe index	# params
def make() in StreamMaker.py	63	30	6
def execute() in SketchExperiment.py	35	9	2
def prepare() in Oracle.py	23	8	2
def makePlotLabels() in analysis/analyze.py	19	7	5
def genQueries() in QueryGenerator.py	16	7	1
def compact() in sketches/Sampler.py	10	6	1
def genQueries() in QueryGenerator.py	17	6	1
def getName() in DataGenerator.py	11	5	3
def genDistributionSequence() in DataGenerator.py	13	5	2
def prepareFromCached() in Oracle.py	17	5	1
def genData() in SyntheticDataGenerators.py	13	5	1
def normalizeDatBySize() in analysis/analyze.py	10	4	4
def cleanByClause() in analysis/analyze.py	3	4	1
def salt() in sketches/Sketches.py	7	4	2
def getSizePerObjective() in sketches/Sampler.py	7	4	1
def add() in sketches/Sampler.py	16	4	3
def genSeq() in QueryGenerator.py	14	4	1
def executeJob() in SketchExperiment.py	27	4	1
def makeJobs() in SketchExperiment.py	13	4	1
def prepareData() in DataGenerator.py	11	3	2
def prepareData() in DataGenerator.py	9	3	2
def genData() in DataGenerator.py	13	3	1
def prefixDict() in sketches/Sketches.py	4	3	2
def query() in sketches/Sketches.py	4	3	3
def filterSum() in sketches/Sampler.py	9	3	3
def lt() in sketches/Sampler.py	5	3	3
def compact() in sketches/Sampler.py	6	3	1
def getScaledThresholds() in sketches/Sampler.py	8	3	2
def compactToSize() in sketches/Sampler.py	7	3	2
def is_infreq() in sketches/Sampler.py	5	3	3
def query() in Oracle.py	4	3	4
def eval_error() in Oracle.py	6	3	3
def query() in Oracle.py	11	3	4
def genData() in SyntheticDataGenerators.py	13	3	1
def prepareData() in DataGenerator.py	4	2	1
def prepare() in DataGenerator.py	5	2	1
def __init__() in DataGenerator.py	9	2	9
def __len__() in DataGenerator.py	4	2	1
def __init__() in DataGenerator.py	8	2	9
def rawAggregateExperimentResults() in analysis/analyze.py	31	2	5
def makeListLike() in analysis/analyze.py	5	2	2
def getSizeBytes() in sketches/Sketches.py	2	2	1
def query() in sketches/Sketches.py	4	2	3
def __init__() in sketches/Sketches.py	2	2	3
def query() in sketches/Sketches.py	5	2	3
def __init__() in sketches/Sketches.py	2	2	3
def query() in sketches/Sketches.py	5	2	3
def reduceSampleSize() in sketches/Sampler.py	3	2	2
def add() in sketches/Sampler.py	6	2	3
def items() in sketches/Sampler.py	3	2	1