func Do has a cyclomatic complexity of 52 with "critical" risk 63}
64
65// movingXyz(seriesList, windowSize)
66func (f *moving) Do(ctx context.Context, eval interfaces.Evaluator, e parser.Expr, from, until int64, values map[parser.MetricRequest][]*types.MetricData) ([]*types.MetricData, error) { 67 var n int
68 var err error
69func Fetch has a cyclomatic complexity of 20 with "high" risk 25 zipper zipper.CarbonZipper
26}
27
28func (eval Evaluator) Fetch(ctx context.Context, exprs []parser.Expr, from, until int64, values map[parser.MetricRequest][]*types.MetricData) (map[parser.MetricRequest][]*types.MetricData, error) { 29 if err := eval.limiter.Enter(ctx); err != nil {
30 return nil, err
31 }func main has a cyclomatic complexity of 30 with "very-high" risk 29// BuildVersion is provided to be overridden at build time. Eg. go build -ldflags -X 'main.BuildVersion=...'
30var BuildVersion = "(development build)"
31
32func main() { 33 err := zapwriter.ApplyConfig([]zapwriter.Config{config.DefaultLoggerConfig})
34 if err != nil {
35 log.Fatal("Failed to initialize logger with default configuration")A function with high cyclomatic complexity can be hard to understand and maintain. Cyclomatic complexity is a software metric that measures the number of independent paths through a function. A higher cyclomatic complexity indicates that the function has more decision points and is more complex.
Functions with high cyclomatic complexity are more likely to have bugs and be harder to test. They may lead to reduced code maintainability and increased development time.
To reduce the cyclomatic complexity of a function, you can:
- Break the function into smaller, more manageable functions.
- Refactor complex logic into separate functions or classes.
- Avoid multiple return paths and deeply nested control expressions.
Bad practice
package main
import "log"
func fizzbuzzfuzz(x int) { // cc = 1
if x == 0 || x < 0 { // cc = 3 (if, ||)
return
}
for i := 1; i <= x; i++ { // cc = 4 (for)
switch i % 15 * 2 {
case 0: // cc = 5 (case)
countDiv3 += 1
countDiv5 += 1
log.Println("fizzbuzz")
break
case 3:
case 6:
case 9:
case 12: // cc = 9 (case)
countDiv3 += 1
log.Println("fizz")
break
case 5:
case 10: // cc = 11 (case)
countDiv5 += 1
log.Println("buzz")
break
default:
log.Printf("%d\n", x)
}
}
} // CC == 11; raises issues
Recommended
package main
import "log"
func fizzbuzz(x int) { // cc = 1
for i := 1; i <= x; i++ { // cc = 2 (for)
y := i%3 == 0
z := i%5 == 0
if y == z { // 3
if y == false { // 4
log.Printf("%d\n", i)
} else {
log.Println("fizzbuzz")
}
} else {
if y { // 5
log.Println("fizz")
} else {
log.Println("buzz")
}
}
}
} // CC == 5
Issue configuration
Cyclomatic complexity threshold can be configured using the
cyclomatic_complexity_threshold (docs) in the
.deepsource.toml config file.
Configuring this is optional. If you don't provide a value, the Analyzer will
raise issues for functions with complexity higher than the default threshold,
which is medium(only raise issues for >15) for the Go Analyzer.
Here's the mapping of the risk category to the cyclomatic complexity score to help you configure this better:
| Risk category | Cyclomatic complexity range | Recommended action |
|---|---|---|
| low | 1-5 | No action needed. |
| medium | 6-15 | Review and monitor. |
| high | 16-25 | Review and refactor. Recommended to add comments if the function is absolutely needed to be kept as it is. |
| very-high. | 26-50 | Refactor to reduce the complexity. |
| critical | >50 | Must refactor this. This can make the code untestable and very difficult to understand. |