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# 🔥 GameService Roast: `apps/api/src/services/gameService.ts`
> *"It works on my machine" is not a scalability strategy.*
**Project:** lila — Vocabulary Trainer
**File Roasted:** `gameService.ts`
**Date:** $(date)
**Roaster:** Qwen3.6
---
## 📋 Executive Summary
| Metric | Score | Notes |
| ------------- | -------- | ---------------------------------------------------- |
| Code Quality | 8/10 | Clean layering, good types, consistent style |
| Correctness | 6/10 | Race condition + N+1 query are critical |
| Test Coverage | 7/10 | Good happy-path tests, missing concurrency tests |
| Scalability | 5/10 | Will choke at ~100 concurrent users without fixes |
| **Overall** | **7/10** | Solid foundation, but fix the footguns before launch |
---
## 🚨 Critical Issues (Fix Before Production)
### 1. Race Condition: Lost Update in `evaluateAnswer`
**Location:** `gameService.ts:45-58` + `InMemoryGameSessionStore.ts:update()`
// Current flow (VULNERABLE):
const session = await store.get(submission.sessionId); // READ
const updatedAnswers = new Map(session.answers); // MODIFY (local copy)
updatedAnswers.delete(submission.questionId);
await store.update(submission.sessionId, { answers: updatedAnswers }); // WRITE
The Attack:
Client submits answer A and answer B for the same question (network retry, bug, or malice)
Both requests read the same session.answers Map (question still present)
Both delete the question from their local copy
Both write back → second write overwrites first
Result: One answer is silently lost, session state desyncs
Why Tests Missed It: Vitest runs tests synchronously. Race conditions require deliberate concurrency testing.
Fix Options:
// Option A: Add atomic operation to store interface
interface GameSessionStore {
deleteAnswer(sessionId: string, questionId: string): Promise<boolean>;
}
// Option B: Use Valkey Lua script for atomic read-modify-write
// Option C: Optimistic locking with version numbers
Priority: 🔴 CRITICAL — Data integrity issue
2. N+1 Query: Database Performance Bomb
Location: gameService.ts:24-26 + termModel.ts:getDistractors()
// For each of N terms, we call getDistractors():
const questions: GameQuestion[] = await Promise.all(
terms.map(async (term) => {
const distractorTexts = await getDistractors(term.termId, ...); // 🚩 N queries!
})
);
Impact Analysis:
Rounds
DB Queries
At 50 concurrent users
3
1 + 3 = 4
200 queries/min
10
1 + 10 = 11
550 queries/min
20
1 + 20 = 21
1,050 queries/min
Each getDistractors() runs:
SELECT text FROM terms
JOIN translations ON ...
WHERE pos = $1 AND difficulty = $2 AND term_id != $3 AND text != $4
ORDER BY RANDOM() LIMIT 6
Fix: Batch Fetch Distractors
// Fetch all distractors in ONE query
const allDistractors = await db
.select({ termId: terms.id, text: translations.text })
.from(terms)
.innerJoin(translations, /* ... */)
.where(and(
eq(terms.pos, pos),
eq(translations.difficulty, difficulty),
inArray(terms.id, termIds), // Batch!
))
.limit(DISTRACTOR_FETCH_COUNT * termIds.length);
// Group by termId in JS, then slice to 3 unique distractors per term
const distractorsByTerm = groupByTermId(allDistractors);
Priority: 🔴 CRITICAL — Performance/scalability issue
3. Error Handling Inconsistency
Location: gameService.ts:33-36
if (uniqueDistractors.length < 3) {
throw new Error(`Not enough unique distractors for term: ${term.targetText}`); // 🚩
}
Problem: Raw Error bypasses your errorHandler middleware:
No HTTP status mapping (defaults to 500)
No structured logging
Inconsistent API responses
Fix:
import { UnprocessableEntityError } from "../errors/AppError.js";
if (uniqueDistractors.length < 3) {
logger.warn({ termId: term.termId, uniqueCount: uniqueDistractors.length },
"insufficient_distractors");
throw new UnprocessableEntityError(
`Not enough unique distractors for term: ${term.targetText}`
);
}
Priority: 🟡 HIGH — Observability & UX issue
⚠️ High-Severity Smells
4. Code Duplication: Singleplayer vs Multiplayer
Compare: gameService.ts vs multiplayerGameService.ts
// gameService.ts
const optionTexts = [term.targetText, ...uniqueDistractors.slice(0, 3)];
const shuffledTexts = shuffleArray(optionTexts);
const correctOptionId = shuffledTexts.indexOf(term.targetText);
// multiplayerGameService.ts (lines 35-45)
const optionTexts = [correctAnswer.targetText, ...distractorTexts];
const shuffledTexts = shuffle(optionTexts); // Different function, same logic!
const correctOptionId = shuffledTexts.indexOf(correctAnswer.targetText);
Risks:
Fix shuffle bias in one place, forget the other
Add new option type (e.g., etymology hint), update one service only
Harder to test core game logic in isolation
Fix: Extract pure function to @lila/shared or new @lila/game-logic:
// packages/shared/src/game-logic.ts
export const buildQuestionOptions = (
correctAnswer: string,
distractors: string[],
optionCount: number = 4
): { options: AnswerOption[]; correctOptionId: number } => {
const uniqueDistractors = [...new Set(distractors.filter(d => d !== correctAnswer))];
const optionTexts = [correctAnswer, ...uniqueDistractors.slice(0, optionCount - 1)];
const shuffled = shuffleSecure(optionTexts);
const correctOptionId = shuffled.indexOf(correctAnswer);
return {
options: shuffled.map((text, idx) => ({ optionId: idx, text })),
correctOptionId
};
};
Priority: 🟡 HIGH — Maintainability issue
5. Shuffle Bias: Math.random() Trap
Location: utils.ts:shuffleArray() + multiplayerGameService.ts:shuffle()
export const shuffleArray = <T>(array: T[]): T[] => {
for (let i = result.length - 1; i > 0; i--) {
const j = Math.floor(Math.random() * (i + 1)); // 🚩 Modulo bias + non-crypto RNG
// ...
}
};
The Math:
Math.random() has ~53 bits of entropy (fine for vocab)
Math.floor(rand * n) has modulo bias when n isn't a power of 2
For n=4: bias is ~0.01% (tiny, but non-zero)
When It Matters:
Competitive leaderboards ("option 0 is correct 26% of the time")
Achievement systems based on answer patterns
Security-sensitive features (not applicable here, but principle matters)
Fix (if needed):
import { randomBytes } from "crypto";
const shuffleSecure = <T>(array: T[]): T[] => {
const result = [...array];
for (let i = result.length - 1; i > 0; i--) {
// Use crypto.getRandomValues for better randomness
const rand = randomBytes(4).readUInt32LE(0);
const j = rand % (i + 1);
[result[i], result[j]] = [result[j], result[i]];
}
return result;
};
Priority: 🟢 LOW — Document tradeoff and move on for now
6. Test Coverage Gaps
File: gameService.test.ts
✅ Well Tested:
Happy path: session creation, answer evaluation
Edge cases: duplicate distractors, empty results, invalid inputs
Error propagation from DB layer
❌ Missing Tests:
// 1. Concurrency test (race condition)
it("rejects duplicate answers for same question under concurrent load", async () => {
const session = await createGameSession(validRequest, store, "user-1");
const question = session.questions[0]!;
// Submit two answers simultaneously
const [result1, result2] = await Promise.allSettled([
evaluateAnswer({ sessionId, questionId, selectedOptionId: 0 }, store, "user-1"),
evaluateAnswer({ sessionId, questionId, selectedOptionId: 1 }, store, "user-1"),
]);
// Exactly one should succeed, one should throw ConflictError
expect([result1, result2].filter(r => r.status === "fulfilled")).toHaveLength(1);
});
// 2. TTL expiration test
it("deletes session after TTL expires", async () => {
vi.useFakeTimers();
const session = await createGameSession(validRequest, store, "user-1");
vi.advanceTimersByTime(31 * 60 * 1000); // 31 minutes
await expect(store.get(session.sessionId)).resolves.toBeNull();
});
// 3. Distractor fallback strategy test
it("uses fallback when <3 unique distractors available", async () => {
mockGetDistractors.mockResolvedValue(["same", "same", "same", "same"]);
// Should either: (a) fetch from broader pool, or (b) reduce rounds gracefully
});
Priority: 🟡 HIGH — Prevents regression on critical fixes
🧼 Code Quality Nitpicks
7. Magic Numbers
// gameService.ts:52
await store.create(sessionId, {...}, 30 * 60 * 1000); // What is this?
// termModel.ts:65
.limit(count); // count=6, but why?
// shared/schemas/game.ts:15
optionId: z.number().int().min(0).max(3), // Why 4 options?
Fix: Centralize in @lila/shared/constants.ts:
export const GAME_SESSION_TTL_MS = 30 * 60 * 1000;
export const DISTRACTOR_FETCH_COUNT = 6;
export const GAME_OPTION_COUNT = 4;
export const MIN_UNIQUE_DISTRACTORS = 3;
8. Mutable Reference Leakage
Location: InMemoryGameSessionStore.ts:get()
get(sessionId: string): Promise<GameSessionData | null> {
return Promise.resolve(entry.data); // 🚩 Returns mutable reference to internal state
}
Risk: Any code that does session.answers.delete(...) mutates the store's internal Map directly.
Fix:
// Option A: Deep clone (simple, works for this data shape)
return Promise.resolve(structuredClone(entry.data));
// Option B: Return readonly view (TypeScript-only protection)
return Promise.resolve(entry.data as Readonly<GameSessionData>);
// Option C: Use immutable data structures (overkill for now)
9. Zero Observability
Problem: No logging, no metrics. You're flying blind in production.
Minimal Fix (5 minutes):
// apps/api/src/lib/logger.ts
import pino from "pino";
export const logger = pino({
level: process.env.LOG_LEVEL || "info",
transport: process.env.NODE_ENV === "production"
? { target: "pino-pretty" }
: undefined
});
// In gameService.ts:
import { logger } from "../lib/logger.js";
logger.info(
{ userId, sourceLang, targetLang, termCount: terms.length },
"game_session_created"
);
logger.debug(
{ sessionId, questionId, isCorrect, responseTimeMs },
"answer_evaluated"
);
Bonus: Export a Prometheus histogram for game_service_duration_seconds.
10. ORDER BY RANDOM() Time Bomb
Location: termModel.ts:getGameTerms() + getDistractors()
.orderBy(sql`RANDOM()`) // 🚩 Fine for 10k rows, slow for 1M
The Comment Admits It:
// TODO(post-mvp): ORDER BY RANDOM() sorts the entire filtered result set...
Reality Check: "Post-MVP" never comes without a ticket.
Fix Options:
-- Option A: Pre-computed random_seed column (updated nightly)
WHERE ... AND random_seed >= random()
ORDER BY random_seed
LIMIT $1
-- Option B: TABLESAMPLE for approximate sampling (Postgres 9.5+)
FROM terms TABLESAMPLE SYSTEM(10)
WHERE ...
LIMIT $1
-- Option C: Random offset (simple, but still scans)
OFFSET floor(random() * (SELECT count(*) FROM terms WHERE ...))
Action: Add a ticket to documentation/tickets/t00009.md now.