Skip to content

[dead-code] chore: remove dead functions — 3 functions removed #45277

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
pelikhan merged 1 commit into from
Jul 13, 2026
Merged

[dead-code] chore: remove dead functions — 3 functions removed #45277

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
54 changes: 0 additions & 54 deletions pkg/stats/spec_test.go
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -135,57 +135,3 @@ func TestSpec_PublicAPI_Median_EvenCount(t *testing.T) {
assert.InDelta(t, 2.5, sv.Median(), 1e-9,
"Median with even count should return the average of the two middle sorted values")
}

// TestSpec_PublicAPI_Sum validates that Sum returns the arithmetic sum of all
// observations as described in the package README.md.
//
// Specification: "Sum: Returns the arithmetic sum"
func TestSpec_PublicAPI_Sum(t *testing.T) {
var sv StatVar

assert.InDelta(t, 0.0, sv.Sum(), 1e-9, "Sum should return 0 for an empty StatVar")

sv.Add(10.0)
sv.Add(20.0)
sv.Add(30.0)

assert.InDelta(t, 60.0, sv.Sum(), 1e-9, "Sum should return the total of all observations")
}

// TestSpec_PublicAPI_Variance validates that Variance returns the population
// variance (N denominator) as described in the package README.md.
//
// Specification: "Variance: Returns population variance (N denominator)"
//
// Example: values [2,4,4,4,5,5,7,9] (N=8, mean=5, sum_sq_dev=32) → population variance = 32/8 = 4
func TestSpec_PublicAPI_Variance(t *testing.T) {
var sv StatVar

assert.InDelta(t, 0.0, sv.Variance(), 1e-9, "Variance should return 0 for an empty StatVar")

for _, v := range []float64{2, 4, 4, 4, 5, 5, 7, 9} {
sv.Add(v)
}

assert.InDelta(t, 4.0, sv.Variance(), 1e-9,
"Variance should use N (population) denominator: sum_sq_dev / N")
}

// TestSpec_PublicAPI_StdDev validates that StdDev returns the population
// standard deviation as described in the package README.md.
//
// Specification: "StdDev: Returns population standard deviation"
func TestSpec_PublicAPI_StdDev(t *testing.T) {
var sv StatVar

assert.InDelta(t, 0.0, sv.StdDev(), 1e-9, "StdDev should return 0 for an empty StatVar")

for _, v := range []float64{2, 4, 4, 4, 5, 5, 7, 9} {
sv.Add(v)
}

assert.InDelta(t, math.Sqrt(sv.Variance()), sv.StdDev(), 1e-9,
"StdDev should equal sqrt(Variance)")
assert.InDelta(t, 2.0, sv.StdDev(), 1e-9,
"StdDev of [2,4,4,4,5,5,7,9] should be 2 (population stddev)")
}
17 changes: 0 additions & 17 deletions pkg/stats/statvar.go
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -77,9 +77,6 @@ func (s *StatVar) Max() float64 {
return s.max
}

// Sum returns the arithmetic sum of all observations, or 0 if none.
func (s *StatVar) Sum() float64 { return s.sum }

// Mean returns the arithmetic mean of all observations, or 0 if none.
func (s *StatVar) Mean() float64 {
if s.count == 0 {
Expand All @@ -88,20 +85,6 @@ func (s *StatVar) Mean() float64 {
return s.mean
}

// Variance returns the population variance (divides by N). Returns 0 when no
// observations are present.
func (s *StatVar) Variance() float64 {
if s.count == 0 {
return 0
}
return s.m2 / float64(s.count)
}

// StdDev returns the population standard deviation (sqrt of Variance).
func (s *StatVar) StdDev() float64 {
return math.Sqrt(s.Variance())
}

// SampleVariance returns the sample variance with Bessel's correction (divides
// by N−1), giving an unbiased estimator when the observations are a random
// sample from a larger population. Returns 0 when fewer than two observations
Expand Down
Loading