Common Algorithm Interview Questions (With Example Answers)
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Algorithms help software developers write error-free and functional programmes. Since they are integral to computer science, companies often include algorithm questions during technical interviews to test potential hires. Understanding common algorithm interview questions and preparing effective answers for these questions can help one feel more confident and prepared during an interview process. In this article, we discuss common questions asked on this subject and share example answers for each of them to help you model your own.
Common Algorithm Interview Questions
Following are some common algorithm interview questions:
1. What is an algorithm? What are the reasons for using an algorithm?
A good understanding of algorithms is essential to every software programmer. Companies ask this question to assess the candidate's understanding of this fundamental aspect of computer engineering. Knowing the benefits of using algorithms indicates that a candidate is aware of the role algorithms play in developing software.
Example: “An algorithm is a set of steps used to solve a problem or complete a particular task. Algorithms help the designer understand software requirements and outcomes in an effective manner, and provide a good understanding of the program flow. Efficient algorithms can improve the efficiency technique and also help reduce design costs. An algorithm can help break complex problems down into a series of logical steps using which programmers can convert it to a program.”
2. Explain the divide-and-conquer technique in algorithms.
Divide and conquer algorithms can help one solve difficult computational problems. To ace your interview for a coding job, it is integral to understand divide and conquer. Asking this question helps the interviewer assess your approach to solving problems using this strategy.
Example: “The divide-and-conquer algorithm approach involves breaking the original problem into minor problems, solving each problem and putting all solutions together into a single efficient solution. The three steps in this approach are divide, conquer and combine. The first step divides the original problems into subproblems and the conquer step solves each subproblem individually. The last step puts together all the smaller solutions to obtain the solution to the original problem. Binary search, quick sort and merge sort are some examples for divide-and-conquer algorithms.”
3. Explain Dijkstra's shortest path algorithm.
Interviewers ask this question to determine your understanding of this algorithm pattern. In order to answer this question effectively, provide a comprehensive and concise answer with a few real-life examples to show your understanding.
Example: “The Dijkstra's shortest path algorithm finds the shortest path from starting node to target node in weighted graphs. Using the algorithm, we make a tree of the shortest paths which begin from the starting vertex to all the other nodes present in the graph. For example, consider you want to travel from point A to point B in the shortest way possible. Certain congested roads are challenging to navigate and resultantly have a large weight. In accordance to the Dijkstra's shortest path algorithm, the shortest path tree avoids edges with larger weight.”
4. Explain the Quick Sort algorithm and its benefits.
Quick Sort is a sorting algorithm that is quite popular in practice. This is a common question in interviews to assess how well you understand this basic sorting algorithm.
Example: “We use Quick Sort to sort queries and lists quickly. It works on the principle of divide and conquer or partition exchange sort. The algorithm segregates a list into three parts. They are the pivot element, elements less than the pivot element and elements greater than the pivot element. The benefits of Quick Sort are that it does not require extra memory while sorting long lists, occupies less space and is cache-friendly. “
5. Explain time-complexity with respect to algorithms.
Effective programmers can assess the time complexity of algorithms, and help plan resources better, process and achieve efficient results. This is among the most basic questions asked with respect to algorithms to assess your ability and knowledge to enhance existing systems.
Example: “Time-complexity of an algorithm denotes its computational complexity and the amount of computer time to run a particular algorithm. We estimate this value by counting the elementary operations performed as a part of the algorithm. We commonly express the time complexity of algorithms through the big O notation.”
6. Explain the binary search algorithm.
Binary search algorithm is an efficient and popular searching algorithm. Since it is a commonly used technique, interviewers often include this question when testing candidates on algorithms to gauge the depth of knowledge of a potential hire.
Example: “In the binary search algorithm, one compares the key with the element that exists in the middle of the array. If the key is less than the element searched, we understand that it must exist in the lower half part of the array. In case the key is greater than the element searched, then we understand that the element must be in the upper half part of the array.”
7. Explain the bubble sort algorithm.
Bubble sort is one of the simplest sorting algorithms, which is also a common interview question. Interviewers often ask this question to freshers new to programming to evaluate them on basic concepts related to computer science and algorithms.
Example: “Also called sinking sort, bubble sort is one of the simplest sorting algorithms. The algorithm steps through elements in a given list and compares adjacent elements to each other. Then, it swaps adjacent elements that exist in the wrong order. This process repeats until the sorting process is complete and all elements are in the correct order.”
8. What is a recursive algorithm? What are the three laws of recursive algorithms?
Recursive algorithms can be powerful tools for solving functional problems of software. With recursive thinking skills, programmers learn to break down problems into smaller ones, making the understanding of this concept important for interviews.
Example: “A recursive algorithm helps one solve a complex problem by breaking it down into smaller sub-problems until one can solve the smallest sub-problem. A recursive function calls itself and passes the return value to the algorithm as a parameter again. Some examples of recursive algorithms are Fibonacci number series and factorial generation.
Recursive algorithms follow three basic laws, which include a recursive algorithm requires calling itself recursively, a recursive algorithm requires a base case and a recursive algorithm requires changing its state and moving towards the base case.”
9. Explain the differences between the best-case scenario and the worst-case scenario with respect to algorithms.
Interviewers ask this question to understand one's depth of knowledge in the area of algorithm analysis. An understanding of the best-case and worst-case scenarios in algorithms can impact system performance significantly. Briefly explaining each scenario with suitable examples is a good way of answering this question.
Example: “Best-case scenario indicates that the data arrangement is such that the algorithm performs at its optimal best. A good example is a binary search where the target value exists at the centre of the list being searched. A worst-case scenario is when an algorithm receives the worst set of inputs. An example for this can be a Quick Sort, where the pivot value is the smallest or largest element in a sub-list.”
10. How do cryptographic algorithms work? Mention some common examples of cryptographic algorithms.
Cryptographic algorithms play an important role in maintaining the integrity of sensitive information in the digital world. So, it is crucial that programmers understand how these algorithms work.
Example: “Encryption converts plain text into ciphertext or encrypted information. To convert a text into ciphertext, algorithms use special keys (strings of letters or numbers). Encryption algorithms usually use 64 to 128-bit long keys for encryption purposes.
Names of common cryptographic algorithms include LOKI, CAST, Blowfish, 3-way, CMEA, GOST, DES/Triple DES and IDEA.”
11. What are hash algorithms?
Developers use hashing algorithms for a variety of purposes. Understanding the uses and working of hash algorithms is critical for developing efficient software, making it an important question that is asked during interviews. Employers want to assess the candidates' understanding of hash algorithms through this question and the efficiency they can offer.
Example: “A hashing algorithm converts data into a hashed value consisting of a character string of fixed length. It is not possible to decode or unscramble these hashed values, resultantly protecting data inputs from users. Hash algorithms are useful for password storage, document management and protection of digital signatures. The most popular hashing algorithms include SHA, MD-5, Whirlpool and RIPEMD-160.”
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