Awesome
Gocognit
Gocognit calculates cognitive complexities of functions (and methods) in Go source code. A measurement of how hard does the code is intuitively to understand.
Understanding the complexity
Given code using if statement,
func GetWords(number int) string {
if number == 1 { // +1
return "one"
} else if number == 2 { // +1
return "a couple"
} else if number == 3 { // +1
return "a few"
} else { // +1
return "lots"
}
} // Cognitive complexity = 4
Above code can be refactored using switch statement,
func GetWords(number int) string {
switch number { // +1
case 1:
return "one"
case 2:
return "a couple"
case 3:
return "a few"
default:
return "lots"
}
} // Cognitive complexity = 1
As you see above codes are the same, but the second code are easier to understand, that is why the cognitive complexity score are lower compare to the first one.
Comparison with cyclomatic complexity
Example 1
Cyclomatic complexity
func GetWords(number int) string { // +1
switch number {
case 1: // +1
return "one"
case 2: // +1
return "a couple"
case 3: // +1
return "a few"
default:
return "lots"
}
} // Cyclomatic complexity = 4
Cognitive complexity
func GetWords(number int) string {
switch number { // +1
case 1:
return "one"
case 2:
return "a couple"
case 3:
return "a few"
default:
return "lots"
}
} // Cognitive complexity = 1
Cognitive complexity give lower score compare to cyclomatic complexity.
Example 2
Cyclomatic complexity
func SumOfPrimes(max int) int { // +1
var total int
OUT:
for i := 1; i < max; i++ { // +1
for j := 2; j < i; j++ { // +1
if i%j == 0 { // +1
continue OUT
}
}
total += i
}
return total
} // Cyclomatic complexity = 4
Cognitive complexity
func SumOfPrimes(max int) int {
var total int
OUT:
for i := 1; i < max; i++ { // +1
for j := 2; j < i; j++ { // +2 (nesting = 1)
if i%j == 0 { // +3 (nesting = 2)
continue OUT // +1
}
}
total += i
}
return total
} // Cognitive complexity = 7
Cognitive complexity give higher score compare to cyclomatic complexity.
Rules
The cognitive complexity of a function is calculated according to the following rules:
Note: these rules are specific for Go, please see the original whitepaper for more complete reference.
Increments
There is an increment for each of the following:
if,else if,elseswitch,selectforgotoLABEL,breakLABEL,continueLABEL- sequence of binary logical operators
- each method in a recursion cycle
Nesting level
The following structures increment the nesting level:
if,else if,elseswitch,selectfor- function literal or lambda
Nesting increments
The following structures receive a nesting increment commensurate with their nested depth inside nesting structures:
ifswitch,selectfor
Installation
go install github.com/uudashr/gocognit/cmd/gocognit@latest
or
go get github.com/uudashr/gocognit/cmd/gocognit
Usage
$ gocognit
Calculate cognitive complexities of Go functions.
Usage:
gocognit [<flag> ...] <Go file or directory> ...
Flags:
-over N show functions with complexity > N only
and return exit code 1 if the output is non-empty
-top N show the top N most complex functions only
-avg show the average complexity over all functions,
not depending on whether -over or -top are set
-test indicates whether test files should be included
-json encode the output as JSON
-d enable diagnostic output
-f format string the format to use
(default "{{.Complexity}} {{.PkgName}} {{.FuncName}} {{.Pos}}")
-ignore expr ignore files matching the given regexp
The (default) output fields for each line are:
<complexity> <package> <function> <file:row:column>
The (default) output fields for each line are:
{{.Complexity}} {{.PkgName}} {{.FuncName}} {{.Pos}}
or equal to <complexity> <package> <function> <file:row:column>
The struct being passed to the template is:
type Stat struct {
PkgName string
FuncName string
Complexity int
Pos token.Position
Diagnostics []Diagnostics
}
type Diagnostic struct {
Inc string
Nesting int
Text string
Pos DiagnosticPosition
}
type DiagnosticPosition struct {
Offset int
Line int
Column int
}
Examples:
$ gocognit .
$ gocognit main.go
$ gocognit -top 10 src/
$ gocognit -over 25 docker
$ gocognit -avg .
$ gocognit -ignore "_test|testdata" .
The output fields for each line are:
<complexity> <package> <function> <file:row:column>
Ignore individual functions
Ignore individual functions by specifying gocognit:ignore directive.
//gocognit:ignore
func IgnoreMe() {
// ...
}
Diagnostic
To understand how the complexity are calculated, we can enable the diagnostic by using -d flag.
Example:
$ gocognit -json -d .
It will show the diagnostic output in JSON format
<details> <summary>JSON Output</summary>[
{
"PkgName": "prime",
"FuncName": "SumOfPrimes",
"Complexity": 7,
"Pos": {
"Filename": "prime.go",
"Offset": 15,
"Line": 3,
"Column": 1
},
"Diagnostics": [
{
"Inc": 1,
"Text": "for",
"Pos": {
"Offset": 69,
"Line": 7,
"Column": 2
}
},
{
"Inc": 2,
"Nesting": 1,
"Text": "for",
"Pos": {
"Offset": 104,
"Line": 8,
"Column": 3
}
},
{
"Inc": 3,
"Nesting": 2,
"Text": "if",
"Pos": {
"Offset": 152,
"Line": 9,
"Column": 4
}
},
{
"Inc": 1,
"Text": "continue",
"Pos": {
"Offset": 190,
"Line": 10,
"Column": 5
}
}
]
}
]
Related project
- Gocyclo where the code are based on.
- Cognitive Complexity: A new way of measuring understandability white paper by G. Ann Campbell.