test: Add tests for calculateTrimmedBaseline and createOrUpdateNodeAlert
- calculateTrimmedBaseline: 8 test cases covering sample count thresholds, trimmed mean calculation, median fallback logic, odd-length arrays - createOrUpdateNodeAlert: 2 test cases for new alert creation and existing alert updates Coverage: calculateTrimmedBaseline 0%→96.9%, createOrUpdateNodeAlert 0%→100% Package coverage: 59.6%→61.3%
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rcourtman
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1 changed files with 244 additions and 0 deletions
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@ -6602,3 +6602,247 @@ func TestCheckPMGOffline(t *testing.T) {
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}
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})
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}
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func TestCalculateTrimmedBaseline(t *testing.T) {
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t.Parallel()
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t.Run("less than 12 samples returns untrustworthy", func(t *testing.T) {
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t.Parallel()
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samples := []float64{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11}
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baseline, trustworthy := calculateTrimmedBaseline(samples)
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if trustworthy {
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t.Error("expected untrustworthy with less than 12 samples")
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}
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if baseline != 0 {
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t.Errorf("expected baseline 0, got %f", baseline)
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}
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})
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t.Run("empty samples returns untrustworthy", func(t *testing.T) {
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t.Parallel()
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samples := []float64{}
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baseline, trustworthy := calculateTrimmedBaseline(samples)
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if trustworthy {
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t.Error("expected untrustworthy with empty samples")
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}
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if baseline != 0 {
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t.Errorf("expected baseline 0, got %f", baseline)
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}
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})
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t.Run("12-23 samples uses simple mean", func(t *testing.T) {
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t.Parallel()
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// 12 samples summing to 78
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samples := []float64{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}
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baseline, trustworthy := calculateTrimmedBaseline(samples)
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if !trustworthy {
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t.Error("expected trustworthy with 12 samples")
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}
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// Mean of 1-12 is (1+2+...+12)/12 = 78/12 = 6.5
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if baseline != 6.5 {
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t.Errorf("expected baseline 6.5, got %f", baseline)
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}
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})
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t.Run("24+ samples uses trimmed mean", func(t *testing.T) {
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t.Parallel()
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// 24 identical values - trimmed mean should equal value
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samples := make([]float64, 24)
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for i := range samples {
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samples[i] = 10.0
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}
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baseline, trustworthy := calculateTrimmedBaseline(samples)
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if !trustworthy {
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t.Error("expected trustworthy with 24 samples")
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}
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if baseline != 10.0 {
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t.Errorf("expected baseline 10.0, got %f", baseline)
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}
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})
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t.Run("24+ samples falls back to median when diff > 40%", func(t *testing.T) {
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t.Parallel()
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// Create samples where trimmed mean differs significantly from median
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// Mostly 10s with some extreme outliers that survive trimming
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samples := make([]float64, 24)
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for i := range samples {
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if i < 4 {
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samples[i] = 100.0 // Extreme high values
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} else {
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samples[i] = 10.0 // Normal values
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}
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}
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// After sorting: 10,10,...,10,100,100,100,100
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// Median is 10 (middle values are 10s)
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// Trimmed mean (drop 2 highest and 2 lowest): still has 2 100s
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// So trimmed mean > median * 1.4, should fall back to median
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baseline, trustworthy := calculateTrimmedBaseline(samples)
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if !trustworthy {
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t.Error("expected trustworthy")
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}
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// Should use median (10) due to large diff
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if baseline != 10.0 {
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t.Errorf("expected baseline 10.0 (median fallback), got %f", baseline)
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}
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})
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t.Run("24+ samples uses trimmed mean when diff <= 40%", func(t *testing.T) {
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t.Parallel()
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// Sequential values with minimal outlier effect
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samples := make([]float64, 24)
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for i := range samples {
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samples[i] = float64(i + 1) // 1,2,3,...,24
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}
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baseline, trustworthy := calculateTrimmedBaseline(samples)
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if !trustworthy {
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t.Error("expected trustworthy")
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}
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// Median of 1-24 is (12+13)/2 = 12.5
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// Trimmed mean of 3-22 is (3+4+...+22)/20 = 250/20 = 12.5
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// Both are close, should use trimmed mean
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if baseline != 12.5 {
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t.Errorf("expected baseline 12.5, got %f", baseline)
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}
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})
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t.Run("odd length array uses middle element for median", func(t *testing.T) {
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t.Parallel()
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// 25 samples: an odd-length array
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samples := make([]float64, 25)
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for i := range samples {
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samples[i] = float64(i + 1) // 1,2,3,...,25
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}
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baseline, trustworthy := calculateTrimmedBaseline(samples)
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if !trustworthy {
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t.Error("expected trustworthy")
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}
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// Median of sorted 1-25 is the 13th element = 13
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// Trimmed mean excludes top/bottom 2: 3..23 = 21 elements, sum = (3+23)*21/2 = 273, mean = 13
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// Both are 13, diff is 0%, should use trimmed mean = 13
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if baseline != 13.0 {
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t.Errorf("expected baseline 13.0, got %f", baseline)
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}
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})
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t.Run("trimmed mean less than median triggers diff calculation", func(t *testing.T) {
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t.Parallel()
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// Create samples where trimmed mean < median but within 40%
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// High outliers at top (excluded by trim), low values in middle
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samples := make([]float64, 24)
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// First 2 (will be trimmed): very low
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samples[0], samples[1] = 1, 2
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// Middle 20: mostly 50 but some variance
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for i := 2; i < 22; i++ {
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samples[i] = 50.0
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}
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// Last 2 (will be trimmed): very high
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samples[22], samples[23] = 100, 200
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baseline, trustworthy := calculateTrimmedBaseline(samples)
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if !trustworthy {
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t.Error("expected trustworthy")
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}
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// After sorting: 1, 2, 50x20, 100, 200
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// Median of even array: (50+50)/2 = 50
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// Trimmed mean: 50x20/20 = 50
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// Should return 50
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if baseline != 50.0 {
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t.Errorf("expected baseline 50.0, got %f", baseline)
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}
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})
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}
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func TestCreateOrUpdateNodeAlert(t *testing.T) {
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t.Parallel()
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t.Run("creates new alert", func(t *testing.T) {
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t.Parallel()
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m := NewManager()
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pmg := models.PMGInstance{ID: "pmg1", Name: "PMG 1"}
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m.createOrUpdateNodeAlert(
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"pmg1-node-queue",
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pmg,
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"mail-node1",
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"pmg-node-queue",
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AlertLevelWarning,
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100,
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50,
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"Queue depth high",
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)
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m.mu.RLock()
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alert := m.activeAlerts["pmg1-node-queue"]
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m.mu.RUnlock()
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if alert == nil {
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t.Fatal("expected alert to be created")
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}
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if alert.Type != "pmg-node-queue" {
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t.Errorf("expected type pmg-node-queue, got %s", alert.Type)
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}
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if alert.Level != AlertLevelWarning {
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t.Errorf("expected warning level, got %s", alert.Level)
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}
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if alert.Value != 100 {
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t.Errorf("expected value 100, got %f", alert.Value)
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}
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if alert.Threshold != 50 {
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t.Errorf("expected threshold 50, got %f", alert.Threshold)
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}
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if alert.Node != "mail-node1" {
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t.Errorf("expected node mail-node1, got %s", alert.Node)
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}
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})
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t.Run("updates existing alert", func(t *testing.T) {
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t.Parallel()
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m := NewManager()
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oldTime := time.Now().Add(-1 * time.Hour)
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m.mu.Lock()
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m.activeAlerts["pmg1-node-queue"] = &Alert{
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ID: "pmg1-node-queue",
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Value: 50,
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Threshold: 40,
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Level: AlertLevelWarning,
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Message: "Old message",
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LastSeen: oldTime,
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}
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m.mu.Unlock()
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pmg := models.PMGInstance{ID: "pmg1", Name: "PMG 1"}
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m.createOrUpdateNodeAlert(
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"pmg1-node-queue",
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pmg,
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"mail-node1",
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"pmg-node-queue",
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AlertLevelCritical,
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200,
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100,
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"New message",
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)
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m.mu.RLock()
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alert := m.activeAlerts["pmg1-node-queue"]
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m.mu.RUnlock()
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if alert == nil {
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t.Fatal("expected alert to exist")
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}
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if alert.Value != 200 {
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t.Errorf("expected value 200, got %f", alert.Value)
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}
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if alert.Threshold != 100 {
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t.Errorf("expected threshold 100, got %f", alert.Threshold)
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}
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if alert.Level != AlertLevelCritical {
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t.Errorf("expected critical level, got %s", alert.Level)
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}
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if alert.Message != "New message" {
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t.Errorf("expected 'New message', got %s", alert.Message)
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}
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if !alert.LastSeen.After(oldTime) {
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t.Error("expected LastSeen to be updated")
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}
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})
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}
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