Files
qbank/internal/sampling/weight.go
T
Jānis Kacēns 968479ff51 Phase 6: take a test (weighted sampling + question flow)
- internal/sampling: ComputeWeight (Laplace-smoothed error rate + recency
  multiplier, floor 0.15) and SelectWeighted (A-Res reservoir algorithm).
  10k-run statistical test verifies weak questions appear >3x more often
  than mastered, and mastered questions still appear (floor exercised).
- GET/POST /test/new: source filter with live available-count JS update,
  n-questions input, weighted vs uniform mode radio.
- GET /test/{id}/q/{n}: deterministic answer shuffle per (test_id,
  question_id), progress bar, mobile-friendly large tap targets.
- POST /test/{id}/q/{n}: records answer + upserts stat; advances to next
  question or finishes test and redirects to results stub.
- GET /test/{id}/results: stub (Phase 7 will add full review).
- Ownership enforced: all test routes 404 for wrong user.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-11 13:56:44 +03:00

42 lines
1.1 KiB
Go

package sampling
import (
"math"
"time"
"qbank/internal/models"
)
const (
FloorWeight = 0.15 // mastered questions still appear at ~15% base rate
RecencyCapDays = 30.0 // days until recency multiplier saturates
RecencyMaxMult = 2.0 // peak recency multiplier
UnseenBaseWeight = 0.5 // base weight for questions with no stats row
)
// ComputeWeight returns the sampling weight for a question given its per-user
// stat. A nil stat means the question has never been seen.
func ComputeWeight(stat *models.UserQuestionStat, now time.Time) float64 {
if stat == nil {
// Unseen: mid-range base + full recency = 1.0
return UnseenBaseWeight * RecencyMaxMult
}
s := float64(stat.TimesSeen)
c := float64(stat.TimesCorrect)
// Laplace-smoothed error rate dampens noise from small samples.
errorRate := (s - c + 1) / (s + 2)
base := math.Max(FloorWeight, errorRate)
var daysSince float64
if stat.LastSeenAt.Valid {
daysSince = now.Sub(stat.LastSeenAt.Time).Hours() / 24
} else {
daysSince = RecencyCapDays
}
recency := 1 + math.Min(daysSince/RecencyCapDays, 1.0)
return base * recency
}