Each week, we Gainlo team will carefully pick one or two popular Uber interview questions that are asked recently. What makes the post special is that the “standard answer” is not the focus. Instead, the whole point of the post is to teach you how to analyze the question step by step and how to come up with the right idea from scratch. At the end of each post, we’ll summarize techniques you may use in similar problems.
Believe it or not, solutions don’t come from nowhere. There are definitely patterns that can help you come up with the solution and we are here to tell you about these “secret patterns”. One classic example is the tradeoff between time and space. When you try to make your algorithm faster, you might consider using extra memory to do that and for extra memory, you should consider data structures like hash table. If you become familiar with this type of logic, you are more likely to think in the right direction.
Again, we believe that answers to those coding interview questions are not important at all. You should pay more attention to the analysis process and summarize common patterns/techniques that can be reused in other problems.
This week, I’m going to talk about the longest increasing subarray problem. You can find more posts like this at Uber Interview Questions.
Also, this question is similar to Subarray With Given Sum. If you have read our previous post, I hope you can solve this problem easily.
In this post, I’m going to cover topics like “sliding window”, dynamic programming, time/space complexity and so on.
This week, I’m going to discuss the question – arrange given numbers to form the biggest number possible. Like our previous posts about Uber interview questions, I’m focusing more about the analysis process than the final solution.
The idea is not to give our readers the answer/code immediately. Instead, I’d like to guide you through the whole analysis process. At the end, I hope you can be equipped everything you need to solve similar questions.
Here we go.
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In this post, we will talk about rotated array binary search problem. Three major things are discussed: First of all, instead of providing the solution, we’ll cover how to analyze the question and how to come up with the right idea. Second, it’s not easy to write the bug-free solution for this problem and we’ll talk about some tips and hacks. Last, like our other posts, common techniques are summarized at the end of the post so that you can use similar tools to solve other coding interview questions.
Following our previous posts about Uber interview questions, this week we’re going to talk about one of my favorite questions – permutations of an array of arrays.
If you keep following our blog, I hope you can solve this problem by yourself as a lot of ideas and techniques used here are common. Here we go.
We’ve received a lot of feedback from our previous posts. Some readers pointed out bugs in the code and hopefully we’ve fixed all of them. Also, a lot of people are asking for more posts about dynamic programming/recursion. That’s why this week we’d like to talk about the question – permutations of parentheses.
Many people are afraid of this topic because it can be hard to come up with the solution if you haven’t practiced enough. On the flip side, the good news is that just because this topic is relatively difficult, the question cannot be too hard in a coding interview (otherwise, no one could solve it).
This week, we’ll continue to discuss this topic with a Uber interview question, but the analysis/solution is slightly different.
As you may know, one of our blog’s current focuses is on Uber interview questions. Their questions are usually representative and you can expect exactly the same kind of questions from other top companies like Google, Facebook, Airbnb, etc.. In addition, we only cover questions that were asked recently. This week, the question is maximum sum of non-adjacent elements. It’s of medium difficulty, you may expect to have it as the second question in an on-site interview. We are going to cover topics including array, recursion/dynamic programming, algorithm efficiency and so on so forth.
As we’ve emphasized many times, most people overestimate the difficulty of Uber/Google/Facebook interview questions and underestimate the importance of bug-free code.
At the end of the day, many people have complained that the questions were simpler than expected, but they didn’t manage to write clean code. Especially when someone is looking over your shoulder, people tend to be nervous.
In our recent posts like this, I really want to discuss more fundamental questions, but get your code correct. This week, we’ll discuss a Uber interview question – move zeroes. This question is usually asked in phone screens or as the first question in on-site interviews. It’s for sure that you’ll write down the solid code and you get no chance if your code is buggy or inefficient.
This week, we’re going to discuss a recent Uber interview question – weighted random numbers. This is also one of my favorite questions to ask and I’m surprised at how many people failed this problem.
In a nutshell, we’ll talk about a couple topics in this post, including sampling, basic data structures, time/space complexity and tips for coding this question.
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We are going to discuss the delimiter matching problem in this week’s post. The question has recently been asked by Uber, however, which is only part of the reason we select this question.
One of the common misunderstandings is that coding interviews are extremely hard to companies like Uber, Google, Facebook etc. and most people failed because they couldn’t come up with any idea at all. However, it’s not the case. More than 70% of questions are quite fundamental and are focused on testing candidates’ understanding of basic data structures/algorithms.
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In this week’s coding interview question post, I’m going to analyze one of the best questions I’ve seen in recent interviews. As many people ask for the pseudo code in order to help them understand the algorithm, I will also include that in the post as well.
It’s worth to emphasize again that what’s truly important is not the final code/solution, it’s all about the analysis process and I’m going to teach you exactly how to come up with the right idea.