Hello All, If you are preparing for

These are based upon common searching and sorting algorithms like binary search, graph algorithms, etc,. It’s important that you practice these Algorithm based questions because even though they seem obvious and easy, sometimes they become tricky to solve in the actual interview, especially if you have never coded them by yourself.

Having practiced them before not only makes you familiar with them but also gives you more confidence in explaining the solution to the interviewer, which plays a very important role in your selection. It also makes you ready for any

Sometimes, if you use a data structure like the one I have used in finding duplicate characters on String, they will ask you to solve that problem without using the Set data structure. That's just some common example and that's why practice matters a lot.

Btw, if you are a complete beginner in the world of Data Structure and Algorithms, then I suggest you first go through a comprehensive Algorithm course like

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Anyway, here is some of the frequently asked Searching and Sorting Algorithms questions from Interviews:

It’s easy, binary search is a divide and conquers algorithm, where the problem is divided into sub-problem and those are solved. It’s a search algorithm so it is used to find things like a number in an integer array or an item in a catalog.

The easiest way to implement a binary search algorithm is by using Recursion, which is what the solution link contains but you should try it yourself before seeing the solution.

One of the worth noting is that the input must be sorted, I mean you can only implement binary search in a sorted array.

It is even easier than binary search, all you need to do is go through all elements in the array using a for loop or recursive method and compare each element with the one you want to search. when an element matches you either return index or true/false depending upon your requirement.

For example, if you are writing a contains() method you can return true or false to indicate whether an element is present in the array or not. Since you need to scan the whole array to find the element, the time complexity of this algorithm is O(n).

You might know that you can replace a recursive algorithm with an iterative one by using a loop or sometimes a stack. For binary search also you can do this, just divide the array and compare the middle element until you find the target element or there is no more element into an array. If the target element is greater than the middle then you got to move towards the right, or otherwise towards the left.

Btw, if you have trouble understanding recursive algorithms or converting a recursive one to an iterative one then I suggest you go through a good online course like

In level order search you first visit sibling nodes then going down into the next level. You can use a Queue to implement a level order search in a binary tree. If you want to learn more, you can check any of these free data structures and algorithms courses on freeCodeCamp.

Isn't this was the first sorting algorithm you learn? Well, I did and that's why I remember that bubble sort is about comparing each number with every other number in an array so that after each pass the largest or smallest element bubble up to the top. I mean found it's placed in the sorting order. This is one of the fundamental algorithms and the time complexity of this is O(n ^2) which makes it unusable for a large set of numbers but it does well for a small set of numbers.

This one was a tricky concept which I didn't know until long ago. I haven't 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 the latter is a stable algorithm.

It's another popular searching algorithm which is mainly used in tree and graphs. This algorithm first visits nodes in depth before searching at the same level, that's why the name Depth-first search algorithm. It's tricky to implement but you can use a Stack to implement DFS or Depth-first search algorithm. If you need more information on this topic, I suggest you check the

Obviously without recursion:-). If you remember, I have told you before that you can use a Stack to convert a recursive algorithm into an iterative one and that's what you can do as well to implement the Quicksort algorithm without recursion. You can further see the solution if you need more help with respect to implementation.

Just like we have done with other O(n) sorting algorithms like Radix sort and Bucket sort. If you don't know Counting sort is another integer sorting algorithm for sorting a collection of objects according to keys that are small integers. It has O(n) time complexity which makes it faster than the likes of Quicksort and Mergesort for a particular set of input. See the solution for more details.

Another tricky question which is easy if you know the trick :-) Well you can swap two numbers without using a temporary or third variable if you can store the sum of numbers in one number and then minus the sum with another number something like

a = 3;

b = 5;

a = a + b; //8

b = a — b; // 3

a = a — b; //5

now you have a = 5 and b = 3, so numbers are swapped without using a third or temp variable.

This is another integer sorting algorithm with O(n) time complexity. As per Wikipedia, Radix sort is a non-comparative sorting algorithm that sorts data with integer keys by grouping keys by the individual digits which share the same significant position and value. You can further see the solution for implementation details.

Have you ever arranged the deck of cards, or maybe shirts in your cupboard? What is common between those two things? Well, you put the next card or shirt into their proper position, or, should I say you insert the next element in its proper position. That's the insertion sort for you.

This is a tricky Algorithm question but if you have to listen to your teacher in your 2D maths class then you can solve this problem. There is another trick, check for all the conditions when rectangles will not overlap and if any condition is false it means both rectangles are overlapping with each other. For example, if the upper side of one rectangle is below the lower side of other rectangles then they won’t overlap as they are vertically aligned.

Similar to Quicksort, merge sort is also a divide and conquer algorithm i.e. you keep divides the array until you can sort the smallest of the array like an array with one or zero elements. 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 O(nlogn) average time, it’s 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.

The Bucket sort is another awesome algorithm that can sort an array without even comparing elements. It’s known as a non-comparison sorting algorithm and can give O(n) performance for the selected input. If you don’t know about the non-comparison-based sorting Algorithm, please see

An anagram is something where length and character matches but not the order e.g. Army and Mary, both have the same number of characters. One trick is to solve this problem is to sort the character and check if they are the same or not.

This one is a very easy sorting algorithm, but only if you have practiced, if not then you may lose your way. Remember, Quicksort is a divide and conquer algorithm which means you keep dividing array, also known as partitioning. Then you solve the problem at the smallest level, also known as a base case like when your array contains just one or zero elements.

There is a simple trick to solve this problem, just concatenate the string with itself and check if the rotation exists there. If the concatenated String contains rotation then the given String is a rotation of the former.

As the name suggests, in comparison-based sorting algorithms you must compare elements to sort like quicksort, but in non-comparison-based sorting algorithms like Counting sort, you can sort elements without comparing them. Surprised? Well yes, then I suggest you check out this course to learn more about O(n) sorting algorithms like Radix Sort, Counting Sort, and Bucket Sort.

This is one of the tough algorithms to implement especially if you don’t remember it :-) Sometimes the interviewer gives you the explanation but other times you need to remember it.

**Programming job interviews**or looking for a new job then you know that it's not an easy process. You got to be lucky to get a call from recruiter or hiring manager and make to the first round of interview at any stage of your career but it is even more difficult at the beginner level when you are searching for your first job. That's why you can't just take your chance lightly. You got to be prepared to grab that chance and for that, you must know what is expected from you on the interview. What is asked, what topics should you prepare, etc? I have blogged a lot about what you can find helpful articles in this blog but to recap let me tell you that apart from data structure questions, System Design Questions, and Programming language-specific questions like Java or Scala, most of the programming job interviews also ask algorithm based questions.These are based upon common searching and sorting algorithms like binary search, graph algorithms, etc,. It’s important that you practice these Algorithm based questions because even though they seem obvious and easy, sometimes they become tricky to solve in the actual interview, especially if you have never coded them by yourself.

Having practiced them before not only makes you familiar with them but also gives you more confidence in explaining the solution to the interviewer, which plays a very important role in your selection. It also makes you ready for any

**twisted questions and alternative problems**like Interviewers often like to ask you to solve a particular coding problem using Recursion or Iteration.Sometimes, if you use a data structure like the one I have used in finding duplicate characters on String, they will ask you to solve that problem without using the Set data structure. That's just some common example and that's why practice matters a lot.

Btw, if you are a complete beginner in the world of Data Structure and Algorithms, then I suggest you first go through a comprehensive Algorithm course like

**Data Structures and Algorithms: Deep Dive Using Java**on Udemy which will not only teach you basic data structure and algorithms but also how to use them on the real world and how to solve coding problems using them.##
__20+ Algorithms Questions from Coding Interviews__

Anyway, here is some of the frequently asked Searching and Sorting Algorithms questions from Interviews:**1. Can you implement a Binary Search Algorithm? (solution)**It’s easy, binary search is a divide and conquers algorithm, where the problem is divided into sub-problem and those are solved. It’s a search algorithm so it is used to find things like a number in an integer array or an item in a catalog.

The easiest way to implement a binary search algorithm is by using Recursion, which is what the solution link contains but you should try it yourself before seeing the solution.

One of the worth noting is that the input must be sorted, I mean you can only implement binary search in a sorted array.

**2. Write a program to implement a Linear Search Algorithm? (solution)**It is even easier than binary search, all you need to do is go through all elements in the array using a for loop or recursive method and compare each element with the one you want to search. when an element matches you either return index or true/false depending upon your requirement.

For example, if you are writing a contains() method you can return true or false to indicate whether an element is present in the array or not. Since you need to scan the whole array to find the element, the time complexity of this algorithm is O(n).

**3. Can you implement a Binary search Algorithm without recursion? (solution)**You might know that you can replace a recursive algorithm with an iterative one by using a loop or sometimes a stack. For binary search also you can do this, just divide the array and compare the middle element until you find the target element or there is no more element into an array. If the target element is greater than the middle then you got to move towards the right, or otherwise towards the left.

Btw, if you have trouble understanding recursive algorithms or converting a recursive one to an iterative one then I suggest you go through a good online course like

**Algorithms and Data Structures - Part 1**and Part 2 in Pluralsight to learn fundamentals better. These courses will also teach you about how to calculate time and space complexity which is very important from both the Coding Interview perspective as well as improving the performance of an Algorithm.**4. Write a Code to implement Level Order Search in a Binary Tree? (solution)**In level order search you first visit sibling nodes then going down into the next level. You can use a Queue to implement a level order search in a binary tree. If you want to learn more, you can check any of these free data structures and algorithms courses on freeCodeCamp.

**5. Implement the Bubble sort Algorithm? (solution)**Isn't this was the first sorting algorithm you learn? Well, I did and that's why I remember that bubble sort is about comparing each number with every other number in an array so that after each pass the largest or smallest element bubble up to the top. I mean found it's placed in the sorting order. This is one of the fundamental algorithms and the time complexity of this is O(n ^2) which makes it unusable for a large set of numbers but it does well for a small set of numbers.

**6. Difference between a stable and unstable sorting algorithm? (answer)**This one was a tricky concept which I didn't know until long ago. I haven't 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 the latter is a stable algorithm.

**7. What is Depth First Search Algorithm for a binary tree? (solution)**It's another popular searching algorithm which is mainly used in tree and graphs. This algorithm first visits nodes in depth before searching at the same level, that's why the name Depth-first search algorithm. It's tricky to implement but you can use a Stack to implement DFS or Depth-first search algorithm. If you need more information on this topic, I suggest you check the

**Grokking Algorithms**book by Aditya Bhargava, his explanation is probably the best explanation of this topic**8. How is an iterative quicksort algorithm implemented? (solution)**Obviously without recursion:-). If you remember, I have told you before that you can use a Stack to convert a recursive algorithm into an iterative one and that's what you can do as well to implement the Quicksort algorithm without recursion. You can further see the solution if you need more help with respect to implementation.

**9. How do you implement a counting sort algorithm? (solution)**Just like we have done with other O(n) sorting algorithms like Radix sort and Bucket sort. If you don't know Counting sort is another integer sorting algorithm for sorting a collection of objects according to keys that are small integers. It has O(n) time complexity which makes it faster than the likes of Quicksort and Mergesort for a particular set of input. See the solution for more details.

**10. How do you swap two numbers without using the third variable? (solution)**Another tricky question which is easy if you know the trick :-) Well you can swap two numbers without using a temporary or third variable if you can store the sum of numbers in one number and then minus the sum with another number something like

a = 3;

b = 5;

a = a + b; //8

b = a — b; // 3

a = a — b; //5

now you have a = 5 and b = 3, so numbers are swapped without using a third or temp variable.

**11. How is a radix sort algorithm implemented? (solution)**This is another integer sorting algorithm with O(n) time complexity. As per Wikipedia, Radix sort is a non-comparative sorting algorithm that sorts data with integer keys by grouping keys by the individual digits which share the same significant position and value. You can further see the solution for implementation details.

**12. How do you implement an insertion sort algorithm? (solution)**Have you ever arranged the deck of cards, or maybe shirts in your cupboard? What is common between those two things? Well, you put the next card or shirt into their proper position, or, should I say you insert the next element in its proper position. That's the insertion sort for you.

**13. Write the Algorithm to check if two rectangles overlap with each other? (solution)**This is a tricky Algorithm question but if you have to listen to your teacher in your 2D maths class then you can solve this problem. There is another trick, check for all the conditions when rectangles will not overlap and if any condition is false it means both rectangles are overlapping with each other. For example, if the upper side of one rectangle is below the lower side of other rectangles then they won’t overlap as they are vertically aligned.

**14. How is a merge sort algorithm implemented? (solution)**Similar to Quicksort, merge sort is also a divide and conquer algorithm i.e. you keep divides the array until you can sort the smallest of the array like an array with one or zero elements. 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 O(nlogn) average time, it’s 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.

**15. How do you implement a bucket sort algorithm? (solution)**The Bucket sort is another awesome algorithm that can sort an array without even comparing elements. It’s known as a non-comparison sorting algorithm and can give O(n) performance for the selected input. If you don’t know about the non-comparison-based sorting Algorithm, please see

**Introduction to Algorithms**book.**16. Write Algorithms to Check if Two String are Anagram (Solution)**An anagram is something where length and character matches but not the order e.g. Army and Mary, both have the same number of characters. One trick is to solve this problem is to sort the character and check if they are the same or not.

**17. Implement the QuickSort Algorithm in your Favorite Programing language? (solution)**This one is a very easy sorting algorithm, but only if you have practiced, if not then you may lose your way. Remember, Quicksort is a divide and conquer algorithm which means you keep dividing array, also known as partitioning. Then you solve the problem at the smallest level, also known as a base case like when your array contains just one or zero elements.

**18. How to check if two String is rotations of each other? (solution)**There is a simple trick to solve this problem, just concatenate the string with itself and check if the rotation exists there. If the concatenated String contains rotation then the given String is a rotation of the former.

**19, Difference between Comparison and Non-Comparison Sorting Algorithms? (answer)**As the name suggests, in comparison-based sorting algorithms you must compare elements to sort like quicksort, but in non-comparison-based sorting algorithms like Counting sort, you can sort elements without comparing them. Surprised? Well yes, then I suggest you check out this course to learn more about O(n) sorting algorithms like Radix Sort, Counting Sort, and Bucket Sort.

**20. Implement Sieve of Eratosthenes Algorithms for Prime Number? (solution)**This is one of the tough algorithms to implement especially if you don’t remember it :-) Sometimes the interviewer gives you the explanation but other times you need to remember it.

**21. Can we sort in linear time? Which sorting algorithm will you use if you have to sort in O(n) time?**

You can use Radix Sort, Counting Sort, and Bucket Sort to sort a group of elements in linear time.

I hope these 20 questions should be enough to get you going on your preparation for Algorithms for Coding interviews. If you need more such coding questions you can take help from books like

**Cracking The Code Interview**, by Gayle Laakmann McDowell which presents 189+ Programming questions and solutions. A good book to prepare for programming job interviews in a short time.

By the way, the more questions you solve in practice, the better your preparation will be. So, if you think 50 is not enough and you need more, then check out these additional 50 programming questions for telephone interviews and these books and courses for more thorough preparation.

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__Now You’re 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 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 coding questions.

This list provides good topics to prepare and also helps assess your preparation to find out your areas of strength and weakness. Good knowledge of data structure and algorithms is important for success in coding interviews and that’s where you should focus most of your attention.

If you want to master this topic for an interview then a course like

**Data Structures and Algorithms: Deep Dive Using Java**on Udemy is best. It will not only teach you basic data structure and algorithms but also how to use them in the real world and how to solve coding problems using them.

On the other hand, if you like to read books or prefer books over online courses then you must read a comprehensive book like

**Introduction to Algorithms**by Thomas H. Cormen to get an understanding of common Computer Science Algorithms like Searching, Sorting, Cryptography, Graph Algorithms and some common ones like Fourier Transform.

This book is considered as the gold standard of algorithms but at the same time it's not easy to go through it and you need to be patient and persistent to get the best out of it. For less brave souls following resources can be more useful.

**Further Learning**

- Data Structures and Algorithms: Deep Dive Using Java
- Grokking the Coding Interview: Patterns for Coding Questions
- Data Structure and Algorithms Analysis — Job Interview
- 10 Websites to Practice Coding Problems
- 21 String Coding problems from Interviews
- 10 Books to Prepare Technical Programming/Coding Job Interviews
- 20+ binary tree problems from Coding interviews
- 10 Algorithm Books Every Programmer Should Read
- 20 linked list problems from Coding interviews
- Top 5 Data Structure and Algorithm Books for Java Developers
- My favorite free courses to learn Algorithms in depth
- 10 Free Data Structure Courses for Java Developers
- 50 Data Structure and Algorithms Coding Problems from Interviews
- A list of courses to Crack Programming Job Interviews
- 10 Tips and 101 Coding Problems to Crack Programming Interview

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__Closing Notes__

Thanks, You made it to the end of the article … Good luck with your programming interview! It’s certainly not going to be easy, but by following these searching and sorting algorithm questions, you are one step closer than others.If you like this article, then please share it with your friends and colleagues, and don’t forget to follow javarevisited on Twitter and javinpaul as well!

**P.S. —**If you need some FREE resources, you can check out this list of

**free data structure and algorithm courses**to start your preparation.

**P. S. -**Are you ready for the Interview?

**Take TripleByte's quiz**and go directly to the final round of interviews with top tech companies like Coursera, Adobe, Dropbox, Grammarly, Uber, Quora, Evernote, Twitch, and many more.

## 1 comment :

I am not sure but merge sort is not unstable sort. it is stable as mentioned here:

https://www.fullstack.cafe/blog/sorting-algorithms-interview-questions

## Post a Comment