String Questions at Swiggy: What to Expect

String manipulation is a core skill tested in Swiggy's technical interviews, with 9 out of their 41 most frequent questions focusing on this domain. This emphasis isn't arbitrary. Swiggy's platform—handling restaurant names, dish items, user addresses, search queries, and order tracking IDs—is fundamentally built on processing and transforming textual data. Efficient string algorithms directly impact search relevance, data parsing from logs, address validation, and ensuring smooth user interactions. Mastering these questions demonstrates your ability to handle the real-world, text-heavy data pipelines that power a delivery super-app.

What to Expect — Types of Problems

Swiggy's string problems typically assess three key competencies:

1. Pattern Matching & Searching: Questions often involve finding or validating patterns within text. This includes implementing standard algorithms like KMP for efficient substring search, or solving problems related to regular expression matching (e.g., wildcard or simple regex matching).
2. String Transformation & Parsing: Given the nature of processing orders and addresses, you can expect problems that require manipulating string formats. Common tasks include converting strings (e.g., ZigZag conversion), parsing complex strings (like serialized data), or solving anagrams and group-anagrams problems which are frequent.
3. Efficient String Operations: Many problems test your ability to perform operations with optimal time and space complexity on strings. This includes finding the longest substring without repeating characters (a classic sliding window problem), palindrome-related questions (longest palindromic substring), or string compression.

The problems are designed to evaluate not just if you can solve them, but if you can do so efficiently at scale—a critical consideration for Swiggy's high-throughput systems.

How to Prepare — Study Tips with One Code Example

Focus on understanding fundamental patterns rather than memorizing solutions. The Sliding Window technique is indispensable for substring problems, and the Two Pointers approach is crucial for in-place manipulations and palindrome checks. Always analyze the time and space complexity of your solution and be prepared to optimize.

For example, the "Longest Substring Without Repeating Characters" problem perfectly illustrates the sliding window pattern. The goal is to find the length of the longest substring containing all unique characters.

def length_of_longest_substring(s: str) -> int:
    char_set = set()
    left = 0
    max_len = 0

    for right in range(len(s)):
        while s[right] in char_set:
            char_set.remove(s[left])
            left += 1
        char_set.add(s[right])
        max_len = max(max_len, right - left + 1)
    return max_len

The algorithm maintains a window (left to right) of unique characters using a set. It expands the window by moving right and shrinks it from the left when a duplicate is found, efficiently tracking the maximum window size.

Recommended Practice Order

Tackle problems in this sequence to build competency progressively:

1. Start with basic anagram and palindrome checks to warm up.
2. Move to core pattern algorithms: Implement Sliding Window (like the example above) and Two Pointers (e.g., reverse a string, valid palindrome II).
3. Practice Pattern Matching fundamentals, such as implementing strStr() or basic regex matching.
4. Finally, solve more complex problems that combine concepts, like ZigZag Conversion or String to Integer (atoi), which test careful parsing and transformation logic.

Consistent practice with this progression will solidify the patterns needed for Swiggy's interviews.

Practice String at Swiggy