func TestMediaPlaylist_Slide
has a cyclomatic complexity of 17 with "high" risk 688 }
689}
690
691func TestMediaPlaylist_Slide(t *testing.T) { 692 m, e := NewMediaPlaylist(3, 4)
693 if e != nil {
694 t.Fatalf("Failed to create media playlist: %v", e)
func Encode
has a cyclomatic complexity of 66 with "critical" risk398
399// Encode generates output in M3U8 format. Marshal `winsize` elements
400// from bottom of the `buf` queue.
401func (p *MediaPlaylist) Encode() *bytes.Buffer {402 if p.buf.Len() > 0 {
403 return &p.buf
404 }
func Encode
has a cyclomatic complexity of 42 with "very-high" risk 70}
71
72// Encode generates the output in M3U8 format.
73func (p *MasterPlaylist) Encode() *bytes.Buffer { 74 if p.buf.Len() > 0 {
75 return &p.buf
76 }
func TestDecodeMediaPlaylistWithCustomTags
has a cyclomatic complexity of 18 with "high" risk 677 }
678}
679
680func TestDecodeMediaPlaylistWithCustomTags(t *testing.T) { 681 cases := []struct {
682 src string
683 customDecoders []CustomDecoder
func decodeLineOfMediaPlaylist
has a cyclomatic complexity of 157 with "critical" risk446}
447
448// Parse one line of media playlist.
449func decodeLineOfMediaPlaylist(p *MediaPlaylist, wv *WV, state *decodingState, line string, strict bool) error {450 var err error
451
452 line = strings.TrimSpace(line)
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:
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
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
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. |