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tool/metric: calc average for ccn and param
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@ -19,12 +19,12 @@ targets = {}
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targets['CCN'] = 10
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targets['PARAM'] = 7
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def metric_count(name):
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def metric_sum(name, value):
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global metrics
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value = 0
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old = 0
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if name in metrics:
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value = metrics[name]
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metrics[name] = value + 1
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old = metrics[name]
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metrics[name] = old + value
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def metric_list(name, item):
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@ -42,17 +42,18 @@ def metric_max(name, max):
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return
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metrics[name] = max
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def metric_measure(metric_name, functino_name, actual):
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def metric_measure(metric_name, function_name, actual):
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metric_max(metric_name + '_MAX', actual)
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if metric_name in targets:
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metric_sum(metric_name + '_SUM', actual)
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if actual > targets[metric_name]:
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metric_count(metric_name + '_DEVIATIONS')
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metric_list(metric_name + '_LIST', functino_name)
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metric_sum(metric_name + '_DEVIATIONS', 1)
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metric_list(metric_name + '_LIST', function_name)
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def analyze_file(path):
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l = lizard.analyze_file(path)
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for f in l.function_list:
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metric_count('FUNC')
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metric_sum('FUNC', 1)
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metric_measure('PARAM', f.name, f.parameter_count)
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metric_measure('CCN', f.name, f.cyclomatic_complexity )
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@ -75,10 +76,16 @@ for path in folders:
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print ("\nResult:")
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num_funcs = metrics['FUNC']
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for key,value in sorted(metrics.items()):
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if key.endswith('LIST'):
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continue
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print ('- %-20s: %4u' % (key, value))
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if key.endswith('_SUM'):
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average = 1.0 * value / num_funcs
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metric = key.replace('_SUM','_AVERAGE')
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print ('- %-20s: %4.3f' % (metric, average))
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else:
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print ('- %-20s: %5u' % (key, value))
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for key,value in sorted(metrics.items()):
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if not key.endswith('LIST'):
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