func handleServerConn
has a cyclomatic complexity of 17 with "high" risk 34 return cmd[i:]
35}
36
37func handleServerConn(keyID string, chans <-chan ssh.NewChannel) { 38 for newChan := range chans {
39 if newChan.ChannelType() != "session" {
40 _ = newChan.Reject(ssh.UnknownChannelType, "unknown channel type")
func renderFile
has a cyclomatic complexity of 24 with "high" risk119 }
120}
121
122func renderFile(c *context.Context, entry *git.TreeEntry, treeLink, rawLink string) {123 c.Data["IsViewFile"] = true
124
125 blob := entry.Blob()
func renderDirectory
has a cyclomatic complexity of 17 with "high" risk 33 FORKS = "repo/forks"
34)
35
36func renderDirectory(c *context.Context, treeLink string) { 37 tree, err := c.Repo.Commit.Subtree(c.Repo.TreePath)
38 if err != nil {
39 c.NotFoundOrError(gitutil.NewError(err), "get subtree")
func Releases
has a cyclomatic complexity of 19 with "high" risk 46 return nil
47}
48
49func Releases(c *context.Context) { 50 c.Data["Title"] = c.Tr("repo.release.releases")
51 c.Data["PageIsViewFiles"] = true
52 c.Data["PageIsReleaseList"] = true
func editFilePost
has a cyclomatic complexity of 30 with "very-high" risk119 editFile(c, true)
120}
121
122func editFilePost(c *context.Context, f form.EditRepoFile, isNewFile bool) {123 c.PageIs("Edit")
124 c.RequireHighlightJS()
125 c.RequireSimpleMDE()
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. |