Dynamic Programming Questions at TikTok: What to Expect

Dynamic Programming (DP) is a critical skill for acing technical interviews at TikTok. With 69 DP questions in their problem bank, it's a core topic for software engineering roles, especially those involving large-scale systems, video processing, and recommendation algorithms. DP tests your ability to break down complex problems into simpler subproblems and optimize for efficiency—skills directly applicable to building scalable features for over a billion users. Mastering it signals you can handle the performance and optimization challenges inherent in a high-traffic platform.

What to Expect — Types of Problems

TikTok's DP questions often focus on practical patterns rather than purely academic puzzles. You can expect a strong emphasis on:

• 1D/2D Dynamic Programming: These are the most common. Problems involve sequences (like strings or arrays) or grids, requiring you to define a state (e.g., dp[i] or dp[i][j]) and a transition relation.
• Knapsack Variants: Questions about resource allocation, feature selection, or optimization within constraints frequently map to knapsack problems (0/1 or unbounded).
• String/Sequence DP: Problems like "Longest Common Subsequence," "Edit Distance," or "Palindrome" variations are highly relevant for tasks involving text processing, data deduplication, or comparing user-generated content.
• DP on Intervals or Trees: While slightly less frequent, these appear for roles dealing with more complex data structures, testing your ability to define states on sub-intervals or subtrees.

The problems are designed to assess not just your memorization of solutions, but your ability to derive the DP state and transition from a novel problem statement.

How to Prepare — Study Tips with One Code Example

Start by internalizing the core DP process: 1) Define the state, 2) Establish the base case(s), 3) Formulate the recurrence relation, and 4) Determine the final answer's location. Practice by drawing out the state table for small examples before coding.

A fundamental pattern is the "Fibonacci-style" 1D DP, which extends to problems like climbing stairs or counting ways. Here is the tabulation (bottom-up) approach, which is often more intuitive and performant than recursion with memoization.

def climb_stairs(n: int) -> int:
    if n <= 2:
        return n
    dp = [0] * (n + 1)
    dp[1] = 1  # Base case: 1 way to reach step 1
    dp[2] = 2  # Base case: 2 ways to reach step 2
    for i in range(3, n + 1):
        # Recurrence: Ways to reach i = ways to reach (i-1) + ways to reach (i-2)
        dp[i] = dp[i - 1] + dp[i - 2]
    return dp[n]

Recommended Practice Order

Do not attempt TikTok's hardest DP questions first. Build competence systematically:

1. Foundation: Master classic problems (Fibonacci, Climbing Stairs, Coin Change, 0/1 Knapsack, Longest Common Subsequence). Understand both memoization and tabulation.
2. Core Patterns: Practice grouped problems: all "string DP" questions, then all "2D grid DP" questions. This helps you recognize patterns.
3. TikTok-Specific: Filter the company's problem list by frequency and start with the most common "Easy" and "Medium" tagged DP questions.
4. Simulation: Finally, practice less frequent "Hard" problems and conduct timed mock interviews focusing on explaining your DP state definition aloud.

Practice Dynamic Programming at TikTok