Files
sanderling/cmd/internal-tools/analyze/analysis.go
T
pj 454988fbc8 fix(trace): an action names the generator that produced it
The setup exclusion landed for the model arm only, because only a model
pick stamped a source. A seeded run returned setup's action through the
same entry with no marker, so its denominator still counted the login
while the model arm's did not, and the two are compared.

serializeAction names setup and seeded on the wire, so both arms are
counted by one rule. An already-recorded trace names nothing and keeps
exactly the count it was reported with; unattributed_actions counts those
steps so the old denominator cannot pass as the new one. TraceVersion is
deliberately unbumped: oracle-reduction refuses a differing version, and
a bump would make all 169 recorded runs unreplayable.
2026-08-18 17:58:38 +05:30

287 lines
10 KiB
Go

package main
import (
"fmt"
"math"
"slices"
"time"
)
type armSummary struct {
Arm string `json:"arm"`
Generator string `json:"generator,omitempty"`
Platform string `json:"platform,omitempty"`
StepBudget int `json:"step_budget"`
Directories []string `json:"directories"`
Recorded int `json:"recorded_runs"`
Usable int `json:"usable_runs"`
Violated int `json:"violated_runs"`
Censored int `json:"censored_runs"`
Excluded int `json:"excluded_runs"`
ExcludedByReason map[string]int `json:"excluded_by_reason,omitempty"`
MissingSeeds []int64 `json:"missing_seeds,omitempty"`
EventsHeldAtBudget int `json:"events_held_at_budget"`
EventsDetectedAfterOrigin int `json:"events_detected_after_origin"`
MedianStepsToFirstViolation *float64 `json:"median_steps_to_first_violation"`
FirstQuartileSteps *float64 `json:"first_quartile_steps_to_first_violation"`
ThirdQuartileSteps *float64 `json:"third_quartile_steps_to_first_violation"`
SurvivalCurve []survivalPoint `json:"survival_curve,omitempty"`
ViolationRate *float64 `json:"violation_rate"`
TotalSteps int `json:"total_steps"`
TotalActions int `json:"total_actions"`
TotalRunHours float64 `json:"total_run_hours"`
Detections int `json:"detections"`
DefectsPerThousandActions *float64 `json:"defects_per_thousand_actions"`
DefectsPerHour *float64 `json:"defects_per_hour"`
DistinctDefects int `json:"distinct_defects"`
SingletonDefects int `json:"singleton_defects"`
SingletonFraction *float64 `json:"singleton_fraction"`
DefectRunCounts map[string]int `json:"defect_run_counts,omitempty"`
}
type pairwiseResult struct {
First string `json:"first"`
Second string `json:"second"`
FirstSize int `json:"first_size"`
SecondSize int `json:"second_size"`
Statistic float64 `json:"mann_whitney_u"`
A12 float64 `json:"a12"`
PValue float64 `json:"p_value"`
HolmPValue float64 `json:"holm_p_value"`
Exact bool `json:"exact"`
}
type analysis struct {
GeneratedAt time.Time `json:"generated_at"`
Outcome string `json:"outcome"`
// Question names the family Holm corrects within. The correction is applied
// across the comparisons of one research question and never across the
// paper, so the family a p-value was adjusted in has to be recorded next to
// it rather than left to the reader to reconstruct.
Question string `json:"question,omitempty"`
HolmFamilySize int `json:"holm_family_size"`
Arms []armSummary `json:"arms"`
LogRank *logRankResult `json:"log_rank"`
Pairwise []pairwiseResult `json:"pairwise"`
Paired *pairedComparison `json:"paired,omitempty"`
Notes []string `json:"notes,omitempty"`
}
const outcomeDescription = "steps to first violation, right-censored at the last step a clean run reached"
func analyse(arms []arm, now time.Time) (analysis, error) {
result, testable, err := baseAnalysis(arms, now)
if err != nil {
return analysis{}, err
}
if len(testable) >= 2 {
result.Pairwise = comparePairs(testable)
result.HolmFamilySize = countCorrected(result.Pairwise)
}
return result, nil
}
// analysePaired is the seed-matched design of the actuation ablation: two arms
// running the same seeds, contrasted seed by seed rather than as two
// independent samples.
func analysePaired(arms []arm, now time.Time) (analysis, error) {
result, testable, err := baseAnalysis(arms, now)
if err != nil {
return analysis{}, err
}
if len(testable) != 2 {
return analysis{}, fmt.Errorf("a paired comparison needs exactly two arms with usable runs, found %d", len(testable))
}
comparison, err := pairArms(testable[0], testable[1])
if err != nil {
return analysis{}, err
}
if comparison.Pairs == 0 {
return analysis{}, fmt.Errorf("arms %q and %q share no seed with a usable run in both",
testable[0].Name, testable[1].Name)
}
if !math.IsNaN(comparison.PValue) {
comparison.HolmPValue = holm([]float64{comparison.PValue})[0]
result.HolmFamilySize = 1
}
result.Paired = &comparison
return result, nil
}
func baseAnalysis(arms []arm, now time.Time) (analysis, []arm, error) {
result := analysis{GeneratedAt: now, Outcome: outcomeDescription}
for _, current := range arms {
result.Arms = append(result.Arms, summarize(current))
}
var testable []arm
for _, current := range arms {
if len(current.observations()) > 0 {
testable = append(testable, current)
}
}
if len(testable) < len(arms) {
result.Notes = append(result.Notes,
"arms with no usable runs are reported but left out of the log-rank test and the pairwise comparisons")
}
if err := sameBudget(testable); err != nil {
return analysis{}, nil, err
}
if len(testable) >= 2 {
names := make([]string, len(testable))
groups := make([][]observation, len(testable))
for index, current := range testable {
names[index] = current.Name
groups[index] = current.observations()
}
test := logRank(names, groups)
result.LogRank = &test
}
return result, testable, nil
}
// sameBudget refuses arms that were given different exposure. A clean run is
// censored somewhere at or below its arm's budget, so the arm with the larger
// budget carries censored runs the smaller arm could not have produced, and
// every test that ranks the two against each other reads that as the arm
// surviving longer. It is the cross-arm form of what groupArms already refuses
// within one arm.
func sameBudget(arms []arm) error {
for index := 1; index < len(arms); index++ {
if arms[index].Budget != arms[0].Budget {
return fmt.Errorf("arm %q has step budget %d and arm %q has %d: "+
"runs censored at different budgets cannot be compared",
arms[0].Name, arms[0].Budget, arms[index].Name, arms[index].Budget)
}
}
return nil
}
func countCorrected(pairs []pairwiseResult) int {
corrected := 0
for _, pair := range pairs {
if !math.IsNaN(pair.PValue) {
corrected++
}
}
return corrected
}
func comparePairs(arms []arm) []pairwiseResult {
var pairs []pairwiseResult
for first := 0; first < len(arms); first++ {
for second := first + 1; second < len(arms); second++ {
test := rankSum(arms[first].stepTimes(), arms[second].stepTimes())
pairs = append(pairs, pairwiseResult{
First: arms[first].Name,
Second: arms[second].Name,
FirstSize: test.FirstSize,
SecondSize: test.SecondSize,
Statistic: test.Statistic,
A12: test.A12,
PValue: test.PValue,
HolmPValue: math.NaN(),
Exact: test.Exact,
})
}
}
// Holm runs over this one family of comparisons. A comparison whose p-value
// could not be computed is not part of the family and does not shrink the
// correction the others receive.
var family []int
var raw []float64
for index, pair := range pairs {
if math.IsNaN(pair.PValue) {
continue
}
family = append(family, index)
raw = append(raw, pair.PValue)
}
for position, adjusted := range holm(raw) {
pairs[family[position]].HolmPValue = adjusted
}
return pairs
}
func summarize(current arm) armSummary {
summary := armSummary{
Arm: current.Name,
Generator: current.Generator,
Platform: current.Platform,
StepBudget: current.Budget,
Directories: current.Directories,
Recorded: len(current.Runs),
MissingSeeds: current.MissingSeeds,
}
runsPerDefect := map[string]int{}
for _, item := range current.Runs {
if item.ExcludedBecause != "" {
summary.Excluded++
if summary.ExcludedByReason == nil {
summary.ExcludedByReason = map[string]int{}
}
summary.ExcludedByReason[item.ExcludedBecause]++
continue
}
summary.Usable++
summary.TotalSteps += item.Steps
// Steps and actions differ by the steps that chose no action, the steps
// whose action was never dispatched, and the steps the spec's setup
// drove into position. Only what the action generator dispatched
// explored the app, so only that belongs in a per-action rate.
summary.TotalActions += item.Actions
summary.TotalRunHours += float64(item.MonotonicMillis) / float64(time.Hour/time.Millisecond)
if item.ClampedToBudget {
summary.EventsHeldAtBudget++
}
if item.Violated && item.EventStep > item.OriginStep {
summary.EventsDetectedAfterOrigin++
}
if item.Violated {
summary.Violated++
} else {
summary.Censored++
}
distinct := slices.Compact(slices.Sorted(slices.Values(item.ViolatedProperties)))
summary.Detections += len(distinct)
for _, property := range distinct {
runsPerDefect[property]++
}
}
summary.SurvivalCurve = kaplanMeier(current.observations())
if median, ok := medianSurvival(summary.SurvivalCurve); ok {
summary.MedianStepsToFirstViolation = &median
}
if lower, ok := quantileSurvival(summary.SurvivalCurve, 0.25); ok {
summary.FirstQuartileSteps = &lower
}
if upper, ok := quantileSurvival(summary.SurvivalCurve, 0.75); ok {
summary.ThirdQuartileSteps = &upper
}
if summary.Usable > 0 {
rate := float64(summary.Violated) / float64(summary.Usable)
summary.ViolationRate = &rate
}
if summary.TotalActions > 0 {
perThousand := 1000 * float64(summary.Detections) / float64(summary.TotalActions)
summary.DefectsPerThousandActions = &perThousand
}
if summary.TotalRunHours > 0 {
perHour := float64(summary.Detections) / summary.TotalRunHours
summary.DefectsPerHour = &perHour
}
if len(runsPerDefect) > 0 {
summary.DefectRunCounts = runsPerDefect
summary.DistinctDefects = len(runsPerDefect)
for _, count := range runsPerDefect {
if count == 1 {
summary.SingletonDefects++
}
}
fraction := float64(summary.SingletonDefects) / float64(summary.DistinctDefects)
summary.SingletonFraction = &fraction
}
return summary
}