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https://github.com/lukaszraczylo/claude-mnemonic.git
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Initial commit
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@@ -0,0 +1,292 @@
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// Package similarity provides text similarity and clustering utilities.
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package similarity
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import (
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"database/sql"
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"testing"
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"github.com/lukaszraczylo/claude-mnemonic/pkg/models"
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"github.com/stretchr/testify/assert"
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"github.com/stretchr/testify/require"
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)
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func TestJaccardSimilarity(t *testing.T) {
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tests := []struct {
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name string
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set1 map[string]bool
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set2 map[string]bool
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expected float64
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}{
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{
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name: "identical sets",
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set1: map[string]bool{"a": true, "b": true, "c": true},
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set2: map[string]bool{"a": true, "b": true, "c": true},
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expected: 1.0,
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},
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{
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name: "no overlap",
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set1: map[string]bool{"a": true, "b": true},
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set2: map[string]bool{"c": true, "d": true},
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expected: 0.0,
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},
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{
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name: "partial overlap",
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set1: map[string]bool{"a": true, "b": true, "c": true},
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set2: map[string]bool{"b": true, "c": true, "d": true},
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expected: 0.5, // intersection=2, union=4
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},
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{
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name: "empty sets",
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set1: map[string]bool{},
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set2: map[string]bool{},
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expected: 1.0,
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},
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{
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name: "one empty set",
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set1: map[string]bool{"a": true},
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set2: map[string]bool{},
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expected: 0.0,
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},
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}
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for _, tt := range tests {
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t.Run(tt.name, func(t *testing.T) {
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result := JaccardSimilarity(tt.set1, tt.set2)
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assert.InDelta(t, tt.expected, result, 0.001)
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})
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}
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}
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func TestExtractObservationTerms(t *testing.T) {
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obs := &models.Observation{
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Title: sql.NullString{String: "Authentication flow implementation", Valid: true},
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Narrative: sql.NullString{String: "We implemented JWT-based authentication", Valid: true},
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Facts: models.JSONStringArray{"Users authenticate via API", "Tokens expire after 24 hours"},
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FilesRead: models.JSONStringArray{"/src/auth/handler.go", "/src/auth/jwt.go"},
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}
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terms := ExtractObservationTerms(obs)
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// Should contain terms from title
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assert.Contains(t, terms, "authentication")
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assert.Contains(t, terms, "flow")
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assert.Contains(t, terms, "implementation")
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// Should contain terms from narrative
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assert.Contains(t, terms, "implemented")
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// Should contain terms from facts
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assert.Contains(t, terms, "tokens")
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assert.Contains(t, terms, "expire")
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assert.Contains(t, terms, "hours")
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// Should contain filenames (without path)
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assert.Contains(t, terms, "handler.go")
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assert.Contains(t, terms, "jwt.go")
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// Should NOT contain stop words
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assert.NotContains(t, terms, "the")
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assert.NotContains(t, terms, "and")
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assert.NotContains(t, terms, "we")
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}
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func TestClusterObservations(t *testing.T) {
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// Create similar observations
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obs1 := &models.Observation{
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ID: 1,
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Title: sql.NullString{String: "Authentication flow implementation", Valid: true},
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Narrative: sql.NullString{String: "JWT-based authentication for API", Valid: true},
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}
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obs2 := &models.Observation{
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ID: 2,
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Title: sql.NullString{String: "Authentication flow update", Valid: true},
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Narrative: sql.NullString{String: "Updated JWT authentication logic", Valid: true},
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}
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obs3 := &models.Observation{
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ID: 3,
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Title: sql.NullString{String: "Database migration guide", Valid: true},
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Narrative: sql.NullString{String: "How to run database migrations", Valid: true},
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}
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obs4 := &models.Observation{
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ID: 4,
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Title: sql.NullString{String: "Database schema changes", Valid: true},
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Narrative: sql.NullString{String: "Updated database schema for users", Valid: true},
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}
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observations := []*models.Observation{obs1, obs2, obs3, obs4}
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// Cluster with 0.4 threshold
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clustered := ClusterObservations(observations, 0.4)
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// obs1 and obs2 should be clustered (similar authentication content)
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// obs3 and obs4 should be clustered (similar database content)
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t.Logf("Clustered %d observations down to %d", len(observations), len(clustered))
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assert.LessOrEqual(t, len(clustered), 4)
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assert.GreaterOrEqual(t, len(clustered), 1)
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// First observation in each cluster should be kept (obs1 for auth, obs3 for db)
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ids := make(map[int64]bool)
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for _, obs := range clustered {
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ids[obs.ID] = true
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}
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// Depending on threshold, obs1 should be kept (first in auth cluster)
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if len(clustered) <= 3 {
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assert.True(t, ids[1], "First observation (ID=1) should be kept as cluster representative")
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}
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}
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func TestClusterObservations_SingleObservation(t *testing.T) {
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obs := &models.Observation{
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ID: 1,
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Title: sql.NullString{String: "Single observation", Valid: true},
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}
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clustered := ClusterObservations([]*models.Observation{obs}, 0.4)
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assert.Len(t, clustered, 1)
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assert.Equal(t, int64(1), clustered[0].ID)
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}
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func TestClusterObservations_EmptyList(t *testing.T) {
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clustered := ClusterObservations([]*models.Observation{}, 0.4)
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assert.Len(t, clustered, 0)
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}
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func TestClusterObservations_NoDuplicates(t *testing.T) {
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// Create observations with completely different content
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observations := []*models.Observation{
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{
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ID: 1,
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Title: sql.NullString{String: "Authentication system", Valid: true},
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Narrative: sql.NullString{String: "JWT tokens for user auth", Valid: true},
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},
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{
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ID: 2,
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Title: sql.NullString{String: "Database configuration", Valid: true},
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Narrative: sql.NullString{String: "PostgreSQL setup and migrations", Valid: true},
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},
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{
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ID: 3,
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Title: sql.NullString{String: "Caching layer", Valid: true},
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Narrative: sql.NullString{String: "Redis caching implementation", Valid: true},
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},
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{
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ID: 4,
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Title: sql.NullString{String: "Logging setup", Valid: true},
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Narrative: sql.NullString{String: "Structured logging with zerolog", Valid: true},
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},
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{
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ID: 5,
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Title: sql.NullString{String: "API endpoints", Valid: true},
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Narrative: sql.NullString{String: "REST API implementation", Valid: true},
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},
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}
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clustered := ClusterObservations(observations, 0.4)
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// With completely different content, all should be kept
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assert.Len(t, clustered, 5, "All unique observations should be kept")
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}
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func TestIsSimilarToAny(t *testing.T) {
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existing := []*models.Observation{
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{
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ID: 1,
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Title: sql.NullString{String: "Authentication implementation", Valid: true},
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Narrative: sql.NullString{String: "JWT authentication flow", Valid: true},
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},
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{
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ID: 2,
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Title: sql.NullString{String: "Database setup", Valid: true},
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Narrative: sql.NullString{String: "PostgreSQL configuration", Valid: true},
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},
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}
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// New observation similar to existing
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similar := &models.Observation{
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ID: 3,
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Title: sql.NullString{String: "Authentication update", Valid: true},
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Narrative: sql.NullString{String: "JWT authentication changes", Valid: true},
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}
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// New observation not similar to any existing
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different := &models.Observation{
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ID: 4,
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Title: sql.NullString{String: "Caching layer", Valid: true},
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Narrative: sql.NullString{String: "Redis caching implementation", Valid: true},
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}
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assert.True(t, IsSimilarToAny(similar, existing, 0.3), "Similar observation should be detected")
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assert.False(t, IsSimilarToAny(different, existing, 0.3), "Different observation should not match")
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}
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func TestIsSimilarToAny_EmptyExisting(t *testing.T) {
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newObs := &models.Observation{
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ID: 1,
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Title: sql.NullString{String: "New observation", Valid: true},
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}
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assert.False(t, IsSimilarToAny(newObs, []*models.Observation{}, 0.4))
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assert.False(t, IsSimilarToAny(newObs, nil, 0.4))
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}
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func TestAddTerms(t *testing.T) {
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terms := make(map[string]bool)
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addTerms(terms, "The quick brown fox jumps over the lazy dog")
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// Should contain words >= 3 chars that aren't stop words
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assert.Contains(t, terms, "quick")
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assert.Contains(t, terms, "brown")
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assert.Contains(t, terms, "fox")
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assert.Contains(t, terms, "jumps")
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assert.Contains(t, terms, "over")
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assert.Contains(t, terms, "lazy")
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assert.Contains(t, terms, "dog")
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// Should NOT contain stop words
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assert.NotContains(t, terms, "the")
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// Should NOT contain short words
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// (all words in the sentence are >= 3 chars after stop word removal)
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}
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func TestClusterObservations_MoreThanOldLimit(t *testing.T) {
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// This test verifies that we can now return more than 5 observations
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// after removing the hardcoded limit
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// Create 10 completely unique observations with very different content
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observations := []*models.Observation{
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{ID: 1, Title: sql.NullString{String: "JWT tokens expire daily", Valid: true}},
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{ID: 2, Title: sql.NullString{String: "PostgreSQL indexes optimize", Valid: true}},
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{ID: 3, Title: sql.NullString{String: "Redis caching TTL values", Valid: true}},
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{ID: 4, Title: sql.NullString{String: "Zerolog structured logging", Valid: true}},
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{ID: 5, Title: sql.NullString{String: "Pytest fixtures setup", Valid: true}},
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{ID: 6, Title: sql.NullString{String: "Docker containers orchestration", Valid: true}},
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{ID: 7, Title: sql.NullString{String: "Prometheus metrics collection", Valid: true}},
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{ID: 8, Title: sql.NullString{String: "OWASP vulnerability scanning", Valid: true}},
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{ID: 9, Title: sql.NullString{String: "Goroutines parallel execution", Valid: true}},
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{ID: 10, Title: sql.NullString{String: "Kubernetes horizontal scaling", Valid: true}},
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}
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clustered := ClusterObservations(observations, 0.4)
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// With unique content, all 10 should be kept (previously would have been capped at 5)
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assert.Len(t, clustered, 10, "Should return all 10 unique observations, not limited to 5")
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}
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func TestClusterObservations_PreservesOrder(t *testing.T) {
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// The first observation in each cluster should be kept
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observations := []*models.Observation{
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{ID: 1, Title: sql.NullString{String: "First auth observation", Valid: true}},
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{ID: 2, Title: sql.NullString{String: "Second auth observation", Valid: true}},
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{ID: 3, Title: sql.NullString{String: "Database observation", Valid: true}},
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}
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clustered := ClusterObservations(observations, 0.4)
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// First observation should always be first in result
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require.NotEmpty(t, clustered)
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assert.Equal(t, int64(1), clustered[0].ID, "First observation should be kept as first result")
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}
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