git.stevedylan.dev

chore: refactored to larger repo with new plan 3430d6fb

Steve · 2026-03-20 08:05 37 file(s) · +18597 −128

.gitignore → web/.gitignore +0 −0

PLAN.md +117 −128

# Keystroke Dynamics: Full Implementation Plan
# Plan: Standardized Keystroke Dynamics Spec + Reference Library

## Context

The existing Svelte app captures raw digraph timing (6 metrics) and displays averages + a table. It has no persistence, no profile building, no comparison logic, and no human-ness analysis. The goal is to build a complete keystroke dynamics research tool that can:
1. Build typing signatures from free-text sessions
2. Store and manage user profiles
3. Compare sessions against profiles (same-user verification)
4. Score whether a typing session appears human or bot-generated
The existing web app (`web/`) has solid keystroke dynamics logic (capture, aggregation, comparison, humanness scoring) but it's coupled to a Svelte UI. The goal is to extract this into a **language-agnostic spec** + **standalone TypeScript reference library** that other languages (Python, Rust, Go) can implement against. Use cases include school enrollment verification and proving humanness in online writing.

Based on research from the keystroke dynamics survey (arxiv 2303.04605v2), the approach uses digraph aggregation, Scaled Manhattan Distance for comparison, and multi-factor human-ness scoring.
## Decisions Made

**Decisions:**
- Keep legacy Svelte `$:` reactive syntax (no runes migration)
- Build all 4 tabs from the start with placeholders for unbuilt phases
- Track paste events and factor into human-ness analysis
- **Structure**: New `spec/` and `ts/` directories alongside `web/`
- **Metrics**: 4 essential per digraph (holdTime1, holdTime2, pressPress, releasePress); 2 derivable ones are optional
- **Digraphs**: Hybrid — ~30 core English digraphs + any-digraph fallback with min 5 observations
- **Scope**: Full end-to-end — spec document, reference library with tests, and web app refactor

---

## Step 0: Refactor & Extract Components
## Phase 1: Spec Document + JSON Schemas

Extract the monolithic `App.svelte` into a component architecture. Keystroke capture stays at the window level (always active regardless of tab).
### 1.1 Create `spec/SPEC.md`

**Files to create:**
- `src/lib/types.ts` — all TypeScript interfaces (RawDigraph, DigraphAggregation, MetricStats, Profile, ComparisonResult, HumannessResult, etc.)
- `src/lib/utils.ts` — extract `round()`, `avg()`, add `std()` helper
- `src/lib/components/CapturePanel.svelte` — textarea + raw digraph table + JSON export (extracted from App.svelte)
- `src/lib/components/StatsBar.svelte` — the 6-metric averages bar
- `src/lib/components/TabBar.svelte` — tab navigation (Capture | Profile | Compare | Human-ness)
RFC-style markdown document with these sections:

**Refactor `App.svelte`** into orchestrator: holds canonical `digraphs[]` array and `sessionMetadata`, manages tab state, keeps `svelte:window` keydown/keyup handlers so capture works on all tabs.
1. **Introduction & Scope** — what this covers, versioning (`kd-spec/1.0`)
2. **Raw Data Capture** — `KeystrokeEvent` and `RawDigraph` definitions, key normalization rules, excluded keys, `SessionMetadata` shape
3. **Digraph Selection** — core set concept, `spec/digraphs/en.json`, confidence tiers (15+/10-14/5-9/<5 shared core digraphs), minimum observation count (5)
4. **Aggregation** — group by normalized key pair, IQR outlier filtering (k=1.5), compute MetricStats (mean, std w/ Bessel's correction, min, max, count), round to 0.1ms
5. **Identity Comparison** — Scaled Manhattan Distance over 4 metrics, `MAX_METRIC_DISTANCE=3.0`, `MIN_STD_FALLBACK=15.0`, similarity % formula, confidence levels
6. **Humanness Scoring** — 6 weighted sub-scores with exact piecewise-linear breakpoints:
   - timingVariance (0.20): CV of pressPress, range [0.03→0, 0.20→100]
   - correctionRate (0.15): backspace ratio, ideal 2-15%
   - pauseDistribution (0.20): gaps >500ms rate + variance bonus
   - distributionShape (0.15): skewness of pressPress, ideal 0.5-3.0
   - flightTimeNegativity (0.15): % negative releasePress, ideal 10-50%
   - burstPatterns (0.15): burst length mean + CV (burst = consecutive <300ms gaps)
   - Paste penalty when >50% pasted content
   - Verdicts: ≥60 likely_human, 40-59 uncertain, <40 likely_bot
7. **Attestation Object** — JSON shape with specVersion, score, verdict, subScores, sessionStats, optional profileComparison

**Tab setup:** All 4 tabs visible from the start. Non-implemented tabs show a placeholder until their phase is built.
### 1.2 Create JSON Schema files in `spec/schemas/`

**Key gotcha:** Don't conditionally render CapturePanel with `{#if}` — either always render it (hide with CSS) or keep the `svelte:window` bindings in App.svelte. Recommended: keep handlers in App.svelte.
- `raw-keystroke-event.schema.json`
- `raw-digraph.schema.json`
- `session-metadata.schema.json`
- `digraph-aggregation.schema.json`
- `profile.schema.json`
- `comparison-result.schema.json`
- `humanness-result.schema.json`
- `humanness-attestation.schema.json`

---
### 1.3 Create `spec/digraphs/en.json`

## Step 1: Per-Digraph Aggregation & Profile Building
~30 high-frequency English digraphs: th, he, in, er, an, re, on, at, en, nd, ti, es, or, te, of, ed, is, it, al, ar, st, to, nt, ng, se, ha, ou, le, ve, co

**New file: `src/lib/aggregation.ts`**
- `groupDigraphs(digraphs)` — group by normalized key pair (lowercase key1 + key2)
- `computeMetricStats(values[])` — returns `{ mean, std, min, max, count }` for a number array
- `aggregateDigraphs(digraphs)` — for each group, compute MetricStats for all 6 metrics, sort by count descending
---

**Session metadata tracking (add to App.svelte handlers):**
- `totalKeystrokes` — increment on every keydown (not just digraph-forming)
- `backspaceCount` — increment when `e.key === 'Backspace'`
- `pauseCount` — gaps > 500ms between consecutive keydowns (track `lastKeydownTime`)
- `avgTypingSpeed` — chars/min from total keystrokes and session duration
- `sessionDurationMs` — first keydown to last keyup
## Phase 2: Reference TypeScript Library (`ts/`)

**New component: `src/lib/components/ProfileSummary.svelte`**
- Table of top 15 digraphs by frequency: `keys | count | HT1 (mean +/- std) | ... all 6 metrics`
- "Show all" toggle
- Session metadata summary row
### 2.1 Package setup

**Case normalization:** Treat `'A'` and `'a'` as the same key when grouping digraphs. Include Backspace and Enter in aggregation (they carry signature), exclude arrow/navigation keys.
- `ts/package.json` — zero production dependencies, `vitest` for testing
- `ts/tsconfig.json` — ES2023, strict, ESM output
- Exports as both ESM and CJS

---
### 2.2 Source modules (extracted + refactored from `web/src/lib/`)

## Step 2: Profile Storage & Management
| File | Source | Changes |
|---|---|---|
| `ts/src/types.ts` | `web/src/lib/types.ts` | Add `KeystrokeEvent`, `HumannessAttestation`. Remove `TabId`. Make `pressRelease`/`releaseRelease` optional. `DigraphAggregation` uses 4 essential metrics (2 optional). |
| `ts/src/math.ts` | `web/src/lib/utils.ts` | Keep `round`, `std`, `filterOutliers`. Drop `avg` (UI concern). Add proper `mean()` returning number. |
| `ts/src/normalize.ts` | `web/src/lib/aggregation.ts` lines 1-28 | Extract `normalizeKey`, `normalizeDigraphKey`, `EXCLUDED_KEYS`, `shouldExclude`. |
| `ts/src/capture.ts` | `web/src/App.svelte` lines 46-107 | **NEW**: Platform-agnostic `CaptureSession` class with `keyDown(key, timestamp)`, `keyUp(key, timestamp)` → `RawDigraph | null`, `getMetadata()`, `getDigraphs()`, `reset()`. |
| `ts/src/aggregate.ts` | `web/src/lib/aggregation.ts` | `computeMetricStats`, `aggregateDigraphs`. Operate on 4 essential metrics by default. |
| `ts/src/compare.ts` | `web/src/lib/comparison.ts` | `compareSession`. Change `METRIC_KEYS` from 6 to 4. |
| `ts/src/humanness.ts` | `web/src/lib/humanness.ts` | All 6 sub-score functions + `analyzeHumanness`. Consolidate duplicated `computeStd` into `math.ts`. |
| `ts/src/attestation.ts` | NEW | `createAttestation(humanness, digraphs, metadata, comparison?)` → `HumannessAttestation` |
| `ts/src/index.ts` | NEW | Barrel export of public API |

**New file: `src/lib/storage.ts`**
- localStorage key: `"kd_profiles"`
- `saveProfile(profile: Profile)` — JSON stringify, append to stored array
- `loadProfiles(): Profile[]` — parse with try/catch, validate shape
- `deleteProfile(id: string)` — filter and re-save
- `exportProfile(profile: Profile)` — Blob + URL.createObjectURL for JSON file download
- `importProfile(file: File): Profile` — FileReader, JSON.parse, validate
### 2.3 Tests (`ts/tests/`)

**Profile interface stores aggregations (not raw digraphs)** to keep localStorage size manageable.

**New component: `src/lib/components/ProfileManager.svelte`**
- Text input + "Save Profile" button (default name: "Session - {date}")
- List of saved profiles: name, date, digraph count, delete button
- Export button per profile (JSON file download)
- Import button (hidden file input)
- `math.test.ts` — round, std, mean, filterOutliers
- `capture.test.ts` — CaptureSession state machine
- `normalize.test.ts` — key normalization edge cases
- `aggregate.test.ts` — grouping, outlier filtering, metric stats
- `compare.test.ts` — distance calculation, similarity %, confidence levels
- `humanness.test.ts` — each sub-score function + composite scoring
- `fixtures.test.ts` — load spec fixtures, assert outputs match

---

## Step 3: Session Comparison (Scaled Manhattan Distance)
## Phase 3: Test Fixtures (`spec/fixtures/`)

**New file: `src/lib/comparison.ts`**
Generate from the reference implementation using real profile data (`1.json`, `2.json`):

**Algorithm: Scaled Manhattan Distance**
1. Build lookup maps from both session and profile aggregations
2. Find shared digraph types (by normalized key pair)
3. For each shared digraph, for each of 6 metrics:
   - `distance = |mean_session - mean_profile| / std_profile`
   - If `std_profile < epsilon`: use `|mean_session - mean_profile| / max(mean_profile * 0.1, 1.0)` as fallback
4. `overallDistance = sum(all distances) / (sharedCount * 6)`
5. `similarityPercent = max(0, 100 * (1 - overallDistance / 3.0))` — distance of 3 std devs = 0% similar
6. Confidence: `shared >= 15` high, `>= 10` medium, `>= 5` low, `< 5` insufficient
- `aggregation/` — input raw digraphs → expected aggregations
- `comparison/` — input session+profile aggregations → expected ComparisonResult
- `humanness/` — human-like session → expected scores; bot-like session → expected scores
- `math/` — known inputs → expected outputs for filterOutliers, std, etc.

**New component: `src/lib/components/ComparisonView.svelte`**
- Dropdown to select a saved profile
- "Compare" button (disabled if insufficient overlap)
- Results: large similarity %, confidence badge, raw distance score
- Per-digraph breakdown table sorted by distance (worst first), with color-coded match quality bars
- Note in UI: comparing prose vs code sessions for the same user will produce poor matches
Each fixture: `{ input: {...}, expectedOutput: {...} }` with 0.1 tolerance for floats.

---

## Step 4: Human-ness Detection
## Phase 4: Refactor Web App

**New file: `src/lib/humanness.ts`**
### 4.1 Add library dependency

Six sub-scores (0-100 each), combined via weighted average:
Add `ts/` as a workspace or path dependency in `web/package.json`.

| Sub-score | Weight | What it measures | Human signal |
|-----------|--------|-----------------|-------------|
| Timing Variance | 0.20 | CV (std/mean) of pressPress per digraph | Humans CV > 0.15, bots < 0.05 |
| Correction Rate | 0.15 | backspaceCount / totalKeystrokes | Humans 5-15%, zero is suspicious |
| Pause Distribution | 0.20 | Presence/variance of gaps > 500ms, > 1s | Humans have thinking pauses |
| Distribution Shape | 0.15 | Skewness of timing arrays | Human timing is right-skewed (log-normal) |
| Flight Time Negativity | 0.15 | % of digraphs with releasePress < 0 | Humans overlap keys, bots don't |
| Burst Patterns | 0.15 | Variance of "burst" lengths (consecutive digraphs < 300ms gap) | Humans type in bursts of 3-15 keys |
### 4.2 Replace inline modules

**Composite verdict:** score >= 60 "likely human", 40-60 "uncertain", < 40 "likely bot"
| Web file | Action |
|---|---|
| `web/src/lib/types.ts` | Replace with re-exports from `@keystroke-dynamics/core` (or path import) |
| `web/src/lib/utils.ts` | Replace with imports from library's `math.ts`. Keep `avg()` locally (UI helper). |
| `web/src/lib/aggregation.ts` | Replace with imports from library |
| `web/src/lib/comparison.ts` | Replace with imports from library |
| `web/src/lib/humanness.ts` | Replace with imports from library |
| `web/src/lib/storage.ts` | **Keep as-is** — browser-specific, intentionally not in spec |
| `web/src/App.svelte` | Replace inline capture logic (lines 46-107) with `CaptureSession` instance |

**Minimum requirement:** 20 digraphs before computing. Show "keep typing..." below that.

**New component: `src/lib/components/HumannessView.svelte`**
- Large score display (0-100) with verdict text and color
- 6 horizontal bars showing each sub-score with label
- Brief explanation under each bar
### 4.3 Verify

**Paste detection:** Add `on:paste` handler to textarea. Track `pasteCount` and `pastedCharCount` in session metadata. Factor into human-ness score — a session where most content was pasted (high paste ratio vs keystrokes) scores lower. Not inherently disqualifying, but a signal.
- `bun run check` passes
- `bun run dev` works, all tabs functional
- Existing profiles (`1.json`, `2.json`) still load and compare correctly

---

## Implementation Order

```
Step 0 (refactor)  -->  Step 1 (aggregation)  -->  Step 2 (storage)
                                                       |
                                                   Step 3 (comparison)
                                                       |
                                                   Step 4 (human-ness)
```
## Key Files to Modify/Create

Steps 3 and 4 are independent of each other (both depend on Step 1's aggregation). Step 2 must come before Step 3 (comparison needs saved profiles to compare against).
**Create:**
- `spec/SPEC.md`
- `spec/schemas/*.schema.json` (8 files)
- `spec/digraphs/en.json`
- `spec/fixtures/` (fixture JSON files)
- `ts/package.json`, `ts/tsconfig.json`
- `ts/src/*.ts` (9 files)
- `ts/tests/*.test.ts` (7 files)

---
**Modify:**
- `web/src/lib/types.ts` — re-export from library
- `web/src/lib/utils.ts` — import from library, keep `avg` locally
- `web/src/lib/aggregation.ts` — re-export from library
- `web/src/lib/comparison.ts` — re-export from library
- `web/src/lib/humanness.ts` — re-export from library
- `web/src/App.svelte` — use `CaptureSession` class
- `web/package.json` — add library dependency

## File Summary

| File | Action |
|------|--------|
| `src/App.svelte` | Refactor into orchestrator |
| `src/lib/types.ts` | New — all interfaces |
| `src/lib/utils.ts` | New — shared math helpers |
| `src/lib/aggregation.ts` | New — digraph grouping + stats |
| `src/lib/storage.ts` | New — localStorage profile CRUD |
| `src/lib/comparison.ts` | New — Scaled Manhattan Distance |
| `src/lib/humanness.ts` | New — 6-factor human-ness scoring |
| `src/lib/components/CapturePanel.svelte` | New — extracted capture UI |
| `src/lib/components/StatsBar.svelte` | New — extracted stats bar |
| `src/lib/components/TabBar.svelte` | New — tab navigation |
| `src/lib/components/ProfileSummary.svelte` | New — aggregated digraph view |
| `src/lib/components/ProfileManager.svelte` | New — save/load/export profiles |
| `src/lib/components/ComparisonView.svelte` | New — comparison results |
| `src/lib/components/HumannessView.svelte` | New — human-ness score display |
| `src/app.css` | Minor additions for tabs, score displays |
**Keep unchanged:**
- `web/src/lib/storage.ts`
- All Svelte components (they import from `web/src/lib/` which will re-export)

---

## Verification

After each step:
1. `bun run dev` — app loads without errors
2. Type in textarea — digraphs still captured correctly
3. Step 1: Verify aggregated stats appear in Profile tab, digraph grouping works with repeated pairs
4. Step 2: Save a profile, reload page, profile persists. Export/import round-trips correctly.
5. Step 3: Save a profile, type new session, compare — similarity score and per-digraph breakdown appear. Test with same content (should be high similarity) and different content (lower but non-zero for same user).
6. Step 4: Type naturally — should score > 60. Test edge case: very short session shows "keep typing" message.
1. `cd ts && bun test` — all library unit tests pass
2. `cd ts && bun test fixtures.test.ts` — all spec fixtures pass
3. `cd web && bun run check` — TypeScript/Svelte checks pass
4. `cd web && bun run dev` — app runs, type in textarea, verify:
   - Capture tab shows digraphs
   - Profile tab shows aggregations
   - Save a profile, compare against it
   - Humanness tab shows score with all 6 sub-metrics
   - Import `1.json`/`2.json`, comparison still works
5. Validate JSON schemas: `npx ajv validate -s spec/schemas/raw-digraph.schema.json -d spec/fixtures/...`


README.md → web/README.md +0 −0

analyze.ts → web/analyze.ts +0 −0

bun.lock → web/bun.lock +0 −0

index.html → web/index.html +0 −0

package.json → web/package.json +0 −0

public/favicon.svg → web/public/favicon.svg +0 −0

public/icons.svg → web/public/icons.svg +0 −0

src/App.svelte → web/src/App.svelte +0 −0

src/app.css → web/src/app.css +0 −0

src/assets/fonts/CommitMono-400-Regular.otf → web/src/assets/fonts/CommitMono-400-Regular.otf +0 −0

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src/assets/fonts/CommitMono-700-Regular.otf → web/src/assets/fonts/CommitMono-700-Regular.otf +0 −0

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src/assets/hero.png → web/src/assets/hero.png +0 −0

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src/assets/svelte.svg → web/src/assets/svelte.svg +0 −0

src/assets/vite.svg → web/src/assets/vite.svg +0 −0

src/lib/aggregation.ts → web/src/lib/aggregation.ts +0 −0

src/lib/comparison.ts → web/src/lib/comparison.ts +0 −0

src/lib/components/CapturePanel.svelte → web/src/lib/components/CapturePanel.svelte +0 −0

src/lib/components/ComparisonView.svelte → web/src/lib/components/ComparisonView.svelte +0 −0

src/lib/components/HumannessView.svelte → web/src/lib/components/HumannessView.svelte +0 −0

src/lib/components/ProfileManager.svelte → web/src/lib/components/ProfileManager.svelte +0 −0

src/lib/components/ProfileSummary.svelte → web/src/lib/components/ProfileSummary.svelte +0 −0

src/lib/components/StatsBar.svelte → web/src/lib/components/StatsBar.svelte +0 −0

src/lib/components/TabBar.svelte → web/src/lib/components/TabBar.svelte +0 −0

src/lib/humanness.ts → web/src/lib/humanness.ts +0 −0

src/lib/storage.ts → web/src/lib/storage.ts +0 −0

src/lib/types.ts → web/src/lib/types.ts +0 −0

src/lib/utils.ts → web/src/lib/utils.ts +0 −0

src/main.ts → web/src/main.ts +0 −0

svelte.config.js → web/svelte.config.js +0 −0

tsconfig.app.json → web/tsconfig.app.json +0 −0

tsconfig.json → web/tsconfig.json +0 −0

tsconfig.node.json → web/tsconfig.node.json +0 −0

vite.config.ts → web/vite.config.ts +0 −0

web/1.json (added) +9999 −0

1	+	{
2	+	"id": "2d427587-9e82-4783-8f43-399d81618e59",
3	+	"name": "1",
4	+	"createdAt": "2026-03-20T11:30:27.431Z",
5	+	"digraphCount": 595,
6	+	"aggregations": [
7	+	{
8	+	"normalizedKeys": "␣ → t",
9	+	"count": 16,
10	+	"holdTime1": {
11	+	"mean": 64.6,
12	+	"std": 22.7,
13	+	"min": 33.9,
14	+	"max": 108.1,
15	+	"count": 16
16	+	},
17	+	"holdTime2": {
18	+	"mean": 3576.9,
19	+	"std": 13990.5,
20	+	"min": 49.8,
21	+	"max": 56041.2,
22	+	"count": 16
23	+	},
24	+	"pressPress": {
25	+	"mean": -3333,
26	+	"std": 13897.8,
27	+	"min": -55449.2,
28	+	"max": 375.3,
29	+	"count": 16
30	+	},
31	+	"releaseRelease": {
32	+	"mean": 179.2,
33	+	"std": 100.8,
34	+	"min": 101.9,
35	+	"max": 483.9,
36	+	"count": 16
37	+	},
38	+	"pressRelease": {
39	+	"mean": 243.9,
40	+	"std": 116.8,
41	+	"min": 142.4,
42	+	"max": 592,
43	+	"count": 16
44	+	},
45	+	"releasePress": {
46	+	"mean": -3397.7,
47	+	"std": 13909.4,
48	+	"min": -55557.3,
49	+	"max": 279.1,
50	+	"count": 16
51	+	}
52	+	},
53	+	{
54	+	"normalizedKeys": "t → ␣",
55	+	"count": 16,
56	+	"holdTime1": {
57	+	"mean": 80.3,
58	+	"std": 20.3,
59	+	"min": 38,
60	+	"max": 108.2,
61	+	"count": 16
62	+	},
63	+	"holdTime2": {
64	+	"mean": 77.2,
65	+	"std": 20.6,
66	+	"min": 46,
67	+	"max": 116.2,
68	+	"count": 16
69	+	},
70	+	"pressPress": {
71	+	"mean": 134.3,
72	+	"std": 109.3,
73	+	"min": 66.5,
74	+	"max": 524.7,
75	+	"count": 16
76	+	},
77	+	"releaseRelease": {
78	+	"mean": 131.2,
79	+	"std": 110.1,
80	+	"min": 66.4,
81	+	"max": 524.9,
82	+	"count": 16
83	+	},
84	+	"pressRelease": {
85	+	"mean": 211.5,
86	+	"std": 120.5,
87	+	"min": 131.2,
88	+	"max": 632.2,
89	+	"count": 16
90	+	},
91	+	"releasePress": {
92	+	"mean": 54,
93	+	"std": 100.5,
94	+	"min": -12.9,
95	+	"max": 417.4,
96	+	"count": 16
97	+	}
98	+	},
99	+	{
100	+	"normalizedKeys": "e → ␣",
101	+	"count": 14,
102	+	"holdTime1": {
103	+	"mean": 96.7,
104	+	"std": 33.3,
105	+	"min": 36,
106	+	"max": 157.7,
107	+	"count": 14
108	+	},
109	+	"holdTime2": {
110	+	"mean": 86.6,
111	+	"std": 19.3,
112	+	"min": 38,
113	+	"max": 107.9,
114	+	"count": 14
115	+	},
116	+	"pressPress": {
117	+	"mean": 79.1,
118	+	"std": 34.1,
119	+	"min": 19.4,
120	+	"max": 153.2,
121	+	"count": 14
122	+	},
123	+	"releaseRelease": {
124	+	"mean": 69,
125	+	"std": 30.4,
126	+	"min": 24.9,
127	+	"max": 150.1,
128	+	"count": 14
129	+	},
130	+	"pressRelease": {
131	+	"mean": 165.7,
132	+	"std": 35.3,
133	+	"min": 102.6,
134	+	"max": 210,
135	+	"count": 14
136	+	},
137	+	"releasePress": {
138	+	"mean": -17.6,
139	+	"std": 31.6,
140	+	"min": -74.7,
141	+	"max": 43.2,
142	+	"count": 14
143	+	}
144	+	},
145	+	{
146	+	"normalizedKeys": "o → u",
147	+	"count": 11,
148	+	"holdTime1": {
149	+	"mean": 123,
150	+	"std": 31.5,
151	+	"min": 77.2,
152	+	"max": 169.7,
153	+	"count": 11
154	+	},
155	+	"holdTime2": {
156	+	"mean": 93,
157	+	"std": 10.2,
158	+	"min": 74.8,
159	+	"max": 108.1,
160	+	"count": 11
161	+	},
162	+	"pressPress": {
163	+	"mean": 67.7,
164	+	"std": 24,
165	+	"min": 31.7,
166	+	"max": 119.9,
167	+	"count": 11
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8369	+	"count": 1
8370	+	},
8371	+	"releasePress": {
8372	+	"mean": 9.2,
8373	+	"std": 0,
8374	+	"min": 9.2,
8375	+	"max": 9.2,
8376	+	"count": 1
8377	+	}
8378	+	},
8379	+	{
8380	+	"normalizedKeys": "c → e",
8381	+	"count": 1,
8382	+	"holdTime1": {
8383	+	"mean": 70.2,
8384	+	"std": 0,
8385	+	"min": 70.2,
8386	+	"max": 70.2,
8387	+	"count": 1
8388	+	},
8389	+	"holdTime2": {
8390	+	"mean": 147.3,
8391	+	"std": 0,
8392	+	"min": 147.3,
8393	+	"max": 147.3,
8394	+	"count": 1
8395	+	},
8396	+	"pressPress": {
8397	+	"mean": 183.6,
8398	+	"std": 0,
8399	+	"min": 183.6,
8400	+	"max": 183.6,
8401	+	"count": 1
8402	+	},
8403	+	"releaseRelease": {
8404	+	"mean": 260.7,
8405	+	"std": 0,
8406	+	"min": 260.7,
8407	+	"max": 260.7,
8408	+	"count": 1
8409	+	},
8410	+	"pressRelease": {
8411	+	"mean": 330.9,
8412	+	"std": 0,
8413	+	"min": 330.9,
8414	+	"max": 330.9,
8415	+	"count": 1
8416	+	},
8417	+	"releasePress": {
8418	+	"mean": 113.4,
8419	+	"std": 0,
8420	+	"min": 113.4,
8421	+	"max": 113.4,
8422	+	"count": 1
8423	+	}
8424	+	},
8425	+	{
8426	+	"normalizedKeys": "n → c",
8427	+	"count": 1,
8428	+	"holdTime1": {
8429	+	"mean": 97.6,
8430	+	"std": 0,
8431	+	"min": 97.6,
8432	+	"max": 97.6,
8433	+	"count": 1
8434	+	},
8435	+	"holdTime2": {
8436	+	"mean": 70.2,
8437	+	"std": 0,
8438	+	"min": 70.2,
8439	+	"max": 70.2,
8440	+	"count": 1
8441	+	},
8442	+	"pressPress": {
8443	+	"mean": 383.2,
8444	+	"std": 0,
8445	+	"min": 383.2,
8446	+	"max": 383.2,
8447	+	"count": 1
8448	+	},
8449	+	"releaseRelease": {
8450	+	"mean": 355.8,
8451	+	"std": 0,
8452	+	"min": 355.8,
8453	+	"max": 355.8,
8454	+	"count": 1
8455	+	},
8456	+	"pressRelease": {
8457	+	"mean": 453.4,
8458	+	"std": 0,
8459	+	"min": 453.4,
8460	+	"max": 453.4,
8461	+	"count": 1
8462	+	},
8463	+	"releasePress": {
8464	+	"mean": 285.6,
8465	+	"std": 0,
8466	+	"min": 285.6,
8467	+	"max": 285.6,
8468	+	"count": 1
8469	+	}
8470	+	}
8471	+	],
8472	+	"metadata": {
8473	+	"totalKeystrokes": 526,
8474	+	"backspaceCount": 22,
8475	+	"pauseCount": 12,
8476	+	"avgTypingSpeed": 184,
8477	+	"sessionDurationMs": 171524,
8478	+	"pasteCount": 0,
8479	+	"pastedCharCount": 0
8480	+	}
8481	+	}

1		-	# Keystroke Dynamics: Full Implementation Plan
	1	+	# Plan: Standardized Keystroke Dynamics Spec + Reference Library
2	2
3	3		## Context
4	4
5		-	The existing Svelte app captures raw digraph timing (6 metrics) and displays averages + a table. It has no persistence, no profile building, no comparison logic, and no human-ness analysis. The goal is to build a complete keystroke dynamics research tool that can:
6		-	1. Build typing signatures from free-text sessions
7		-	2. Store and manage user profiles
8		-	3. Compare sessions against profiles (same-user verification)
9		-	4. Score whether a typing session appears human or bot-generated
	5	+	The existing web app (`web/`) has solid keystroke dynamics logic (capture, aggregation, comparison, humanness scoring) but it's coupled to a Svelte UI. The goal is to extract this into a language-agnostic spec + standalone TypeScript reference library that other languages (Python, Rust, Go) can implement against. Use cases include school enrollment verification and proving humanness in online writing.
10	6
11		-	Based on research from the keystroke dynamics survey (arxiv 2303.04605v2), the approach uses digraph aggregation, Scaled Manhattan Distance for comparison, and multi-factor human-ness scoring.
	7	+	## Decisions Made
12	8
13		-	Decisions:
14		-	- Keep legacy Svelte `$:` reactive syntax (no runes migration)
15		-	- Build all 4 tabs from the start with placeholders for unbuilt phases
16		-	- Track paste events and factor into human-ness analysis
	9	+	- Structure: New `spec/` and `ts/` directories alongside `web/`
	10	+	- Metrics: 4 essential per digraph (holdTime1, holdTime2, pressPress, releasePress); 2 derivable ones are optional
	11	+	- Digraphs: Hybrid — ~30 core English digraphs + any-digraph fallback with min 5 observations
	12	+	- Scope: Full end-to-end — spec document, reference library with tests, and web app refactor
17	13
18	14		---
19	15
20		-	## Step 0: Refactor & Extract Components
	16	+	## Phase 1: Spec Document + JSON Schemas
21	17
22		-	Extract the monolithic `App.svelte` into a component architecture. Keystroke capture stays at the window level (always active regardless of tab).
	18	+	### 1.1 Create `spec/SPEC.md`
23	19
24		-	Files to create:
25		-	- `src/lib/types.ts` — all TypeScript interfaces (RawDigraph, DigraphAggregation, MetricStats, Profile, ComparisonResult, HumannessResult, etc.)
26		-	- `src/lib/utils.ts` — extract `round()`, `avg()`, add `std()` helper
27		-	- `src/lib/components/CapturePanel.svelte` — textarea + raw digraph table + JSON export (extracted from App.svelte)
28		-	- `src/lib/components/StatsBar.svelte` — the 6-metric averages bar
29		-	- `src/lib/components/TabBar.svelte` — tab navigation (Capture \| Profile \| Compare \| Human-ness)
	20	+	RFC-style markdown document with these sections:
30	21
31		-	Refactor `App.svelte` into orchestrator: holds canonical `digraphs[]` array and `sessionMetadata`, manages tab state, keeps `svelte:window` keydown/keyup handlers so capture works on all tabs.
	22	+	1. Introduction & Scope — what this covers, versioning (`kd-spec/1.0`)
	23	+	2. Raw Data Capture — `KeystrokeEvent` and `RawDigraph` definitions, key normalization rules, excluded keys, `SessionMetadata` shape
	24	+	3. Digraph Selection — core set concept, `spec/digraphs/en.json`, confidence tiers (15+/10-14/5-9/<5 shared core digraphs), minimum observation count (5)
	25	+	4. Aggregation — group by normalized key pair, IQR outlier filtering (k=1.5), compute MetricStats (mean, std w/ Bessel's correction, min, max, count), round to 0.1ms
	26	+	5. Identity Comparison — Scaled Manhattan Distance over 4 metrics, `MAX_METRIC_DISTANCE=3.0`, `MIN_STD_FALLBACK=15.0`, similarity % formula, confidence levels
	27	+	6. Humanness Scoring — 6 weighted sub-scores with exact piecewise-linear breakpoints:
	28	+	- timingVariance (0.20): CV of pressPress, range [0.03→0, 0.20→100]
	29	+	- correctionRate (0.15): backspace ratio, ideal 2-15%
	30	+	- pauseDistribution (0.20): gaps >500ms rate + variance bonus
	31	+	- distributionShape (0.15): skewness of pressPress, ideal 0.5-3.0
	32	+	- flightTimeNegativity (0.15): % negative releasePress, ideal 10-50%
	33	+	- burstPatterns (0.15): burst length mean + CV (burst = consecutive <300ms gaps)
	34	+	- Paste penalty when >50% pasted content
	35	+	- Verdicts: ≥60 likely_human, 40-59 uncertain, <40 likely_bot
	36	+	7. Attestation Object — JSON shape with specVersion, score, verdict, subScores, sessionStats, optional profileComparison
32	37
33		-	Tab setup: All 4 tabs visible from the start. Non-implemented tabs show a placeholder until their phase is built.
	38	+	### 1.2 Create JSON Schema files in `spec/schemas/`
34	39
35		-	Key gotcha: Don't conditionally render CapturePanel with `{#if}` — either always render it (hide with CSS) or keep the `svelte:window` bindings in App.svelte. Recommended: keep handlers in App.svelte.
	40	+	- `raw-keystroke-event.schema.json`
	41	+	- `raw-digraph.schema.json`
	42	+	- `session-metadata.schema.json`
	43	+	- `digraph-aggregation.schema.json`
	44	+	- `profile.schema.json`
	45	+	- `comparison-result.schema.json`
	46	+	- `humanness-result.schema.json`
	47	+	- `humanness-attestation.schema.json`
36	48
37		-	---
	49	+	### 1.3 Create `spec/digraphs/en.json`
38	50
39		-	## Step 1: Per-Digraph Aggregation & Profile Building
	51	+	~30 high-frequency English digraphs: th, he, in, er, an, re, on, at, en, nd, ti, es, or, te, of, ed, is, it, al, ar, st, to, nt, ng, se, ha, ou, le, ve, co
40	52
41		-	New file: `src/lib/aggregation.ts`
42		-	- `groupDigraphs(digraphs)` — group by normalized key pair (lowercase key1 + key2)
43		-	- `computeMetricStats(values[])` — returns `{ mean, std, min, max, count }` for a number array
44		-	- `aggregateDigraphs(digraphs)` — for each group, compute MetricStats for all 6 metrics, sort by count descending
	53	+	---
45	54
46		-	Session metadata tracking (add to App.svelte handlers):
47		-	- `totalKeystrokes` — increment on every keydown (not just digraph-forming)
48		-	- `backspaceCount` — increment when `e.key === 'Backspace'`
49		-	- `pauseCount` — gaps > 500ms between consecutive keydowns (track `lastKeydownTime`)
50		-	- `avgTypingSpeed` — chars/min from total keystrokes and session duration
51		-	- `sessionDurationMs` — first keydown to last keyup
	55	+	## Phase 2: Reference TypeScript Library (`ts/`)
52	56
53		-	New component: `src/lib/components/ProfileSummary.svelte`
54		-	- Table of top 15 digraphs by frequency: `keys \| count \| HT1 (mean +/- std) \| ... all 6 metrics`
55		-	- "Show all" toggle
56		-	- Session metadata summary row
	57	+	### 2.1 Package setup
57	58
58		-	Case normalization: Treat `'A'` and `'a'` as the same key when grouping digraphs. Include Backspace and Enter in aggregation (they carry signature), exclude arrow/navigation keys.
	59	+	- `ts/package.json` — zero production dependencies, `vitest` for testing
	60	+	- `ts/tsconfig.json` — ES2023, strict, ESM output
	61	+	- Exports as both ESM and CJS
59	62
60		-	---
	63	+	### 2.2 Source modules (extracted + refactored from `web/src/lib/`)
61	64
62		-	## Step 2: Profile Storage & Management
	65	+	\| File \| Source \| Changes \|
	66	+	\|---\|---\|---\|
	67	+	\| `ts/src/types.ts` \| `web/src/lib/types.ts` \| Add `KeystrokeEvent`, `HumannessAttestation`. Remove `TabId`. Make `pressRelease`/`releaseRelease` optional. `DigraphAggregation` uses 4 essential metrics (2 optional). \|
	68	+	\| `ts/src/math.ts` \| `web/src/lib/utils.ts` \| Keep `round`, `std`, `filterOutliers`. Drop `avg` (UI concern). Add proper `mean()` returning number. \|
	69	+	\| `ts/src/normalize.ts` \| `web/src/lib/aggregation.ts` lines 1-28 \| Extract `normalizeKey`, `normalizeDigraphKey`, `EXCLUDED_KEYS`, `shouldExclude`. \|
	70	+	\| `ts/src/capture.ts` \| `web/src/App.svelte` lines 46-107 \| NEW: Platform-agnostic `CaptureSession` class with `keyDown(key, timestamp)`, `keyUp(key, timestamp)` → `RawDigraph \| null`, `getMetadata()`, `getDigraphs()`, `reset()`. \|
	71	+	\| `ts/src/aggregate.ts` \| `web/src/lib/aggregation.ts` \| `computeMetricStats`, `aggregateDigraphs`. Operate on 4 essential metrics by default. \|
	72	+	\| `ts/src/compare.ts` \| `web/src/lib/comparison.ts` \| `compareSession`. Change `METRIC_KEYS` from 6 to 4. \|
	73	+	\| `ts/src/humanness.ts` \| `web/src/lib/humanness.ts` \| All 6 sub-score functions + `analyzeHumanness`. Consolidate duplicated `computeStd` into `math.ts`. \|
	74	+	\| `ts/src/attestation.ts` \| NEW \| `createAttestation(humanness, digraphs, metadata, comparison?)` → `HumannessAttestation` \|
	75	+	\| `ts/src/index.ts` \| NEW \| Barrel export of public API \|
63	76
64		-	New file: `src/lib/storage.ts`
65		-	- localStorage key: `"kd_profiles"`
66		-	- `saveProfile(profile: Profile)` — JSON stringify, append to stored array
67		-	- `loadProfiles(): Profile[]` — parse with try/catch, validate shape
68		-	- `deleteProfile(id: string)` — filter and re-save
69		-	- `exportProfile(profile: Profile)` — Blob + URL.createObjectURL for JSON file download
70		-	- `importProfile(file: File): Profile` — FileReader, JSON.parse, validate
	77	+	### 2.3 Tests (`ts/tests/`)
71	78
72		-	Profile interface stores aggregations (not raw digraphs) to keep localStorage size manageable.
73		-
74		-	New component: `src/lib/components/ProfileManager.svelte`
75		-	- Text input + "Save Profile" button (default name: "Session - {date}")
76		-	- List of saved profiles: name, date, digraph count, delete button
77		-	- Export button per profile (JSON file download)
78		-	- Import button (hidden file input)
	79	+	- `math.test.ts` — round, std, mean, filterOutliers
	80	+	- `capture.test.ts` — CaptureSession state machine
	81	+	- `normalize.test.ts` — key normalization edge cases
	82	+	- `aggregate.test.ts` — grouping, outlier filtering, metric stats
	83	+	- `compare.test.ts` — distance calculation, similarity %, confidence levels
	84	+	- `humanness.test.ts` — each sub-score function + composite scoring
	85	+	- `fixtures.test.ts` — load spec fixtures, assert outputs match
79	86
80	87		---
81	88
82		-	## Step 3: Session Comparison (Scaled Manhattan Distance)
	89	+	## Phase 3: Test Fixtures (`spec/fixtures/`)
83	90
84		-	New file: `src/lib/comparison.ts`
	91	+	Generate from the reference implementation using real profile data (`1.json`, `2.json`):
85	92
86		-	Algorithm: Scaled Manhattan Distance
87		-	1. Build lookup maps from both session and profile aggregations
88		-	2. Find shared digraph types (by normalized key pair)
89		-	3. For each shared digraph, for each of 6 metrics:
90		-	- `distance = \|mean_session - mean_profile\| / std_profile`
91		-	- If `std_profile < epsilon`: use `\|mean_session - mean_profile\| / max(mean_profile * 0.1, 1.0)` as fallback
92		-	4. `overallDistance = sum(all distances) / (sharedCount * 6)`
93		-	5. `similarityPercent = max(0, 100 * (1 - overallDistance / 3.0))` — distance of 3 std devs = 0% similar
94		-	6. Confidence: `shared >= 15` high, `>= 10` medium, `>= 5` low, `< 5` insufficient
	93	+	- `aggregation/` — input raw digraphs → expected aggregations
	94	+	- `comparison/` — input session+profile aggregations → expected ComparisonResult
	95	+	- `humanness/` — human-like session → expected scores; bot-like session → expected scores
	96	+	- `math/` — known inputs → expected outputs for filterOutliers, std, etc.
95	97
96		-	New component: `src/lib/components/ComparisonView.svelte`
97		-	- Dropdown to select a saved profile
98		-	- "Compare" button (disabled if insufficient overlap)
99		-	- Results: large similarity %, confidence badge, raw distance score
100		-	- Per-digraph breakdown table sorted by distance (worst first), with color-coded match quality bars
101		-	- Note in UI: comparing prose vs code sessions for the same user will produce poor matches
	98	+	Each fixture: `{ input: {...}, expectedOutput: {...} }` with 0.1 tolerance for floats.
102	99
103	100		---
104	101
105		-	## Step 4: Human-ness Detection
	102	+	## Phase 4: Refactor Web App
106	103
107		-	New file: `src/lib/humanness.ts`
	104	+	### 4.1 Add library dependency
108	105
109		-	Six sub-scores (0-100 each), combined via weighted average:
	106	+	Add `ts/` as a workspace or path dependency in `web/package.json`.
110	107
111		-	\| Sub-score \| Weight \| What it measures \| Human signal \|
112		-	\|-----------\|--------\|-----------------\|-------------\|
113		-	\| Timing Variance \| 0.20 \| CV (std/mean) of pressPress per digraph \| Humans CV > 0.15, bots < 0.05 \|
114		-	\| Correction Rate \| 0.15 \| backspaceCount / totalKeystrokes \| Humans 5-15%, zero is suspicious \|
115		-	\| Pause Distribution \| 0.20 \| Presence/variance of gaps > 500ms, > 1s \| Humans have thinking pauses \|
116		-	\| Distribution Shape \| 0.15 \| Skewness of timing arrays \| Human timing is right-skewed (log-normal) \|
117		-	\| Flight Time Negativity \| 0.15 \| % of digraphs with releasePress < 0 \| Humans overlap keys, bots don't \|
118		-	\| Burst Patterns \| 0.15 \| Variance of "burst" lengths (consecutive digraphs < 300ms gap) \| Humans type in bursts of 3-15 keys \|
	108	+	### 4.2 Replace inline modules
119	109
120		-	Composite verdict: score >= 60 "likely human", 40-60 "uncertain", < 40 "likely bot"
	110	+	\| Web file \| Action \|
	111	+	\|---\|---\|
	112	+	\| `web/src/lib/types.ts` \| Replace with re-exports from `@keystroke-dynamics/core` (or path import) \|
	113	+	\| `web/src/lib/utils.ts` \| Replace with imports from library's `math.ts`. Keep `avg()` locally (UI helper). \|
	114	+	\| `web/src/lib/aggregation.ts` \| Replace with imports from library \|
	115	+	\| `web/src/lib/comparison.ts` \| Replace with imports from library \|
	116	+	\| `web/src/lib/humanness.ts` \| Replace with imports from library \|
	117	+	\| `web/src/lib/storage.ts` \| Keep as-is — browser-specific, intentionally not in spec \|
	118	+	\| `web/src/App.svelte` \| Replace inline capture logic (lines 46-107) with `CaptureSession` instance \|
121	119
122		-	Minimum requirement: 20 digraphs before computing. Show "keep typing..." below that.
123		-
124		-	New component: `src/lib/components/HumannessView.svelte`
125		-	- Large score display (0-100) with verdict text and color
126		-	- 6 horizontal bars showing each sub-score with label
127		-	- Brief explanation under each bar
	120	+	### 4.3 Verify
128	121
129		-	Paste detection: Add `on:paste` handler to textarea. Track `pasteCount` and `pastedCharCount` in session metadata. Factor into human-ness score — a session where most content was pasted (high paste ratio vs keystrokes) scores lower. Not inherently disqualifying, but a signal.
	122	+	- `bun run check` passes
	123	+	- `bun run dev` works, all tabs functional
	124	+	- Existing profiles (`1.json`, `2.json`) still load and compare correctly
130	125
131	126		---
132	127
133		-	## Implementation Order
134		-
135		-	```
136		-	Step 0 (refactor) --> Step 1 (aggregation) --> Step 2 (storage)
137		-	\|
138		-	Step 3 (comparison)
139		-	\|
140		-	Step 4 (human-ness)
141		-	```
	128	+	## Key Files to Modify/Create
142	129
143		-	Steps 3 and 4 are independent of each other (both depend on Step 1's aggregation). Step 2 must come before Step 3 (comparison needs saved profiles to compare against).
	130	+	Create:
	131	+	- `spec/SPEC.md`
	132	+	- `spec/schemas/*.schema.json` (8 files)
	133	+	- `spec/digraphs/en.json`
	134	+	- `spec/fixtures/` (fixture JSON files)
	135	+	- `ts/package.json`, `ts/tsconfig.json`
	136	+	- `ts/src/*.ts` (9 files)
	137	+	- `ts/tests/*.test.ts` (7 files)
144	138
145		-	---
	139	+	Modify:
	140	+	- `web/src/lib/types.ts` — re-export from library
	141	+	- `web/src/lib/utils.ts` — import from library, keep `avg` locally
	142	+	- `web/src/lib/aggregation.ts` — re-export from library
	143	+	- `web/src/lib/comparison.ts` — re-export from library
	144	+	- `web/src/lib/humanness.ts` — re-export from library
	145	+	- `web/src/App.svelte` — use `CaptureSession` class
	146	+	- `web/package.json` — add library dependency
146	147
147		-	## File Summary
148		-
149		-	\| File \| Action \|
150		-	\|------\|--------\|
151		-	\| `src/App.svelte` \| Refactor into orchestrator \|
152		-	\| `src/lib/types.ts` \| New — all interfaces \|
153		-	\| `src/lib/utils.ts` \| New — shared math helpers \|
154		-	\| `src/lib/aggregation.ts` \| New — digraph grouping + stats \|
155		-	\| `src/lib/storage.ts` \| New — localStorage profile CRUD \|
156		-	\| `src/lib/comparison.ts` \| New — Scaled Manhattan Distance \|
157		-	\| `src/lib/humanness.ts` \| New — 6-factor human-ness scoring \|
158		-	\| `src/lib/components/CapturePanel.svelte` \| New — extracted capture UI \|
159		-	\| `src/lib/components/StatsBar.svelte` \| New — extracted stats bar \|
160		-	\| `src/lib/components/TabBar.svelte` \| New — tab navigation \|
161		-	\| `src/lib/components/ProfileSummary.svelte` \| New — aggregated digraph view \|
162		-	\| `src/lib/components/ProfileManager.svelte` \| New — save/load/export profiles \|
163		-	\| `src/lib/components/ComparisonView.svelte` \| New — comparison results \|
164		-	\| `src/lib/components/HumannessView.svelte` \| New — human-ness score display \|
165		-	\| `src/app.css` \| Minor additions for tabs, score displays \|
	148	+	Keep unchanged:
	149	+	- `web/src/lib/storage.ts`
	150	+	- All Svelte components (they import from `web/src/lib/` which will re-export)
166	151
167	152		---
168	153
169	154		## Verification
170	155
171		-	After each step:
172		-	1. `bun run dev` — app loads without errors
173		-	2. Type in textarea — digraphs still captured correctly
174		-	3. Step 1: Verify aggregated stats appear in Profile tab, digraph grouping works with repeated pairs
175		-	4. Step 2: Save a profile, reload page, profile persists. Export/import round-trips correctly.
176		-	5. Step 3: Save a profile, type new session, compare — similarity score and per-digraph breakdown appear. Test with same content (should be high similarity) and different content (lower but non-zero for same user).
177		-	6. Step 4: Type naturally — should score > 60. Test edge case: very short session shows "keep typing" message.
	156	+	1. `cd ts && bun test` — all library unit tests pass
	157	+	2. `cd ts && bun test fixtures.test.ts` — all spec fixtures pass
	158	+	3. `cd web && bun run check` — TypeScript/Svelte checks pass
	159	+	4. `cd web && bun run dev` — app runs, type in textarea, verify:
	160	+	- Capture tab shows digraphs
	161	+	- Profile tab shows aggregations
	162	+	- Save a profile, compare against it
	163	+	- Humanness tab shows score with all 6 sub-metrics
	164	+	- Import `1.json`/`2.json`, comparison still works
	165	+	5. Validate JSON schemas: `npx ajv validate -s spec/schemas/raw-digraph.schema.json -d spec/fixtures/...`
	166	+