Every day, billions of people search, email, navigate, and create, all powered by Google’s engineering. From Search to Maps, Gmail to YouTube, Google’s products touch nearly every aspect of modern life. The scale and variety of these tools reflect Google’s drive to build for everyone, everywhere, and that same mindset is at the core of Google’s interview process.
You are not just asked to solve a coding problem in a Google coding interview. You are challenged to design solutions that scale, to think through real-world edge cases, and to adapt quickly when a question takes a new direction. The next line of code you write could end up powering a feature millions use.
Grokking the Coding Interview Patterns
With thousands of potential questions to account for, preparing for the coding interview can feel like an impossible challenge. Yet with a strategic approach, coding interview prep doesn’t have to take more than a few weeks. Stop drilling endless sets of practice problems, and prepare more efficiently by learning coding interview patterns. This course teaches you the underlying patterns behind common coding interview questions. By learning these essential patterns, you will be able to unpack and answer any problem the right way — just by assessing the problem statement. This approach was created by FAANG hiring managers to help you prepare for the typical rounds of interviews at major tech companies like Apple, Google, Meta, Microsoft, and Amazon. Before long, you will have the skills you need to unlock even the most challenging questions, grok the coding interview, and level up your career with confidence. This course is also available in JavaScript, Python, Go, and C++ — with more coming soon!
Candidates have many options for preparing for such a dynamic interview. There are curated lists, community suggestions, Reddit threads, and more. Two popular approaches are Blind 75 and LeetCode patterns, which you have probably heard of. But with so many choices, the real question is which works best for Google’s unique interview style.
This blog will closely examine what matters for Google coding interviews. Instead of reviewing popular problem lists, we’ll compare how curated sets like Blind 75 and Google Top 75 stack up against a patterns-based approach using the 28 core LeetCode Patterns featured in the “Grokking the Coding Interview Patterns” course. Along the way, I’ll help you craft a prep strategy that matches the scale, creativity, and technical depth Google is known for.
Blind 75 is a list of 75 well-known LeetCode problems that cover the most common data structures and algorithms, like arrays, strings, trees, and dynamic programming. It’s popular because it’s focused and easy to start with, but it may not help you practice the depth and flexibility Google sometimes looks for.
Google Top 75 is a collection of the 75 LeetCode questions most often seen in recent Google interviews. Solving these problems can help you spot what’s trending now in Google’s interview process and target your practice on the questions most likely to appear.
LeetCode patterns group coding problems by 28 core problem-solving techniques, such as sliding window, graph traversal, or two pointers. Studying by pattern helps you spot the underlying strategy in any question, which is especially useful at Google, where problems often have unexpected twists.
For engineers aiming at Google, the real question isn’t “How many problems should I practice?” but “How do I prepare for the unknowns, the twists, the follow-ups, and the pattern variations?”
Unlike many companies, Google rarely recycles problems verbatim. Instead, they reframe classic techniques, like sliding windows or topological sort, into new scenarios you may have never encountered. Even if you recognize the core idea, you should expect follow-up twists: “Now, can you optimize it?” or “How does your approach scale?” A question that starts as a simple merge can quickly become a K-way heap, or a basic range sum can become a prefix sum optimization.
This is why relying on a static list of problems might not prepare you for the unseen. To succeed at Google, you need more than repetition; you must build the ability to adapt, spot patterns, and think through new challenges as they arise.
We have already discussed how twists, randomness, and optimizations are common to Google’s interview process. With AI, giving a new twist to an existing problem is no longer a challenge. Interviewers can easily generate fresh variations beyond what you’ve seen in Blind 75.
Adding to this, by now, LeetCode has hundreds of questions for Google’s interview prep. This makes it even more challenging for you to think which one to pick and which to leave, the old or the new ones? What will get you the full coverage?
This is where LeetCode patterns help. When you practice by patterns, you build the muscle to adapt quickly, no matter how the problem is framed. It’s the most efficient way to prepare for interviews that test how you think, not just what you remember.
With 28 core patterns, it’s easy to feel overwhelmed or lose sight of what matters most. The key is not to treat every pattern as equally likely. Google’s interview process is well-known for focusing on a specific set of high-yield techniques, with a handful of patterns dominating most interviews.
To help you navigate and prioritize your prep, I’ve grouped the patterns by how often they’re likely to show up at Google, and how much value they add to your overall readiness:
Let’s see what each category means:
Must‑knows: These patterns appear in almost every SWE loop.
Very common: These patterns occur at least once across a multi‑round onsite.
Solid but situational: These patterns are worth a refresher; reach‑candidate questions or role‑specific rounds.
Finishing‑line helpers: These patterns are rare as a standalone prompt, but often emerge as space/time optimisations once you’ve solved the core.
Most candidates either grind through a fixed list or try to memorize every pattern. But what if there’s a more strategic path that maximizes coverage, saves time, and keeps your prep focused on what Google tests?
Here’s the approach I recommend:
Begin with the problems common to both Google 75 and Blind 75.
Move on to Google-only problems for depth and relevance.
Fill remaining gaps with Blind-only questions.
Finish with a targeted review of any pattern not yet covered.
Do you remember the rubric I shared in my earlier post? Aim for one easy, two medium, and one hard problem to cover any pattern adequately. This approach helps you build breadth and depth across all the core techniques. Keeping this in mind at each sequence stage maximizes exposure to relevant patterns, ensures you get practice with the twists Google uses, and keeps your study time focused on what matters most.
Here’s a quick visual to show how this approach ensures you’re prepared for what Google asks or can ask.
Starting with the problems common to both Google 75 and Blind 75 is one of the most efficient ways to ramp up. This small, high-impact set gives you immediate exposure to about half the essential patterns and helps you quickly build fluency with Google’s foundational problem types.
To clarify things, I’ve compared both lists so you can easily spot the problems that appear in both Blind 75 and Google 75.
Blind 75 (Problem Name) | Google 75 (Problem Name) |
Two Sum | Two Sum |
Best Time To Buy And Sell Stock | Best Time To Buy And Sell Stock |
Merge Intervals | Merge Intervals |
Number Of Islands | Number Of Islands |
Valid Parentheses | Valid Parentheses |
Longest Substring Without Repeating Characters | Longest Substring Without Repeating Characters |
Longest Palindromic Substring | Longest Palindromic Substring |
Group Anagrams | Group Anagrams |
Top K Frequent Elements | Top K Frequent Elements |
3Sum | 3Sum |
Container With Most Water | Container With Most Water |
Climbing Stairs | Climbing Stairs |
Rotate Image | Rotate Image |
Longest Consecutive Sequence | Longest Consecutive Sequence |
Merge Two Sorted Lists | Merge Two Sorted Lists |
Jump Game | Jump Game |
Search In Rotated Sorted Array | Search In Rotated Sorted Array |
Valid Anagram | Valid Anagram |
Set Matrix Zeroes | Set Matrix Zeroes |
Reverse Linked List | Reverse Linked List |
Unique Paths | Unique Paths |
Implement Trie (Prefix Tree) | Implement Trie (Prefix Tree) |
Meeting Rooms II | Add Two Numbers |
Merge K Sorted Lists | Longest Common Prefix |
Spiral Matrix | Median of Two Sorted Arrays |
Maximum Subarray | Roman to Integer |
Alien Dictionary | Trapping Rain Water |
Valid Palindrome | Partition String |
Course Schedule | N-Queens |
Minimum Window Substring | Palindrome Number |
Find Median From Data Stream | Subarray Sum Equals K |
Word Search | Maximum Number of Events That Can Be Attended |
Coin Change | Number of Visible People in a Queue |
Product of Array Except Self | Next Permutation |
Palindromic Substrings | Sort Colors |
House Robber | Find Peak Element |
Binary Tree Maximum Path Sum | Reverse Integer |
Word Break | Regular Expression Matching |
Contains Duplicate | Generate Parentheses |
Serialize and Deserialize Binary Tree | Remove Element |
Longest Repeating Character Replacement | Subsets |
Longest Increasing Subsequence | Merge Sorted Array |
Combination Sum | Single Number |
Clone Graph | Maximal Square |
Remove Nth Node From End of List | Single Element in a Sorted Array |
Word Search II | Koko Eating Bananas |
Reorder List | Merge Strings Alternately |
Maximum Product Subarray | Find All K-Distant Indices in an Array |
Missing Number | Add Two Integers |
Sum of Two Integers | Find the K-th Character in String Game I |
Decode Ways | Find the Original Typed String I |
Linked List Cycle | Find the Original Typed String II |
Lowest Common Ancestor of a Binary Search Tree | Minimum Increments to Equalize Leaf Paths |
Number of Connected Components in an Undirected Graph | Remove Duplicates From Sorted Array |
House Robber II | Minimum Path Sum |
Binary Tree Level Order Traversal | Largest Rectangle in Histogram |
Longest Common Subsequence | Reverse Words in a String |
Non-Overlapping Intervals | Decode String |
Meeting Rooms | Split Array Largest Sum |
Pacific Atlantic Water Flow | Longest Harmonious Subsequence |
Maximum Depth of Binary Tree | Task Scheduler |
Encode and Decode Strings | Find Lucky Integer in an Array |
Find Minimum in Rotated Sorted Array | Maximum Number of Events That Can Be Attended II |
Kth Smallest Element in a BST | Kth Smallest Product of Two Sorted Arrays |
Validate Binary Search Tree | Inverse Coin Change |
Insert Interval | Maximal Rectangle |
Same Tree | Subsets II |
Design Add and Search Words Data Structure | Best Time to Buy and Sell Stock II |
Construct Binary Tree From Preorder and Inorder Traversal | Rotate Array |
Invert Binary Tree | Isomorphic Strings |
Reverse Bits | Power of Two |
Graph Valid Tree | Find Subsequence of Length K With the Largest Sum |
Counting Bits | Minimum Time to Finish the Race |
Number of 1 Bits | Divide Array Into Arrays With Max Difference |
Subtree of Another Tree | Valid Word |
This list view shows that out of the full Blind 75 and Google 75 sets, there are 22 problems that both lists have in common. These shared questions cover many core topics and essential patterns that form the backbone of most interviews. Focusing on this overlap efficiently builds momentum and early confidence for anyone starting their Google prep.
Let’s quickly compare this step to our rubric. The following bar chart shows the distribution of problems by difficulty level across the patterns covered at this stage.
The analysis above shows that you get introduced to 14 out of 28 patterns, about 50% coverage, which is a strong starting point. Most common patterns are just one or two problems away from meeting the ideal rubric. This means only minimal supplementation is needed to ensure well-rounded practice, especially for the harder problems.
The real value here is momentum, as you build confidence in solving real interview questions and start to spot recurring themes and techniques that will surface repeatedly.
After covering the common problems, the Google-only set is where you expand your pattern coverage. At this stage, your main gain is exposure to several important patterns that do not appear in the common set.
Let’s see what new patterns you add to your toolkit by focusing on Google-only questions.
Adding the Google-only questions expands your pattern coverage from 50% to 71%. You unlock 6 new coding patterns. This set is where you see Google’s favorite twists and layered follow-ups, often missing from the common set.
Let’s quickly see how well this stage maps to our rubric by looking at the following bar chart. In the bar chart below, you’ll see the newly covered patterns highlighted in green on the y-axis.
When measured against the rubric, the Google-only set is nearly rubric-complete, often requiring a problem or two to round out each pattern. Another benefit is getting additional practice for your identified patterns, helping you strengthen your skills and fill any remaining gaps.
By working through these, you unlock 6 new patterns and your pattern coverage jumps to over 90%. You also pick up various long-tail patterns and techniques that occasionally appear as surprise twists in Google interviews.
Let’s quickly see how well this stage maps to our rubric using the following bar chart.
While these patterns provide a good range of practice, some are short of the rubric and would require the addition of several problems, particularly at the hard level, for complete coverage. Again, the focus is not on what’s missing, but on how each new problem can fill a specific gap identified by your earlier progress.
After the previous three stages, nearly every pattern is covered in the full checklist of 28 coding patterns. You are now only about 10% away from complete pattern coverage.
According to my data, two patterns are still missing: Custom Data Structures and Sort and Search. These are rarely seen but can be make-or-break in a tight interview loop.
As per our 1—2—1 rubric, here are some problems you can practice to build confidence in the missing patterns:
Pattern | Easy Problem | Medium Problems | Hard Problem |
Sort and Search |
|
|
|
Custom Data Structures |
|
|
|
Half of the coverage, 50%, comes from common patterns across all sets, forming the core of your preparation. Google-only patterns add another 21%, highlighting the value of including company-specific questions to close additional gaps. Similarly, Blind 75–only patterns account for another 21%, showing that unique patterns from classic lists still play a meaningful role. The final 7% represents remaining patterns not directly addressed by these standard sets. By strategically layering these different problem categories, you get much closer to comprehensive pattern coverage, ensuring your prep addresses the basics and the specialized challenges of Google interviews.
Let’s recap the incremental benefit:
This workflow means:
Maximum coverage with minimum redundancy
Immediate exposure to what Google asks
Confidence in handling any variation, at any difficulty
If you want to prepare for Google efficiently, and thoroughly, don’t just grind through lists. Work smart. Prioritize pattern recognition, start with the overlapping core, focus on Google’s favorites, and fill the gaps. Use data to guide your efforts, not guesswork.
Master the fundamentals, but make sure your prep reflects the reality of Google interviews: twists, follow-ups, and a focus on thinking, not memorization.
When measured against the ideal rubric, this strategy ensures you build genuine mastery, not just checking off problems but developing the adaptability and depth that Google interviewers seek.
If you found this helpful, check out Blind 75 vs LeetCode patterns for Apple coding interviews for further FAANG prep.
Wishing you clarity, confidence, and success as you tackle your next interview.
While this blog gives you a data-driven way to measure and close your prep gaps, the right learning tools can accelerate your progress even further. Here are two highly effective resources to complement your study plan:
Educative’s Personalized Interview Prep: It’s your tailored prep companion that adapts to your skill level and focuses on the 28 essential LeetCode patterns we’ve been talking about. You can work on the patterns that need the most attention, track progress with clear metrics, and know exactly what to tackle next. Whether it’s adding an easy problem to build confidence or a hard one to push for mastery, you’ll always be working on the right problems at the right time.
Educative’s Mock Interviews: Practicing is not just about solving problems. It is also about handling real interview pressure. Educative’s AI mock interviews let you simulate actual interview conditions, get actionable feedback, and improve in areas like problem-solving speed. This way, you are not only technically prepared but also confident and ready to perform under time constraints.
Free Resources