Backend Engineer Take-Home Solutions (Problems 4–6): Go Algorithms, Express API, and Scoreboard System Design

[linhtutkyawdev]

This PR contains complete solutions for the backend engineering assessment, covering:

• Problem 4: Three implementations of “sum to N” in Go
• Problem 5: Task Management API (Express + TypeScript + SQLite)
• Problem 6: Scoreboard service design (live leaderboard + security model)

Each solution focuses on different aspects of backend engineering: algorithms, API design, persistence, and distributed system thinking.

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1. Problem 4 – Sum to N (Golang)

Three distinct approaches are implemented to compute 1..n sum:

Implementations

• Solution A – Gauss Formula

  • Direct arithmetic formula: n(n+1)/2
  • O(1) time, O(1) space
  • Optimal and production-ready for this problem

• Solution B – Iterative Loop

  • Simple accumulation from 1..n
  • O(n) time, O(1) space
  • Baseline readable implementation

• Solution C – Parallel Divide & Conquer

  • Recursive range splitting with controlled goroutines
  • O(n) time, O(p + log n) space
  • Demonstrates concurrency model and workload partitioning

Notes

• Negative input support handled by normalization
• Parallel version includes goroutine throttling to avoid overhead explosion
• Benchmarks included for comparative analysis

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2. Problem 5 – Task Management API (Express + TypeScript + SQLite)

A fully functional CRUD backend with persistence and relational structure.

Core Features

• Task CRUD operations
• Status updates and lifecycle tracking
• Tag management (many-to-many relationship)
• Filtering by status, priority, and tags
• Task event logging (audit trail)
• SQLite persistence with foreign key constraints

Architecture

• Controller → Service → DB separation
• Parameterized SQL queries (SQL injection safe)
• Input validation layer
• Soft delete behavior (with cascade handling for relations)

Database Design

• tasks – core task data
• tags – reusable tags
• task_tags – many-to-many mapping
• task_events – lifecycle audit log

Notes

• SQLite database is bundled for assessment simplicity
• Cascading deletes ensure relational consistency
• Urgency score is computed at runtime
• Designed for easy migration to PostgreSQL

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3. Problem 6 – Scoreboard Service Design (Live Leaderboard System)

A backend design for a real-time Top 10 scoreboard with secure score updates.

System Overview

• Users perform actions → backend increments score
• Live leaderboard updates pushed to clients
• Strong focus on preventing score manipulation

Architecture

• API Server (score validation + orchestration)
• Postgres (source of truth)
• Redis (leaderboard cache using sorted sets)
• WebSocket layer (real-time updates)

Score Update Flow

1. Client performs action

2. Signed request sent (HMAC-based)

3. Backend validates:

   • signature validity
   • timestamp window
   • replay protection (actionId uniqueness)

4. Score update:

   • Postgres update
   • Redis ZSET update

5. Event broadcast via WebSocket

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Security Model

• HMAC request signing (prevents fake score injection)
• Replay protection using actionId deduplication
• Timestamp validation (anti-replay window)
• Rate limiting per user/IP

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Leaderboard Strategy

Redis Sorted Set used for performance:

• ZINCRBY leaderboard <score> <userId>
• ZREVRANGE leaderboard 0 9 WITHSCORES

Provides:

• O(log N) updates
• Fast Top-K queries
• DB remains source of truth

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Real-Time Updates

• Score changes emit events
• WebSocket server pushes updated Top 10 to clients

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Added Artifacts

• README.md for Problem 4 (Go implementations + benchmarks)
• README.md for Task API (Problem 5)
• README.md for Scoreboard design (Problem 6)
• API_SPECIFICATION.md (bonus design detail)
• PROJECT_PLAN.md (bonus planning breakdown)
• Postman collection (Task API testing)

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