computer science problem solving questions

• Create A Quiz
• Relationship
• Personality
• Harry Potter
• Online Exam
• Entertainment
• Training Maker
• Survey Maker
• Brain Games
• ProProfs.com

Computer Science Quizzes, Questions & Answers

Top trending quizzes.

Popular Topics

Recent quizzes.

« Previous 1 2 3 Next »

Popular Quizzes

2.2 Computer Science Fundamentals

Wrap your mind around computational thinking, from everyday tasks to algorithms.

Making Decisions

Computers use decision trees to turn many simple decisions into one big decision.

Searching for Solutions

Sometimes, the right way to solve a computational problem is by “brute force.”

• Parallelism

When Pierre the baker wants to get lots of things done, it helps to do many things at once.

End of Unit 1

Complete all lessons above to reach this milestone.

0 of 3 lessons complete

Resource Tradeoffs

Computer scientists deal with tradeoffs all the time. So does Farhad when he does his chores.

Order and Search

Information needs to be organized for use by humans or computers, as Tiye the librarian knows well.

Computer systems and people need to be able to reliably find and access people and resources.

Abstraction

Mayor Jing uses abstraction—a critical tool in computer science—to help her run City Hall.

Abstractions have interfaces that explain what they can and cannot do.

End of Unit 2

0 of 5 lessons complete

Algorithms and Implementations

Algorithms are step-by-step processes for achieving an outcome. They can be very specific or quite general.

Divide and Conquer

Problems often get easier when you split them in half, as the 20 Questions guessing game shows.

• Binary Search

Binary search is a more algorithm-friendly version of the 20 Questions game.

Thinking with Graphs

Graphs are a powerful tool for understanding problems and solving them in clever ways.

Representing Games and Puzzles

Graphs can help us plan solutions to complex problems, like this classic river-crossing puzzle.

Graph Search

Some of the most fundamental algorithms on graphs are designed to get you from point A to point B.

End of Unit 3

0 of 6 lessons complete

Course description

Learn the key ideas of computer science with this interactive course – no coding required! This course is ideal for a high school or college student who wants to learn the fundamentals, or an early professional who wants to strengthen their knowledge of core computer science concepts. Whether you're exploring computer science for the first time or looking to deepen your understanding, this course will allow you to develop the problem-solving techniques you need to think like a computer scientist. Follow librarians, cooks, and mayors to see how computer science problem solving techniques affect their daily lives. Get hands-on with a few specific algorithms, and learn the general principles demonstrated by these algorithms.

Topics covered

• Brute-Force Search
• Concurrency
• Decision Trees
• Graph Abstractions
• Greedy Algorithms
• Programming

Prerequisites and next steps

You don’t need any previous computer science experience to take this course! This course is for anyone excited to actively learn more about how computer scientists think and understand our world.

3.1 Next Steps in Python

Boost your proficiency in Python by learning how to access social media data with public functions.

Problem Solving

Solving problems is the core of computer science. Programmers must first understand how a human solves a problem, then understand how to translate this "algorithm" into something a computer can do, and finally how to "write" the specific syntax (required by a computer) to get the job done. It is sometimes the case that a machine will solve a problem in a completely different way than a human.

Computer Programmers are problem solvers. In order to solve a problem on a computer you must:

Know how to represent the information (data) describing the problem.

Determine the steps to transform the information from one representation into another.

Information Representation

A computer, at heart, is really dumb. It can only really know about a few things... numbers, characters, booleans, and lists (called arrays) of these items. (See Data Types). Everything else must be "approximated" by combinations of these data types.

A good programmer will "encode" all the "facts" necessary to represent a problem in variables (See Variables). Further, there are "good ways" and "bad ways" to encode information. Good ways allow the computer to easily "compute" new information.

An algorithm (see Algorithm) is a set of specific steps to solve a problem. Think of it this way: if you were to tell your 3 year old neice to play your favorite song on the piano (assuming the neice has never played a piano), you would have to tell her where the piano was, and how to sit on the bench, and how to open the cover, and which keys to press, and which order to press them in, etc, etc, etc.

The core of what good programmers do is being able to define the steps necessary to accomplish a goal. Unfortunately, a computer, only knows a very restricted and limited set of possible steps. For example a computer can add two numbers. But if you want to find the average of two numbers, this is beyond the basic capabilities of a computer. To find the average, you must:

• First: Add the two numbers and save this result in a variable
• Then: Divide this new number the number two, and save this result in a variable.
• Finally: provide this number to the rest of the program (or print it for the user).

We "compute" all the time. Computing is the act of solving problems (or coming up with a plan to solve problems) in an organized manner. We don't need computers to "compute". We can use our own brain.

Encapsulation and Abstraction and Complexity Hiding

Computer scientists like to use the fancy word "Encapsulation" to show how smart we are. This is just a term for things we do as humans every day. It is combined with another fancy term: "Abstraction".

Abstraction is the idea of "ignoring the details". For example, a forest is really a vastly complex ecosystem containing trees, animals, water paths, etc, etc, etc. But to a computer scientist (and to a normal person), its just "a forest".

For example, if your professor needs a cup of coffee, and asks you the single item: "Get me a cup of coffee", he has used both encapsulation and abstraction. The number of steps required to actually get the coffee are enumerable. Including, getting up, walking down the hall, getting in your car, driving to a coffee stand, paying for the coffee, etc, etc, etc. Further, the idea of what a cup of coffee is, is abstract. Do you bring a mug of coffee, or a Styrofoam cup? Is it caffeinated or not? Is it freshly brewed or from concentrate? Does it come from Africa or America?

All of this information is TOO MUCH and we would quickly be unable to funciton if we had to remember all of these details. Thus we "abstract away" the details and only remember the few important items.

This brings us to the idea of "Complexity Hiding". Complexity hiding is the idea that most of the times details don't matter. In a computer program, as simple an idea as drawing a square on the screen involves hundreds (if not thousands) of (low level) computer instructions. Again, a person couldn't possible create interesting programs if every time they wanted to do something, they had to re-write (correctly) every one of those instructions. By "ecapsulating" what is meant by "draw square" and "reusing" this operation over and over again, we make programming tractable.

Encapsulation

The idea behind encapsulation is to store the information necessary to a particular idea in a set of variables associated with a single "object". We then create functions to manipulate this object, regardless of what the actual data is. From that point on, we treat the idea from a "high level" rather than worry about all the parts (data) and actions (functions) necessary to represent the object in a computer.

Brute Force

Brute force is a technique for solving problems that relies on a computers speed (how fast it can repeat steps) to solve a problem. For example, if you wanted to know how many times the number 8 goes into the number 100, you could do the following:

Of course this is a silly way for a computer (or a human) to solve this problem. The real way we would do it is:

When in doubt, you can often use "brute force" to solve a problem, but it often saves time (at least computer time) to think about the problem and solve it in an elegant manner.

Browse Course Material

Course info.

• Prof. John Guttag

Departments

• Electrical Engineering and Computer Science

As Taught In

• Computer Science

Introduction to Computer Science and Programming

Lecture 3: problem solving.

• Download video
• Download transcript

You are leaving MIT OpenCourseWare

Classic Computer Science Problems

Essential techniques for practicing programmers, a book series by david kopec, free content.

• Contact David

Classic Computer Science Problems is a series of books that helps software developers learn several problem solving techniques from the realm of computer science. The series spans three programming languages and nine human languages. The books are written in a tutorial-like, code-centric format. They are appropriate for experienced software developers who want to refresh their skillset, and intermediate programmers who are looking to take their skills to the next level. They can also be helpful when learning some of the more advanced aspects of the programming languages covered by the series.

The three books in the series are Classic Computer Science Problems in Java , Classic Computer Science Problems in Python , and Classic Computer Science Problems in Swift . They are published by Manning . Reading each book does not require a CS degree. In fact, self-taught programmers will get a useful survey of computer science topics they missed by not having a CS education. The books are broad, not deep. Each topic is covered by going over some classic problems, typically taught in a CS undergraduate curriculum, and their solutions in the book's respective language.

These are not textbooks. They are not heavy on mathematical notation, nor do they claim to be replacements for a class in data structures and algorithms. Instead, they aim to excite developers and students about engaging computer science topics by presenting them succinctly with working code in the language of the reader's choice.

The computer science topics touched on through the problems are wide ranging and include:

• Memoization
• Bit Manipulation
• Dynamic Programming
• Permutation Generation
• Binary Search
• Breadth-First Search
• Depth-First Search
• Constraint Satisfaction Problems
• Representing Graphs using Hybrid Adjacency Lists
• Search in Graphs
• Finding shortest paths with Dijkstra's Algorithm
• Finding the minimum-spanning tree with Jarnik's Algorithm (Prim's Algorithm)
• Genetic Algorithms
• K-means Clustering
• Neural Networks
• Alpha beta pruning (Python, Java books only)

Classic Computer Science Problems in Java

• Requires Java 11+
• Published in December, 2020
• Available in English in print from Manning , Amazon , and other fine book sellers.
• Available in English in PDF, .mobi (Kindle), and .epub (Apple Books & Other E-readers) from Manning
• Published in German by Rheinwerk Computing and available from Amazon Germany

Classic Computer Science Problems in Python

• Requires Python 3.7+
• Published in March, 2019
• Every code example uses type hints
• Available in English in PDF, .mobi (Kindle), and .epub (Apple Books & Other E-readers) from Manning .
• Published in Japanese by O'Reilly Japan and available from Amazon Japan .
• Published in Portuguese by Novatec Editora and available from Amazon Brazil .
• Published in Russian by Piter
• Published in Polish by Wydawnictwo Naukowe PWN
• Published in Korean by Hanbit Media
• Published in Simplified Chinese by Posts & Telecom Press
• A Traditional Chinese version is in the works.

Classic Computer Science Problems in Swift

• Written against Swift 4.1 (Xcode 9), all examples compile in Swift 4.2 (Xcode 10)
• Published in April, 2018
• Available in Simplified Chinese from Amazon China .

The source code from all of the books is freely available under the terms of the Apache License. This effectively means you can reuse the code in any project you work on, whether personal or commercial, as long as you credit me/the book in an acknowledgement. You can find repositories on GitHub containing the source code for the Java book , the Python book , and the Swift book .

The code has been ported by readers (and in the case of PHP and JavaScript, the German translator) to C++ , Go , PHP , JavaScript , Ruby , and Rust . So, in total, the source code is available in 8 programming languages. Please let me know if you port the book to another language. I would love to link to that here.

The series has been fortunate to receive great reviews from official reviewers and readers alike.

Praise for Classic Computer Science Problems in Python

Praise for classic computer science problems in swift, interviews with david, codexpanse (august, 2020).

#5 – David Kopec: Classic Computer Science Problems in Java

Profitable Python (April, 2020)

Classic Computer Science Problems in Python | David Kopec

The Local Maximum (December, 2019)

Episode 97: Classic Computer Science Problems with David Kopec

Data Science at Home (July, 2019)

Episode 67: Classic Computer Science Problems in Python

Castalio (June, 2019)

Episode 142: David Kopec - Classic Computer Science Problems in Python

Talk Python to Me (May, 2019)

#211 Classic CS problems in Python

Podcast.__init__ (February, 2019)

Classic Computer Science For Pythonistas - Episode 197

Inside iOS Dev (July, 2018)

Classic Computer Science Problems in Swift with David Kopec

The Learn Swift Podcast (June, 2018)

29: David Kopec - Assistant Professor @ Champlain College and Author of Classic Computer Science Problems in Swift

• Article: Constraint-Satisfaction Problems in Python
• Video: Constraint-Satisfaction Problems in Python
• Chapter 2: Search Problems (PDF)
• Chapter 4: Graph Problems (PDF)
• Article: Solving Mazes with Swift
• Slideshare: A* Search in Swift: navigating a maze
• Article: Tic-Tac-Toe (in Swift)

Open Source Projects Related to the Books

The Swift book was based on several (fairly small) open source projects that I had worked on prior to writing it.

• SwiftPriorityQueue
• SwiftSimpleNeuralNetwork

Questions (and Answers)

Are these books suitable for beginning programmers.

Not really: The books in the series assume at least intermediate knowledge of the programming language they are written against. For example, you should be at least an intermediate Python programmer before picking up Classic Computer Science Problems in Python . You do not need to have taken a data structures and algorithms class, though. No data structures and algorithms knowledge is assumed, but programming knowledge is.

Are the books a good way to learn the programming languages that they cover?

Generally, no, but for some readers, yes. I have heard some readers have used them that way, but I think this will only work for programmers who are very experienced in another language prior to picking up the book. There is no "beginners" content about how to use each of the languages in the books. That said, if you are already an intermediate programmer in the given language, reading the book will help you learn some of the language's more advanced constructs. For example, if you have some basic knowledge of Swift and a strong programming background, you will better understand protocol-oriented programming and Swift enums after reading Classic Computer Science Problems in Swift .

Why isn't sorting or some other classic data structures and algorithms topic covered in the series?

These books are not data structures and algorithms textbooks. They don't claim to be that, and they are geared for a slightly different audience. These are broad survey books that cover a large variety of computer science topics in a succinct, friendly, tutorial-like fashion, heavy with a lot of real code. In other words, they are not meant to be academically rigorous, but instead fun while still being educational. Frankly, some of the cliche topics, like sorting, are left out because they will bore many of the self-taught programmers who will pickup the books. The breadth of topics covered in the series actually stretches beyond the gamut of most data structures and algorithms textbooks by covering several topics from artificial intelligence. About half of each book's content can be considered AI. On the other hand, yes, several traditional data structures and algorithms topics are left out.

Will a book in the series in another programming language come out?

It's not likely to happen in the near-term. I think three programming languages is enough for a while. We did three languages in three years (Swift 2018, Python 2019, Java 2020). In the future, depending on the success of the Java book and the publisher's interest, I am open to working with a co-author on a "port" of the book to a language that I am less familiar with. Go is one language the publisher and I have discussed. We've also discussed Rust, Kotlin, JavaScript, C#, and more. However, beyond Java, these books would be looking at release dates of 2022 or later if they happen. If you look at the Code section above though, you can find ports of the books' code to many other programming languages.

Will a book in the series be translated into another human language?

Yes, Classic Computer Science Problems in Python has been translated into Japanese , Polish , Portuguese , German , Russian , Korean , and Simplified Chinese . The rights to translate Classic Computer Science Problems in Python into Traditional Chinese have been acquired as well. Classic Computer Science Problems in Swift is available in Simplified Chinese . Classic Computer Science Problems in Java is available in German . If you are interested in acquiring the rights to translate one of the books into another language, please contact me and I will put you in touch with the appropriate person at the publisher.

How much do the books cost?

The MSRP of the English print editions ranges from $39.99 to $49.99. However, you can often find them cheaper than that from third-party booksellers. Every English print edition copy comes with a way to download the eBook for free from Manning's website. The standalone DRM-free eBooks are available for less from Manning directly. As a bonus for reading this far, here is a promo code: ccspkopec should get you 40% off on Manning.com for any of the books ( links to Manning's website are above). Please let me know if the promo code does not work for you.

I know of a classic problem you didn't include in the book.

Please let me know about it if you think it's just esoteric enough that I haven't heard of it, but it's still fairly classic.

What references did you use when writing the book?

As you can see from footnotes and the More Resources appendix, the two books I relied most heavily upon as references are Algorithms by Sedgewick and Wayne and Artificial Intelligence: A Modern Approach by Russell and Norvig. I also relied on Introduction to Algorithms by Cormen, Leiserson, Rivest, and Stein, The Algorithm Design Manual by Skiena, and Artificial Intelligence in the 21st Century by my late father, Danny Kopec, and Lucci, as further references. I was fortunate to see most of the classic computer science problems in the books during my education at Dartmouth, so I must extend a thank you to the faculty there, especially Tom Cormen and Devin Balkcom. Since, once again (see the earlier question on why certain data structure and algorithms topics are not in the series), these books are not textbooks, if you want a more academically rigorous introduction to the topics covered, I recommend the above mentioned textbooks.

What is the background of the author?

I am an associate professor of Computer Science and Innovation at Champlain College, a small teaching college in Burlington, Vermont, USA . I have worked professionally as a software developer and I am an active contributor to open source projects. I am also the author of Dart for Absolute Beginners (Apress, 2014) but I no longer recommend that book since it is now significantly out-of-date. I hold a bachelor's degree in economics from Dartmouth College and a master's degree in computer science, also from Dartmouth. I live in Burlington with my wife, Rebecca, and my kids. I co-host a podcast about business books and a podcast explaining software for laypeople.

I always love to hear from readers. Please send me your questions or comments on X or by email .

If you'd like to get notified about my future books and other projects through a very low volume newsletter, please subscribe below.

PapersByTopic

IGCSE Computer Science By Topic

1.1 data representation, 1.1.1 binary systems, 1.1.2 hexadecimal, 1.1.3 data storage, 1.2 communication and internet technologies, 1.2.1 data transmission, 1.2.2 security aspects, 1.2.3 internet principles of operation, 1.3 hardware and software, 1.3.1 logic gates, 1.3.2 computer architecture and the fetch-execute cycle, 1.3.3 input devices, 1.3.4 output devices, 1.3.5 memory, storage devices and media, 1.3.6 operating systems, 1.3.7 high- and low-level languages and their translators, 1.4 security, 1.4.1 security, 2.1 algorithm design and problem-solving, 2.1.1 problem-solving and design, 2.1.2 pseudocode and flowcharts, 2.2 programming, 2.2.1 programming concepts, 2.2.2 data structures; arrays, 2.3 databases, privacy overview.

Necessary cookies are absolutely essential for the website to function properly. This category only includes cookies that ensures basic functionalities and security features of the website. These cookies do not store any personal information.

Any cookies that may not be particularly necessary for the website to function and is used specifically to collect user personal data via analytics, ads, other embedded contents are termed as non-necessary cookies. It is mandatory to procure user consent prior to running these cookies on your website.

If you're seeing this message, it means we're having trouble loading external resources on our website.

If you're behind a web filter, please make sure that the domains *.kastatic.org and *.kasandbox.org are unblocked.

To log in and use all the features of Khan Academy, please enable JavaScript in your browser.

AP®︎/College Computer Science Principles

Course: ap®︎/college computer science principles   >   unit 4.

• Using heuristics

Undecidable problems

• Solving hard problems

The halting problem

More undecidable problems, want to join the conversation.

• Upvote Button navigates to signup page
• Downvote Button navigates to signup page
• Flag Button navigates to signup page

100+ Coding Interview Questions for Programmers and Software Engineers in 2024

Solve these frequently asked coding problems to do well on your next programming job interviews..

Coding Interviews are such an important thing in a programmer’s life that he just can’t get away with that. It’s the first hurdle they need to cross to get the software developer job they wish throughout their school and college days.

To make the matter worse, you will find that so many people on the internet telling that coding interview is flawed, the hiring process for programmers sucks, and so on but you don’t need to pay attention to them, not at least at the start of your career.

They may be right but they are inside the train which you are trying to get into. No matter, how much they criticize the coding interviews and programmers hiring process, many of them have gone through the same route to where they are.

We all know that Coding Interview System is not perfect and many are trying to change it but until it's changed, you got to follow its rules to get into the System. This is something for experience developers to deal with, as a junior developer your priority should be to clear the coding interview and get the job you want.

As an author of a Java blog and a Medium publication , I receive a lot of queries related to coding problems and how to deal with them and that’s why I keep writing articles like this which have helped a lot of programmers directly and in-directly in their career.

In this article, I am going to share with you the top 100 coding interview problems from programming job interviews which every programmer should know.

What to prepare for Coding Interviews?

Now that, I have cleared the confusion that Coding interviews is important and you should not distract, let’s get into real work. The big question is what to prepare for Coding interviews?

Well, the most important thing to prepare is Data Structure-based coding problems like array-based coding problems, string problems, linked list problems, binary tree problems, etc.

Apart from data structure-based questions, most of the programming job interviews also ask algorithm, design, bit manipulation, and general logic-based questions, which I’ll describe in this section.

It’s important that you practice these concepts because sometimes they become tricky to solve in the actual interview. Having practiced them before not only makes you familiar with them but also gives you more confidence in explaining the solution to the interviewer.

One of the main problems with coding problems is that there are hundreds and thousands of coding problems on interviews, there are even sites like LeetCode , HackerRank , Codewars , Topcoder , freeCodeCamp , HackerEarth which train programmers for coding interviews with lots of tough questions, which sometimes just overwhelms a beginner looking for a job.

I believe in simplicity and the 10% of effort which produce 90% of results and that’s why I have collected top 100 coding problems which are not too tough and also frequently asked on real interviews.

Solving these problems not only gives you confidence but also helps you to recognize some of the most common algorithmic patterns which will also help you to solve some unseen problems in real interviews.

Best Resources for Coding Interviews

The selection of good resources is very important for success in your coding interviews. If you chose the wrong resource then more than money, you will lose the valuable time you need for preparation, hence spending some time researching for a good resource.

If you need recommendations, the following are some of my the tried and tested resources to learn Data Structure and Algorithms in-depth for coding interviews:

• Data Structures and Algorithms: Deep Dive Using Java for Java developers. Learn about Arrays, Linked Lists, Trees, Hashtables, Stacks, Queues, Heaps, Sort algorithms, and Search algorithms

Data Structures and Algorithms: Deep Dive Using Java

So you've worked with the basics of data structures and algorithms in java (or another oo programming language) but….

• Algorithms and Data Structures in Python for those who love Python A guide to implementing the most up to date algorithms from scratch: arrays, linked lists, graph algorithms, and sorting

Algorithms and Data Structures in Python

This course is about data structures and algorithms. we are going to implement the problems in python. i highly….

• JavaScript Algorithms and Data Structures Masterclass by Colt_Steele for JavaScript programmers. The Missing Computer Science and Coding Interview Bootcamp. Learn everything you need to ace difficult coding interviews.

JavaScript Algorithms and Data Structures Masterclass

This course crams months of computer science and interview prep material into 20 hours of video. the content is based….

• Mastering Data Structures & Algorithms using C and C++ for those who are good at C/C++
• Data Structures in Java: An Interview Refresher by The Educative Team to refresh important Data Structure and algorithms concepts in Java. This course contains a detailed review of all the common data structures and provides implementation-level details in Java to allow readers to become well equipped.
• Grokking the Coding Interview: Patterns for Coding Questions by Fahim ul Haq and The Educative Team This is like the meta course for coding interviews, which will not teach you how to solve a coding problem but, instead, teach you how to solve a particular type of coding problem using patterns. Master these 15 underlying patterns to interview questions, and you’ll be able to tackle anything you face on the interview

Grokking the Coding Interview: Patterns for Coding Questions

Coding interviews are getting harder every day. a few years back, brushing up on key data structures and going through….

www.educative.io

System Design is another topic which is quite important for coding interviews and when it comes to System design , there are not many places where you can learn System design concepts and architecture in depth, but ByteByteGo is exceptional.

ByteByteGo | Ace Your Next System Design Interview

Everything you need to take your system design skill to the next level.

bytebytego.com

It’s one of those sites where I have learned a lot. They explain many key System design concept like Microservices , load balancing, caching, Algorithms like CAP theorem and how to design a particular system with easily digestible diagram. It’s created by Alex Xu, author of System Design Interview — An insider’s guide , one of the best System Design book , and I highly recommend this to everyone preparing for coding interviews.

System Design Interview - An insider's guide

Buy system design interview - an insider's guide on amazon.com ✓ free shipping on qualified orders.

www.amazon.com

And, if you prefer books, there is no better than the Cracking The Coding 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. Btw, I will also earn some money if you buy any of these resources mentioned here.

5 Best Tips to Crack Coding Interviews in 2023

Here are a few of my practical tips to crack your next coding interview. These are hard-earned and I learned from my own mistakes and experience.

• There is no better way to do well in Coding interviews than practicing as many coding problems as possible. This will not only train your mind to recognize algorithmic patterns in problems but also give you the much-needed confidence to solve problems you have never seen before.
• My second tips are to learn about as many data structure and algorithms as possible. This is an extension of the previous tip but it also involves reading and not just practicing. For example, If you know about the hash table you can also many array and counter-based problems easily. The same is true for trees and graphs.
• Choosing the right data structure is a very important part of software development and coding interview and unless and until you know them, you won’t be able to choose.
• Time yourself — candidates who solve interview problems within the time limit and quickly are more likely to do well in the interview so you should also time yourself.
• Think of edge cases and run your code through them. Some good edge cases might be the empty input, some weird input, or some really large input to test the boundary conditions and limits.
• After solving the problem, try explaining it to a friend or colleague how is also interested in coding problems. This will tell you whether you have really understood the problem or not. If you can explain easily means you understood . Also, the discussion makes your mind work and you could come up with an alternative solution and be able to find some flaws in your existing algorithms.
• Another useful tip to excel in Coding interviews is to appear in the coding interview and lots of them. You will find yourself getting better after every interview and this also helps you to get multiple offers which further allows you to better negotiate and get those extra 30K to 50K which you generally leave on a table if you just have one offer in hand.
• Btw, If you are ready for Coding Interview then you can also take TripleByte’s quiz and go directly to the final round of interviews with top tech companies like Coursera , Adobe Acrobat , Dropbox , Grammarly , Uber , Quora , Evernote , Twitch , and many more. I didn’t know about Triplebyte before, but they are providing a great service to job seekers. A big thanks to them.

Triplebyte: Software Engineer Job Search

Take a quiz. get offers from multiple top tech companies at once..

triplebyte.com

Top 100 Coding Problems from Programming Job interviews

Without wasting any more of your time, here is my list of 100 frequently asked coding problems from programming job interviews. In order to get most of this list, I suggest actually solving the problem.

Do it yourself, no matter whether you are stuck because that’s the only way to learn. After solving a couple of problems you will gain confidence.

I also suggest you look at the solution when you are stuck or after you have solved the problem, this way you learn to compare different solutions and how to approach a problem from a different angle.

• How is a bubble sort algorithm implemented? ( solution )
• How is a merge sort algorithm implemented? ( solution )
• How do you count the occurrence of a given character in a string? ( solution )
• How do you print the first non-repeated character from a string? ( solution )
• How do you convert a given String into int like the atoi() ? ( solution )
• How do you implement a bucket sort algorithm? ( solution )
• How do you implement a counting sort algorithm? ( solution )
• How do you remove duplicates from an array in place? ( solution )
• How do you reverse an array in place in Java? ( solution )
• How are duplicates removed from an array without using any library? ( solution )
• How is a radix sort algorithm implemented? ( solution )
• How do you swap two numbers without using the third variable? ( solution )
• How do you check if two rectangles overlap with each other? ( solution )
• How do you design a vending machine? ( solution )
• How do you find the missing number in a given integer array of 1 to 100? ( solution )
• How do you find the duplicate number on a given integer array? ( solution )
• How do you find duplicate numbers in an array if it contains multiple duplicates? ( solution )
• Difference between a stable and unstable sorting algorithm? ( answer )
• How is an iterative quicksort algorithm implemented? ( solution )
• How do you find the largest and smallest number in an unsorted integer array? ( solution )
• How do you reverse a linked list in place? (solution)
• How to add an element at the middle of the linked list? (solution)
• How do you sort a linked list in Java? ( solution )
• How do you find all pairs of an integer array whose sum is equal to a given number? ( solution )
• How do you implement an insertion sort algorithm? ( solution )
• How are duplicates removed from a given array in Java? ( solution )
• how to remove the duplicate character from String? ( solution )
• How to find the maximum occurring character in a given String? ( solution )
• How is an integer array sorted in place using the quicksort algorithm? ( solution )
• How do you reverse a given string in place? ( solution )
• How do you print duplicate characters from a string? ( solution )
• How do you check if two strings are anagrams of each other? ( solution )
• How do you find all the permutations of a string? ( solution )
• How can a given string be reversed using recursion? ( solution )
• How do you check if a given string is a palindrome? ( solution )
• How do you find the length of the longest substring without repeating characters? (solution)
• Given string str, How do you find the longest palindromic substring in str? (solution)
• How do you check if a string contains only digits? ( solution )
• How to remove Nth Node from the end of a linked list? ( solution )
• How to merge two sorted linked lists? (solution)
• How to convert a sorted list to a binary search tree? ( solution )
• How do you find duplicate characters in a given string? ( solution )
• How do you count the number of vowels and consonants in a given string? ( solution )
• How do you reverse words in a given sentence without using any library method? ( solution )
• How do you check if two strings are a rotation of each other? ( solution )
• How to convert a byte array to String? ( solution )
• How do you remove a given character from String? ( solution )
• How do you find the middle element of a singly linked list in one pass? ( solution )
• How do you check if a given linked list contains a cycle? How do you find the starting node of the cycle? ( solution )
• How do you reverse a linked list? ( solution )
• How do you reverse a singly linked list without recursion? ( solution )
• How are duplicate nodes removed in an unsorted linked list? ( solution )
• How do you find the length of a singly linked list? ( solution )
• How do you find the third node from the end in a singly linked list? ( solution )
• How do you find the sum of two linked lists using Stack? ( solution )
• What is the difference between array and linked list? ( answer )
• How to remove duplicates from a sorted linked list? ( solution )
• How to find the node at which the intersection of two singly linked lists begins. ( solution )
• Given a linked list and a value x , partition it such that all nodes less than x come before nodes greater than or equal to x . ( solution )
• How to check if a given linked list is a palindrome? (solution)
• How to remove all elements from a linked list of integers which matches with given value? (solution)
• How is a binary search tree implemented? ( solution )
• How do you perform preorder traversal in a given binary tree? ( solution )
• How do you traverse a given binary tree in preorder without recursion? ( solution )
• How do you perform an inorder traversal in a given binary tree? ( solution )
• How do you print all nodes of a given binary tree using inorder traversal without recursion? ( solution )
• How do you implement a postorder traversal algorithm? ( solution )
• How do you traverse a binary tree in postorder traversal without recursion? ( solution )
• How are all leaves of a binary search tree printed? ( solution )
• How do you count a number of leaf nodes in a given binary tree? ( solution )
• How do you perform a binary search in a given array? ( solution )
• How to Swap two numbers without using the third variable? ( solution )
• How to check if two rectangles overlap with each other? ( solution )
• How to design a Vending Machine? ( solution )
• How to implement an LRU Cache in your favorite programming language? ( solution )
• How to check if a given number is a Palindrome? ( solution )
• How to check if a given number is an Armstrong number? ( solution )
• How to find all prime factors of a given number? ( solution )
• How to check if a given number is positive or negative in Java? ( solution )
• How to find the largest prime factor of a given integral number? ( solution )
• How to print all prime numbers up to a given number? ( solution )
• How to print Floyd’s triangle? ( solution )
• How to print Pascal’s triangle? ( solution )
• How to calculate the square root of a given number? ( solution )
• How to check if the given number is a prime number? ( solution )
• How to add two numbers without using the plus operator in Java? ( solution )
• How to check if a given number is even/odd without using the Arithmetic operator? ( solution )
• How to print a given Pyramid structure? ( solution )
• How to find the highest repeating world from a given file in Java? ( solution )
• How to reverse a given Integer in Java? ( solution )
• How to convert a decimal number to binary in Java? ( solution )
• How to check if a given year is a leap year in Java? ( solution )
• Can you implement a Binary search Algorithm without recursion? ( solution )
• What is Depth First Search Algorithm for a binary tree? (solution)
• What is the difference between Comparison and Non-Comparison Sorting Algorithms? ( answer )
• How do implement Sieve of Eratosthenes Algorithms for Prime Number? ( solution )

These many questions should be enough but 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.

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 algorithm questions are the ones you need to know to successfully interview any company, big or small, for any level of programming job.

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.

Further Learning Data Structures and Algorithms: Deep Dive Using Java 10 Books to Prepare Technical Programming/Coding Job Interviews 10 Algorithm Books Every Programmer Should Read Top 5 Data Structure and Algorithm Books for Java Developers From 0 to 1: Data Structures & Algorithms in Java Data Structure and Algorithms Analysis — Job Interview 20+ String based coding problems from interviews 20+ linked list problems from interviews 20+ basic algorithms based problems from interviews ByteByteGo for System Design and Architecture

And, if you like to watch videos, here are videos where you will data structure and algorithms courses and tutorials:

and here are free DSA tutorials

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.

By the way, the more questions you solve in practice, the better your preparation will be.

So, if you think 100 coding problems are 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.

All the best for your coding interview.

Other Articles you may like:

Top 10 Free Data Structure and Algorithms Courses for Beginners — Best of Lot

Algorithms and data structure are two of the most fundamentals and essential topics from computer science, which is…, 10 best books for data structure and algorithms for beginners in java, c/c++, and python, algorithms are language agnostic, and any programmer worth their salt should be able to convert them to code in their…, my favorite free courses to learn data structures and algorithms in depth, by javinpaul data structures and algorithms are some of the most essential topics for programmers, both to get a job….

www.freecodecamp.org

Written by javinpaul

I am Java programmer, blogger, working on Java, J2EE, UNIX, FIX Protocol. I share Java tips on http://javarevisited.blogspot.com and http://java67.com

More from javinpaul and codeburst

Javarevisited

The 2024 Software Architect or Solution Architect RoadMap

An illustrated guide to becoming a software architect in 2024 with links to relevant courses.

How To Create Horizontal Scrolling Containers

As a front end developer, more and more frequently i am given designs that include a horizontal scrolling component. this has become….

Top 50 Java Interview Questions for Beginners and Junior Developers

A list of frequently asked java questions and answers from programming job interviews of java developers of different experience..

The 2024 Java Programmer RoadMap

An illustrated guide to becoming a java developer in 2024 with links to relevant courses, recommended from medium.

Alex Klimenko

Java: Mastering SOLID Principles

Building robust and maintainable software.

Practical Tips for Job Searching

In the ever-changing landscape of the job market, finding a new job can seem like a challenging expedition. i’ve had the privilege of….

General Coding Knowledge

Coding & Development

Stories to Help You Grow as a Software Developer

Predictive Modeling w/ Python

Nathan Byers

10 MORE Books That Every Software Developer Must Read in 2024

In the ever-evolving world of software development, continual learning is key. building on our previous recommendations, here are 10 more….

Tanvi Upadhyay

20 Basic Coding Patterns You Need To Keep Handy

Navigate the coding maze with 20 patterns. crack the code or succumb to fate.

I Solved 300+ Leetcode problems , Here is what I learnt.

Somnath Singh

Level Up Coding

The Era of High-Paying Tech Jobs is Over

The death of tech jobs..

Text to speech

Have an account?

iGCSE Computer Science: Problem Solving

9th - 12th grade.

20 questions

Introducing new   Paper mode

No student devices needed.   Know more

Which of these activities are examples of following an algorithm?

Playing a game of chess

Baking a cake

Playing a piece of sheet music on the piano

Following directions from Google Maps

Which of these are fundamental control structures in any computer program?

A structured approach to programming which involves breaking a large program down into a number of smaller sub-programs is called ...

object orientation

decomposition

abstraction

Which of these are valid methods of representing the steps of an algorithm? (select all that apply)

Program code

Which of these are valid reasons for using subprograms to structure a program? (select all that apply)

Fewer lines of code

Can test subprograms independently

Avoids repetition of code

Different programmers can work on different parts of the program

Avoids need to use local variables

Which of these are recognised techniques of Computational Thinking? (select all that apply)

Decomposition

Abstraction

Pattern recognition

Brute-force search

Abstraction is a recognised technique of Computational Thinking. Which of these is the best definition of abstraction?

Creating a set of logical steps that when followed achieve a particular task

Breaking a problem down into several layers of smaller and simpler subproblems

The process of removing or hiding unnecessary detail from a problem

Exploiting the recurrence of patterns in data to make processing more efficient

Which of these sorting algorithms is the most efficient?

Bubble sort

Insertion sort

Selection sort

Which of these sorting algorithms uses recursion?

For which algorithm would it be best to use a conditional loop?

Finding largest number in a list

Calculating average of a list of numbers

Counting occurrences of an item in a list

Checking if an item is in a list

For which algorithm would it be best to use an unconditional loop?

Validating username and password

Adding up numbers in a list

Finding first occurrence of a number in a list

Validating user input for date of birth

What would the list [9, 6, 12, 7, 3, 16, 10] look like after one iteration of the Bubble sort algorithm (smallest to biggest)?

[6, 9, 7, 3, 12, 10, 16]

[3, 9, 6, 12, 7, 16, 10]

[3, 6, 7, 9, 10, 12, 16]

[9, 6, 12, 3, 7, 16, 10]

Which of these algorithms is an example of a divide-and-conquer type algorithm?

Binary search

Linear search

Count occurrences

What is the standard Scientific measurement for measuring algorithm efficiency?

Big-O notation

Scientific notation

Floating-point

Which is the correct flowchart symbol for input/output?

This is the main loop from an algorithm (shown in Python.) Which algorithm is it?

LInear search

BInary search

Find maximum

This is the main loop from an algorithm (shown in pseudocode.) Which algorithm is it?

Explore all questions with a free account

Continue with email

Continue with phone

• Python for Machine Learning
• Machine Learning with R
• Machine Learning Algorithms
• Math for Machine Learning
• Machine Learning Interview Questions
• ML Projects
• Deep Learning
• Computer vision
• Data Science
• Artificial Intelligence
• Quantiphi Interview Experience for ChatBot Engineer (On-Campus)
• Wadhwani AI Interview Experience for ML Engineer 2023
• TCS Interview Experience for System Engineer
• DELL Interview Experience for Platform Engineer
• SquadStack Interview Experience for Product Engineer
• Neosoft Interview Experience for Trainee Engineer
• Visa Interview Experience for Senior Data Engineer FTE
• Promact Interview Experience for Software Engineer
• TCS Digital Interview Experience for System Engineer
• TRIANZ Interview Experience For Software Engineer
• Quantiphi Interview Experience 9
• Quantiphi Interview Experience (On-Campus)
• Sophos Interview Experience for Software Engineer 2021
• Truminds Interview Experience for Software Engineer
• Quantiphi Interview Experience
• Searce Interview Experience for Software Engineer
• Qualitest Interview Experience for Graduate Engineer
• Accenture Interview Experience for Software Engineer

Quantiphi Interview Experience For A ML Ops Engineer

The interview process at Quantiphi began with a warm introduction. They wanted to know more about my background, my journey into ML Ops, and what drew me to Quantiphi specifically. It felt more like a conversation than an interrogation. They asked about my experiences my qualifications in deploying and managing machine learning models, and how I tackled challenges in previous projects in my colleges or anywhere.

They asked me questions like:

• Can you tell us about your journey and why you chose the path of ML Ops engineer?
• What are some of the projects you’ve worked on involving the deployment and management of machine learning models?
• How do you handle challenges that arise during the deployment phase of ML projects?

Round 2: The Technical round

In the second round, they dove into the technical aspects. They asked detailed questions about the tools and technologies I’ve used, my understanding of cloud platforms, containerization, orchestration tools, and version control systems. They asked me

• Could you walk us through your experience with cloud platforms like AWS or GCP?
• What containerization tools have you worked with, and how do you ensure scalability and reliability in your deployments?
• How do you manage version control for machine learning models, especially when dealing with multiple versions and iterations?

Round 3: The Problem-Solving Challenge

This round was all about putting theory into practice. They presented me with a real-world scenario where a machine learning model needed to be deployed in a production environment, and I had to outline the steps I would take to ensure a smooth deployment and ongoing management. It was a hands-on discussion that allowed me to showcase my problem-solving skills.

Round 4: The Cultural Fit

The final round wasn’t just about skills; it was about fit. They wanted to gauge whether I would thrive in their collaborative and innovative environment. We discussed team dynamics, communication styles, and how I approach learning and personal growth. It was refreshing to see how much they valued culture fit alongside technical expertise. They discussed

• How do you collaborate with team members, especially across different functions like data science, engineering, and operations?
• Can you describe a time when you had to adapt to a new technology or approach, and how did you approach the learning process?
• What do you value most in a work environment, and how do you contribute to fostering that environment?

Overall, my interview experience at Quantiphi was both challenging and enjoyable. Each round felt like a meaningful exchange rather than a test, and it gave me a great sense of the company’s values and culture. I left feeling excited about the opportunity to join their team and contribute to their cutting-edge ML Ops projects.

Please Login to comment...

Similar reads.

• Machine Learning
• Write It Up 2024
• Experiences
• Interview Experiences

Improve your Coding Skills with Practice

What kind of Experience do you want to share?