Data Structures and Algorithms

DSA Interview Questions

Most Asked Interview Questions at Google (2025 Edition)

Landing a role at Google is a dream for many aspiring software engineers, but the interview process can be daunting. With competition fiercer than ever in 2025, understanding the most frequently asked questions—and how to tackle them—can give you a significant edge. This comprehensive guide dives deep into real questions drawn from recent interviews, providing in-depth explanations, strategies, and actionable insights to help you prepare effectively. Before we dive in, to stay updated with free resources and course alerts tailored for tech interview prep, sign up for our newsletter here.

Google’s Interview Process in 2025: What to Expect

Google’s hiring process for software engineers remains rigorous, focusing on problem-solving, technical depth, and cultural fit. Based on recent candidate experiences and official guidelines, the process typically includes:

Application and Resume Screening: Google receives millions of applications annually, so tailor your resume to highlight relevant projects and skills. Networking via LinkedIn or events can help you stand out.
Online Assessment: A 60-90 minute coding test on platforms like HackerRank, often involving 2-3 medium-to-hard problems on data structures and algorithms (DSA).
Phone/Virtual Screens: 1-2 rounds, 45 minutes each, emphasizing DSA coding in a shared doc without auto-complete.
Onsite/Virtual Loop: 4-6 interviews, covering coding (2-3 rounds), system design (for L4+ levels), behavioral/Googleyness, and sometimes leadership or domain-specific questions.
Hiring Committee Review: Independent evaluation based on feedback, followed by team matching.

In 2025, there’s an increased emphasis on AI/ML integration, scalability, and ethical considerations in questions, reflecting Google’s push in these areas. Expect hybrid formats, with some onsite for senior roles. The process takes 4-8 weeks, with a 4-5% acceptance rate from initial applications.

To build a strong foundation in DSA, which forms the core of technical rounds, consider our specialized DSA course.

Behavioral Interview Questions: Showcasing Your Googleyness

Google values “Googleyness”—a mix of curiosity, ethics, and teamwork. Behavioral questions assess this using the SPSIL framework (Situation, Problem, Solution, Impact, Lessons). Here are some of the most asked, with in-depth guidance based on real interviews.

Why Do You Want to Work at Google?

This is often the opener. Interviewers want genuine passion tied to Google’s mission.

In-Depth Answer: Structure your response around 2-3 specific reasons. For example: “Google’s commitment to organizing the world’s information resonates with my experience building scalable search tools in my last project at [Company], where I optimized query times by 40%. I’m excited about contributing to products like Search, which impact billions, and the collaborative culture that fosters innovation—something I’ve seen in open-source contributions from Googlers.” Avoid generic answers; personalize with research on recent initiatives like AI advancements.

Tell Me About a Time You Failed at Work

Focus on growth, not the failure itself.

In-Depth Answer: Use SPSIL: “In a previous role (Situation), I led a feature rollout that missed a key edge case, causing a 10% downtime (Problem). I debugged it immediately, implemented automated tests, and rolled out a fix within hours (Solution). This reduced future incidents by 30% (Impact). I learned to prioritize comprehensive testing early, now incorporating it in all sprints (Lessons).” This shows accountability and learning.

What Is Your Favorite Google Product and Why?

Demonstrate product thinking.

In-Depth Answer: Pick one and analyze: “Google Kubernetes Engine (GKE) because it simplifies container orchestration. In my project, I used it to scale a microservices app, reducing deployment time from days to hours. I’d improve it by enhancing auto-scaling for AI workloads, aligning with Google’s cloud strategy.”

Tell Me About a Time You Dealt with Conflict

Highlight resolution skills.

In-Depth Answer: “On a cross-team project (Situation), a colleague’s delayed deliverables blocked progress (Problem). I scheduled a one-on-one, listened to their challenges, and proposed shared tools for better visibility (Solution). We met deadlines, improving team efficiency by 20% (Impact). I learned proactive communication prevents escalation (Lessons).”

Describe a Challenging Technical Problem You Solved

Tie to impact.

In-Depth Answer: “I optimized a database query handling millions of records (Situation), which was timing out (Problem). Using indexing and sharding (Solution), I cut response time by 70% (Impact). This taught me the value of profiling tools (Lessons).”

For more on full-stack skills that complement behavioral prep, explore our web development course.

Coding Interview Questions: Deep Dives into Real Problems

Coding rounds test DSA proficiency. Expect to code on a whiteboard or doc, explaining time/space complexity. Here are 20 frequently asked questions from 2024-2025 interviews, with in-depth explanations, approaches, and sample code (in Python for clarity). Use the framework: Clarify inputs/outputs, plan solution, implement, test edges, optimize.

1. Add Binary (LeetCode Easy)

Question: Given two binary strings a and b, return their sum as a binary string.

In-Depth Answer: Simulate binary addition with carry. Traverse from right to left, adding bits and carry. Time: O(max(len(a), len(b))), Space: O(max(len(a), len(b))).

				
					def addBinary(a: str, b: str) -> str:
    result = []
    carry = 0
    i, j = len(a) - 1, len(b) - 1
    while i >= 0 or j >= 0 or carry:
        total = carry
        if i >= 0:
            total += int(a[i])
            i -= 1
        if j >= 0:
            total += int(b[j])
            j -= 1
        result.append(str(total % 2))
        carry = total // 2
    return ''.join(result[::-1])

Test: addBinary(“11”, “1”) -> “100”. Edge: Empty strings.

2. Valid Mountain Array (LeetCode Easy)

Question: Given an array, return true if it strictly increases then decreases.

In-Depth Answer: Find peak by scanning for increase then decrease. Ensure no plateaus. Time: O(n), Space: O(1).

				
					def validMountainArray(arr: list[int]) -> bool:
    if len(arr) < 3: return False
    i = 1
    while i < len(arr) and arr[i] > arr[i-1]:
        i += 1
    if i == 1 or i == len(arr): return False
    while i < len(arr) and arr[i] < arr[i-1]:
        i += 1
    return i == len(arr)

3. Set Mismatch (LeetCode Easy)

Question: Find duplicate and missing number in [1,n] with one error.

In-Depth Answer: Use math: Sum and sum of squares for identification. Time: O(n), Space: O(1).

				
					
def findErrorNums(nums: list[int]) -> list[int]:
    n = len(nums)
    expected_sum = n * (n + 1) // 2
    actual_sum = sum(nums)
    expected_sq = sum(i**2 for i in range(1, n+1))
    actual_sq = sum(x**2 for x in nums)
    diff = actual_sum - expected_sum
    sq_diff = actual_sq - expected_sq
    dup = (diff + sq_diff // diff) // 2
    missing = dup - diff
    return [dup, missing]

4. Length of Last Word (LeetCode Easy)

Question: Return length of last word in string.

In-Depth Answer: Traverse from end, skip spaces, count chars. Time: O(n), Space: O(1).

python

				
					def lengthOfLastWord(s: str) -> int:
    i = len(s) - 1
    while i >= 0 and s[i] == ' ':
        i -= 1
    length = 0
    while i >= 0 and s[i] != ' ':
        length += 1
        i -= 1
    return length

5. Monotonic Array (LeetCode Easy)

Question: Check if array is entirely non-increasing or non-decreasing.

In-Depth Answer: Track direction, check consistency. Time: O(n), Space: O(1).

				
					
def isMonotonic(nums: list[int]) -> bool:
    increasing = decreasing = True
    for i in range(1, len(nums)):
        if nums[i] < nums[i-1]: increasing = False
        if nums[i] > nums[i-1]: decreasing = False
    return increasing or decreasing

6. Find the Difference (LeetCode Easy)

Question: Find added letter in shuffled string t from s.

In-Depth Answer: XOR all chars. Time: O(n), Space: O(1).

				
					def findTheDifference(s: str, t: str) -> str:
    res = 0
    for c in s + t:
        res ^= ord(c)
    return chr(res)

7. Binary Tree Paths (LeetCode Easy)

Question: Return all root-to-leaf paths as strings.

In-Depth Answer: DFS recursion, build path string. Time: O(n), Space: O(h) for height h.

				
					class TreeNode:
    def __init__(self, val=0, left=None, right=None):
        self.val = val
        self.left = left
        self.right = right

def binaryTreePaths(root: TreeNode) -> list[str]:
    def dfs(node, path, res):
        if not node: return
        path += str(node.val)
        if not node.left and not node.right:
            res.append(path)
            return
        path += '->'
        dfs(node.left, path, res)
        dfs(node.right, path, res)
    res = []
    dfs(root, '', res)
    return res

8. Merge Strings Alternately (LeetCode Easy)

Question: Merge two strings alternately.

In-Depth Answer: Use two pointers, append remaining. Time: O(m+n), Space: O(m+n).

				
					
def mergeAlternately(word1: str, word2: str) -> str:
    res = []
    i = 0
    while i < len(word1) or i < len(word2):
        if i < len(word1):
            res.append(word1[i])
        if i < len(word2):
            res.append(word2[i])
        i += 1
    return ''.join(res)

9. 2 Keys Keyboard (LeetCode Medium)
Question: Min steps to get n ‘A’s using copy/paste.
In-Depth Answer: DP: dp[i] = min steps for i ‘A’s. Factorization insight for primes. Time: O(n^2), Space: O(n).

				
					def minSteps(n: int) -> int:
    dp = [0] * (n + 1)
    for i in range(2, n + 1):
        dp[i] = i
        for j in range(1, i // 2 + 1):
            if i % j == 0:
                dp[i] = min(dp[i], dp[j] + i // j)
    return dp[n]

10. Arithmetic Slices (LeetCode Medium)
Question: Count arithmetic subarrays.
In-Depth Answer: Track current slice length. Time: O(n), Space: O(1).

				
					def numberOfArithmeticSlices(nums: list[int]) -> int:
    if len(nums) < 3: return 0
    res = 0
    cur = 0
    diff = nums[1] - nums[0]
    for i in range(2, len(nums)):
        if nums[i] - nums[i-1] == diff:
            cur += 1
            res += cur
        else:
            diff = nums[i] - nums[i-1]
            cur = 0
    return res

- 11. 01 Matrix (LeetCode Medium)
  Question: Distance to nearest 0 for each cell.
  In-Depth Answer: BFS from all 0s, multi-source. Time: O(mn), Space: O(mn)

				
					from collections import deque
def updateMatrix(mat: list[list[int]]) -> list[list[int]]:
    m, n = len(mat), len(mat[0])
    q = deque()
    for i in range(m):
        for j in range(n):
            if mat[i][j] == 0:
                q.append((i, j))
            else:
                mat[i][j] = -1
    dirs = [(0,1),(1,0),(0,-1),(-1,0)]
    while q:
        x, y = q.popleft()
        for dx, dy in dirs:
            nx, ny = x + dx, y + dy
            if 0 <= nx < m and 0 <= ny < n and mat[nx][ny] == -1:
                mat[nx][ny] = mat[x][y] + 1
                q.append((nx, ny))
    return mat

- 12. Minimum Area Rectangle (LeetCode Medium)
  Question: Min area axis-aligned rectangle from points.
  In-Depth Answer: Group by x, sort y, check pairs. Time: O(n^2), Space: O(n).

				
					def minAreaRect(points: list[list[int]]) -> int:
    cols = {}
    for x, y in points:
        if x not in cols:
            cols[x] = set()
        cols[x].add(y)
    res = float('inf')
    lastx = {}
    for x in sorted(cols):
        ys = sorted(cols[x])
        for i in range(len(ys)):
            for j in range(i+1, len(ys)):
                y1, y2 = ys[i], ys[j]
                if (y1, y2) in lastx:
                    res = min(res, (x - lastx[(y1, y2)]) * (y2 - y1))
                lastx[(y1, y2)] = x
    return res if res != float('inf') else 0

- 13. Fair Distribution of Cookies (LeetCode Medium)
  Question: Min max cookies per child.
  In-Depth Answer: Backtracking to assign bags. Time: O(k^n), optimize with sorting.

				
					
def distributeCookies(cookies: list[int], k: int) -> int:
    cookies.sort(reverse=True)
    dist = [0] * k
    res = float('inf')
    def backtrack(i):
        nonlocal res
        if i == len(cookies):
            res = min(res, max(dist))
            return
        if max(dist) >= res: return
        for j in range(k):
            dist[j] += cookies[i]
            backtrack(i + 1)
            dist[j] -= cookies[i]
            if dist[j] == 0: break
    backtrack(0)
    return res

- 14. Container With Most Water (LeetCode Medium)
  Question: Max area between height lines.
  In-Depth Answer: Two pointers, move shorter. Time: O(n), Space: O(1).

				
					def maxArea(height: list[int]) -> int:
    l, r = 0, len(height) - 1
    res = 0
    while l < r:
        res = max(res, min(height[l], height[r]) * (r - l))
        if height[l] < height[r]:
            l += 1
        else:
            r -= 1
    return res

- 15. Candy (LeetCode Hard)
  Question: Min candies based on ratings.
  In-Depth Answer: Two passes: left-to-right, right-to-left. Time: O(n), Space: O(n).

				
					def candy(ratings: list[int]) -> int:
    n = len(ratings)
    candies = [1] * n
    for i in range(1, n):
        if ratings[i] > ratings[i-1]:
            candies[i] = candies[i-1] + 1
    for i in range(n-2, -1, -1):
        if ratings[i] > ratings[i+1]:
            candies[i] = max(candies[i], candies[i+1] + 1)
    return sum(candies)

- 16. Burst Balloons (LeetCode Hard)
  Question: Max coins bursting balloons.
  In-Depth Answer: DP[i][j] = max for subarray i to j. Time: O(n^3), Space: O(n^2).

				
					def maxCoins(nums: list[int]) -> int:
    nums = [1] + nums + [1]
    n = len(nums)
    dp = [[0] * n for _ in range(n)]
    for length in range(2, n):
        for left in range(n - length):
            right = left + length
            for k in range(left + 1, right):
                dp[left][right] = max(dp[left][right], nums[left] * nums[k] * nums[right] + dp[left][k] + dp[k][right])
    return dp[0][n-1]

- 17. Trapping Rain Water (LeetCode Hard)
  Question: Water trapped between bars.
  In-Depth Answer: Two pointers, track max left/right. Time: O(n), Space: O(1).

				
					def trap(height: list[int]) -> int:
    if not height: return 0
    l, r = 0, len(height) - 1
    maxL, maxR = height[l], height[r]
    res = 0
    while l < r:
        if maxL < maxR:
            l += 1
            maxL = max(maxL, height[l])
            res += max(0, maxL - height[l])
        else:
            r -= 1
            maxR = max(maxR, height[r])
            res += max(0, maxR - height[r])
    return res

18. Decode String (LeetCode Medium)

Question: Decode encoded string like “3[a]2[bc]”.

In-Depth Answer: Stack for numbers/strings. Time: O(n), Space: O(n).

				
					def decodeString(s: str) -> str:
    stack = []
    cur_num = 0
    cur_str = ''
    for c in s:
        if c.isdigit():
            cur_num = cur_num * 10 + int(c)
        elif c == '[':
            stack.append((cur_str, cur_num))
            cur_str = ''
            cur_num = 0
        elif c == ']':
            prev_str, num = stack.pop()
            cur_str = prev_str + cur_str * num
        else:
            cur_str += c
    return cur_str

- 19. Word Ladder (LeetCode Hard)
  Question: Shortest transformation sequence.
  In-Depth Answer: BFS with word graph. Time: O(m^2 * n), Space: O(m^2 * n) for m=word len, n=words.

				
					from collections import defaultdict, deque
def ladderLength(beginWord: str, endWord: str, wordList: list[str]) -> int:
    if endWord not in wordList: return 0
    nei = defaultdict(list)
    wordList.append(beginWord)
    for word in wordList:
        for j in range(len(word)):
            pattern = word[:j] + "*" + word[j+1:]
            nei[pattern].append(word)
    visit = set([beginWord])
    q = deque([beginWord])
    res = 1
    while q:
        for _ in range(len(q)):
            word = q.popleft()
            if word == endWord:
                return res
            for j in range(len(word)):
                pattern = word[:j] + "*" + word[j+1:]
                for neiWord in nei[pattern]:
                    if neiWord not in visit:
                        visit.add(neiWord)
                        q.append(neiWord)
        res += 1
    return 0

- 20. Longest Increasing Path in a Matrix (LeetCode Hard)
  Question: Longest increasing path in grid.
  In-Depth Answer: DFS with memoization. Time: O(mn), Space: O(mn).

				
					def longestIncreasingPath(matrix: list[list[int]]) -> int:
    if not matrix: return 0
    m, n = len(matrix), len(matrix[0])
    memo = [[-1] * n for _ in range(m)]
    dirs = [(0,1),(1,0),(0,-1),(-1,0)]
    def dfs(i, j):
        if memo[i][j] != -1: return memo[i][j]
        res = 1
        for dx, dy in dirs:
            x, y = i + dx, j + dy
            if 0 <= x < m and 0 <= y < n and matrix[x][y] > matrix[i][j]:
                res = max(res, 1 + dfs(x, y))
        memo[i][j] = res
        return res
    return max(dfs(i, j) for i in range(m) for j in range(n))

- If you’re aiming to master both DSA and system design, our master course covers it all.
  System Design Interview Questions: Scaling for Billions
  For mid-senior roles, expect 1-2 system design rounds. Focus on high-level architecture, trade-offs, and scalability.
  1. Design Google Search
  Question: How would you design Google Search to be scalable and fast?
  In-Depth Answer: Break into components: Crawler (web spider with BFS/priority queue), Indexer (inverted index with sharding), Query Processor (ranking with PageRank/ML), Storage (distributed like BigTable). Handle 100B+ pages: Use MapReduce for indexing, caching for queries. Trade-offs: Latency vs. freshness. Bottlenecks: Network I/O—mitigate with CDNs. For 2025, integrate AI for semantic search.
  2. Design TinyURL
  Question: Design a URL shortening service.
  In-Depth Answer: Hash long URL to short key (base62 encoding). Database for mapping. Handle collisions with custom keys. Scale with sharding, Redis cache. Analytics via counters. Security: Validate URLs.

4. Design YouTube

Question: Scalable video streaming system.

In-Depth Answer: Components: Upload (chunking to storage like GCS), Transcoding (FFmpeg clusters), Storage (CDN for delivery), Recommendation (ML models). Handle 5M+ videos/day: Sharding databases, edge caching.

5. Design an Elevator System

Question: Algorithm for min waiting time.

In-Depth Answer: Scheduler with priority queue for requests. Directions-based grouping. Optimize with ML for peak predictions.

For data science roles or AI-focused prep, check our data science course.

Preparation Tips and Resources

Practice Strategy: Solve 200+ LeetCode problems tagged “Google.” Mock interviews on platforms like Pramp. Time yourself.
Study Areas: DSA (trees, graphs, DP), system design patterns, OS fundamentals.
Resources: Cracking the Coding Interview, Grokking the System Design Interview. For quick refreshers, our crash course.
Mock Tips: Think aloud, handle hints gracefully.
2025 Trends: Expect AI ethics questions, e.g., “How to mitigate bias in search results?”

Category	Key Topics	Recommended Practice
Coding	Arrays, Trees, Graphs, DP	LeetCode Google tag, 50-100 problems
System Design	Scalability, Databases, Caching	Design Gurus courses, case studies
Behavioral	Leadership, Failures, Conflicts	SPSIL stories from past experiences

Common Mistakes to Avoid

Not clarifying assumptions in coding questions—always ask about constraints.
Ignoring edge cases; test your code verbally.
Being too rigid in system design; discuss trade-offs.
Forgetting Googleyness—show enthusiasm and ethics.
Poor time management; practice under 45-min limits.

Conclusion: Your Path to Google

Preparing for Google’s interviews requires dedication, but with focused practice on these questions, you’ll be well-equipped. Remember, it’s about demonstrating how you think, not just what you know. Start practicing today, and you could be the next Googler shaping the future. Ready to accelerate your prep? Enroll in our courses for expert guidance.

FAQs

What are the most common coding questions in Google interviews 2025?

Common questions include array manipulations like Trapping Rain Water and graph problems like Word Ladder, focusing on optimization and edge cases.

How to prepare for Google system design interviews?

Study scalable systems like search engines or key-value stores, emphasizing components, trade-offs, and bottlenecks for billions of users.

What behavioral questions does Google ask in 2025?

Expect “Why Google?” and “Tell me about a failure,” using SPSIL to highlight growth and alignment with Googleyness.

What's the Google interview process timeline in 2025?

It spans 4-8 weeks: application, online assessment, 1-2 phone screens, 4-6 onsite rounds, and committee review.

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Most Asked Interview Questions at Google (2025 Edition)

Google’s Interview Process in 2025: What to Expect

Behavioral Interview Questions: Showcasing Your Googleyness

Why Do You Want to Work at Google?

Tell Me About a Time You Failed at Work

What Is Your Favorite Google Product and Why?

Tell Me About a Time You Dealt with Conflict

Describe a Challenging Technical Problem You Solved

Coding Interview Questions: Deep Dives into Real Problems

1. Add Binary (LeetCode Easy)

2. Valid Mountain Array (LeetCode Easy)

3. Set Mismatch (LeetCode Easy)

4. Length of Last Word (LeetCode Easy)

5. Monotonic Array (LeetCode Easy)

6. Find the Difference (LeetCode Easy)

7. Binary Tree Paths (LeetCode Easy)

8. Merge Strings Alternately (LeetCode Easy)

In-Depth Answer: Use two pointers, append remaining. Time: O(m+n), Space: O(m+n).

9. 2 Keys Keyboard (LeetCode Medium)

10. Arithmetic Slices (LeetCode Medium)

11. 01 Matrix (LeetCode Medium)

In-Depth Answer: BFS from all 0s, multi-source. Time: O(mn), Space: O(mn)

12. Minimum Area Rectangle (LeetCode Medium)

13. Fair Distribution of Cookies (LeetCode Medium)

14. Container With Most Water (LeetCode Medium)

15. Candy (LeetCode Hard)

16. Burst Balloons (LeetCode Hard)

17. Trapping Rain Water (LeetCode Hard)

18. Decode String (LeetCode Medium)

19. Word Ladder (LeetCode Hard)

20. Longest Increasing Path in a Matrix (LeetCode Hard)

System Design Interview Questions: Scaling for Billions

1. Design Google Search

2. Design TinyURL

4. Design YouTube

5. Design an Elevator System

Preparation Tips and Resources

Common Mistakes to Avoid

Conclusion: Your Path to Google

FAQs

What are the most common coding questions in Google interviews 2025?

How to prepare for Google system design interviews?

What behavioral questions does Google ask in 2025?

What's the Google interview process timeline in 2025?

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