Saturday, February 24, 2024

# How To Solve Coding Interview Problems

## Always Go For Alternatives

Whiteboard Coding Interviews: 6 Steps to Solve Any Problem

If we talk about programming, then chances are theres an alternative solution. Many times, you may have more than one answer to the problem. Dont pick the best one.

Firstly, analyze the approach that might suit the culture of the company. Once you explain this approach, subtly mention the alternative approach, which can benefit certain scenarios.

The reason why explaining an alternative approach offers additional credibility to the candidate is because it proves you are not depicting only textbook knowledge. It shows that you can find different solutions too.

For example, if you have been asked to write code for a streaming Android app. You may choose a quick approach to write the code. But, verbally explaining about a long approach will speak volumes.

## Coding Interview Questions On Arrays

Here are some sample coding interview questions on Arrays:

• Given an unordered array of integers, write a program that finds a contiguous subarray whose sum is equal to the given one.
• For two unsorted arrays in ascending order, write a code to merge them such that the new array is in ascending order.
• For a given array having values from 1 to N and the first array containing the element at every position in the second array, write a program that finds the position of the missing element in the second array.
• For a given array of positive integers, write a code that computes the sum of the elements.
• For a given unsorted array of size N, write a function to rotate it by D elements anticlockwise.
• For a given sequence of size N, determine a code to print the original sequence.
• Write a function to locate and delete duplicate elements from an ordered array.
• For a given 2D array containing integer elements, write code to find the minimum length and maximum length.
• ## Not Checking Your Work

When you’ve completed a problem, be sure to review your code for bugs. Checking for bugs in a whiteboard interview can be an unfamiliar practice, but it’s important to show interviewers every aspect of your process. To debug whiteboard code, consider writing a short sample input and walking through your code one line at a time. Write out the input changes on the board along with any new variables. Following this process can show your interviewer you understand what a computer processor does when it runs through lines of code.

If youâve begun preparing for your next technical interview, register for Interview Kickstartâs technical interview webinar and get ahead by understanding foolproof and advanced strategies from industry experts. These reviews from our alums will tell you exactly how weâve helped thousands of students to scallop their professional careers by helping them crack technical interviews at the biggest companies.

## Coding Interview Questions On Java And Python

Java and Python are the most common programming languages that are used by programmers at coding interviews. Apart from testing your knowledge of core data structures and algorithms, hiring managers also evaluate your understanding of core OOP concepts in these languages.

Weâll look at some sample coding interview questions in Java and Python to help you prepare for your next coding interview!

## Coding Interview Questions On Linked Lists

Questions on linked lists are pretty common at tech interviews at top companies. Here are a few sample questions to get you started:

• How to insert a node at the end of a Linked List
• How do you remove a particular node from a Linked List?
• Write a function to reverse a singly linked list
• Write a recursive function to remove the nth node from a Linked List.
• Write a function to move nodes in a link list by swapping adjacent nodes
• Write a code that will invert the values of an array at a specific point
• ## Now Youre Ready For The Coding Interview

These are some of the most common questions outside of data structure and algorithms that help you to do really well in your interview.

I have also shared a lot of these questions on my blog, so if you are really interested, you can always go there and search for them.

These common coding, data structure, and algorithms questions are the ones you need to know to successfully interview with any company, big or small, for any level of programming job.

If you are looking for a programming or software development job, you can start your preparation with this list of courses to learn patterns, tips, and tricks to solve coding problems

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## Tips To Ace Coding Interviews

Before the interview, it is worth clarifying with recruiters what kinds of coding questions will be asked, as well as the approximate difficulty level. Lots of data science interviews do not require heavy programming, but that does not mean interviewers will not expect basic coding proficiency at your fingertips. Always ask your recruiter what to expect. If you make incorrect assumptions on the types of questions that can appear during interviews, you may end up preparing inadequately.

During the interview, use these tips to answer coding questions effectively.

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## When Your Explanations Are Just As Important As The Code You Write

10 Common Coding Interview Problems – Solved!

At the beginning of the interview cycle for most software positions, there is a series of technical programming challenges, some on the phone with a person and some auto-graded. Those auto-graded assessments are really a mental test between you and the problem: get as many test cases to pass in the shortest amount of time possible.

Many people assume the same about the phone interview: get as many to pass as you can to impress the person on the other end of the line. This route is definitely not the most optimal. You should replace to impress with and work with. You should treat the phone interview as a partnership or a pair-programming task where you are the primary programmer.

Whether you can or cant solve the problem, there are some things you should do in the interview to increase your chances, including asking clarifying questions, explaining your thought process as you go along, and identifying pain points to your interviewer. If you cant solve the problem youve been given, instead of just giving up, do these three things so you can demonstrate your problem-solving ability and possibly elicit some sort of hint from the interviewer.

## Do Not Memorize Problems

There are 100s of different types of coding interview questions you can be asked to solve. It is literally impossible to memorize every single one! The best approach is to understand the concepts behind the algorithm.

I needed to use two pointers in this algorithm because..I used depth first search here because..I didnt need two for loops for this question because..I didnt have to traverse the entire input because..

Memorizing coding interview questions can create anxiety when youre presented a problem youve never seen before. Understanding concepts and patterns will require more effort up front, but will pay off in the long run.

Facebookâs technical interview comprises 2-3 coding interview rounds, where hiring managers specifically aim to evaluate your approach to problem-solving and how youâre able to articulate problem solutions effectively. Practicing as many coding problems as possible is key to cracking Facebookâs technical interview.

Letâs look at some sample Facebook coding interview questions:

• Write a program to print only the left view of a given binary tree.
• Write a program to remove duplicate elements in a given string.
• Write a code to implement Tarjanâs Greedy algorithm. To perform BFS.
• Write a function to implement a queue using two stacks.
• Write a program to find the maximum path sum for a non-empty binary search tree.
• Check out the page to access several more coding questions asked at Facebookâs interview.

Practicing these above coding interview questions can help you tackle challenging problems at FAANG+ technical interviews.

## Consider All The Information Youre Given

Lots of times, our interviewers give us clues as to how we should think about a problem. By giving us details about how the input is formatted or any restrictions on the input, they are subtly hinting at how to view the problem.

For example, lets say that we wanted to find a value in a sorted matrix. If we know that the rows and columns of the matrix are in sorted order, that gives us a big clue for how we can solve the problem.

Without that information, were fairly limited in how we can approach this problem. Our best bet would be to just iterate over every value in the matrix to see if the value were searching for exists. However, we have a big clue, which is that our matrix is sorted.

Knowing the matrix is sorted, we have algorithms to help us deal with that. Theres binary search and we can also consider other properties of our matrix. For example, since both rows and columns are sorted, if we pick an arbitrary cell , any cell < i and < j is going to have a value less than cell .

From the information given, if youre stuck, you can simply take some time to extrapolate everything you can. If the array is sorted, what does that mean? If the input is in tree format, how can we use that to our advantage? Look for these clues.

## Difference Between A Stable And Unstable Sorting Algorithm

This one was a tricky concept that I didnt know until long ago. I havent come across any practical use case of this one yet, but just knowing the concept is Ok from the interview perspective.

In a stable sorting algorithm, the order of the same element remains the same even after sorting, but during the unstable sorting algorithm, these changes.

A good example is a quicksort and mergesort, where the former is unstable while latter is a stable algorithm.

## + Searching And Sorting Algorithms Questions From Coding Interviews

Anyway, here are some of the frequently asked Searching and Sorting Algorithms questions from Interviews. I have linked the solution, but you should try to solve the problem before looking at the solution.

## How Is A Merge Sort Algorithm Implemented

Similar to Quicksort, merge sort is also a divide and conquers algorithm, which means you keep the problem until you can sort the smallest of them.

For example, to sort an array of numbers, you divide the array into smaller parts until you know how to sort them like an array with one or zero elements is already sorted. Once you sort small arrays, you merge them to get the final result.

The only difference between Quicksort and Mergesort is that mergesort is stable while Quicksort is not-stable. This means equal elements retain their spot before and after sorting.

Another worth noting difference is that even though both have average time, its better to use quicksort than mergesort because Quicksort takes less time for the same number of input, the constant factor is less in Quicksort than merge sort.

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## Sort A Linked List Using Merge Sort

Problem Statement

Given the head pointer of a linked sort, sort the linked list in ascending order using merge sort, and return the new head pointer of sorted linked list.

Hint:

• Divide and Conquer

Solution and Breakdown

`typedef LinkedListNode* node_ptr // this method splits linked list in two halves by iterating over whole list// It returns head pointers of first and 2nd halves of linked lists in first_second// Head of 1st half is just the head node of linked listvoid split_in_half   // Only one element in the list.  if   else     }    first_second.first = head     first_second.second = slow-> next     // Terminate first linked list.    slow-> next = nullptr   }}node_ptr merge_sorted_lists   else if    node_ptr new_head   if    else   node_ptr new_current = new_head   while   else     new_current-> next = temp     new_current = temp   }  if   else if    return new_head }node_ptr merge_sort   // Let's split the list in half, sort the sublists  // and then merge the sorted lists.  pair< node_ptr,node_ptr>  first_second   split_in_half   first_second.first = merge_sort   first_second.second = merge_sort   return merge_sorted_lists }int main    node_ptr list_head_1 = LinkedList::create_linked_list   cout < < "Unsorted list: "   LinkedList::display   list_head_1 = merge_sort   cout< < "Sorted list: "   LinkedList::display }`

Time Complexity: O O

In the combining step, we merge sorted lists until we have a completely sorted list.

## Common Mistakes With Nested Loop

Solve Coding Interview Backtracking Problems – Crash Course

Find the Big O complexity of the following code:

`for}`

Solution Explanation

This is a gotcha question that tests if you really understand Big O.

Even if theyre nested, the inner loops number of executions is not dependent on the input. It will always execute the same number of times.

A common mistake is to answer O O. Big O calculates for asymptotic behavior therefore we remove constants, like 10,000.

The correct answer is then O

## How To Optimize Space Complexity

Most of the time, time complexity is more important than space complexity. But when you have already reached the optimal time complexity, the interviewer might ask you to optimize the space your solution is using . Here are some techniques you can use to improve the space complexity of your code.

#### 1. Changing data in-place/overwriting input data

If your solution contains code to create new data structures to do intermediate processing/caching, memory space is being allocated and can sometimes be seen as a negative. A trick to get around this is by overwriting values in the original input array so that you are not allocating any new space in your code. However, be careful not to destroy the input data in irreversible ways if you need to use it in subsequent parts of your code.

A possible way which works is to mutate the original array and use it as a hash table to store intermediate data. Refer to the example below.

Note that in Software Engineering, mutating input data is generally frowned upon and makes your code harder to read and maintain, so changing data in-place is mostly something you should do only in coding interviews.

#### Example

The Dutch National Flag problem could be easily solved with O time and O space by creating a new array and filling it up with the respective values in a sorted fashion. As an added challenge and space optimization, the interviewer will usually ask for an O time and O space solution which involves sorting the input array in-place.

## Tips For Smart Learning

• Our goal must be to cover at least 80% syllabus and prioritize the topics based on strengths and weaknesses. A topic that requires more time should get more time.
• Doing a weekly critical review could help us to understand the progress. We need to think what is the further scope of improvement in the topic? What is the current level of our problem-solving ability? For the fact-based view, we recommend rating each topic on a scale of 1 to 10.
• Few ideas always come during learning DSA: Brute force solution, efficient solution, boundary conditions, time and space complexity analysis, coding style. Keep preparing notes if you find something unique or essential patterns.
• In the starting journey, rather than solving many problems, focus on the top 100 coding interview questions. The best idea would be to pick famous coding interview problems which can be solved using various techniques.
• Learn to visualize critical operations, implementations, and use cases of each data structure.
• Never mind going through the same concepts and problems again and again. This would help in figuring out hidden ideas. Focus on reason and never try to memorize!

A blog to explore: Step by step learning plan for interview success

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## Coding Interview Questions: Topics To Prepare

To crack coding interviews at FAANG+ companies, it is important to know what topics to prepare. Below is the list of topics to cover in order to be able to solve coding interviews at FAANG+ companies.

• Graph algorithms, including greedy algorithms
• Dynamic programming

For a comprehensive checklist of all coding interview topics you should prepare, check out the technical interview checklist.

## How Would You Handle Working On A Team With People From Other Departments

During a programming interview, youll take technical tests or complete technical interviews. You can use these opportunities to showcase your soft skills as well, such as providing examples of your interpersonal and communication skills.

ExampleI work well on teams, including ones with non-tech members. I find that these groups can produce products and solutions that a team of like-minded people may not consider. I also enjoy meeting new people and considering other angles to the projects we work on together. I have worked on teams with only programmers and mixed teams in the past, and feel the mixed groups were often more innovative. I would welcome an opportunity to work on this type of team.

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## Explain Concepts Out Loud

Coding concepts are challenging to explain, especially when speaking to someone unfamiliar with the field. When a hiring manager wants to learn about your thought process, they might ask you to explain concepts.

Before your interview, explain complex coding topics out loud to a friend. When explaining concepts out loud, it is easier to recognize how well you grasp a topic and what you should review. Explaining concepts ahead of time helps you grow confident in verbalizing your techniques.

## Faqs On Coding Interview Questions

Q1. What topics should you prepare to solve coding interview questions in a technical interview?

To solve data structures interview questions, you must be thorough with the following concepts – arrays, strings, linked lists, recursion, hash tables, graphs, trees, and dynamic programming.

Q2. How many coding interview rounds are there in FAANG interviews?

Interviews at FAANG companies typically have 2-3 coding interview rounds. The first two rounds are usually technical screening rounds.

Q3. How long should you ideally prepare for FAANG coding interviews?

As a rule of thumb, it is crucial that you start preparing for your coding interview at least 6 weeks before your interview.

Q4. Are coding interview questions asked at domain-specific tech interviews?

Yes, most domain-specific tech interviews, such as ML interviews, testing interviews, cloud interviews, and web developer interviews, have mandatory coding rounds where your knowledge of programming concepts, core data structures, and algorithms is evaluated.

Q5. How long do coding interview rounds last at FAANG companies?

Coding interview rounds typically last 30-40 minutes. Recruiters mostly aim to evaluate your approach to problem-solving and your ability to write error-free code.