Top 10 Algorithms to Prepare for Coding Interviews

Top 10 Algorithms to Prepare for Coding Interviews
Algorithms to prepare for Coding Interviews

Data structure and algorithms are vast topics in the world of web development. This is why many of us feel rather confused when we are preparing DSA questions for coding interviews. It is only natural that we cannot memorize all the algorithms and problem-solving questions. However, there are some very important algorithms that you must learn for any coding interview.

In this article, we will discuss the top 10 algorithms that you should definitely prepare for before sitting for any coding interview and wanting to crack it.


Sorting is the most frequently asked algorithm in coding interviews. Sorting questions are often asked directly. For example, interviewers can ask you to code using merge sort or quick sort. Interviewers also focus on theoretical questions related to sorting, such as “What is the complexity of a merge sort in the best case?” and other similar questions.

Once you have grasped the basic concepts of sorting and attempted coding questions, from insertion to merge or quick, you will automatically learn time complexity and its analysis; this also helps in increasing your confidence level.

Sliding Window

Sliding window is one of the most scoring topics because its questions are very similar and can be easily figured out if you have good practice with even a few of them. Sliding window questions are usually of two types: the first type is where the size constraint of the sliding window is given and you have to tell the maximum sum. The other type is one in which the size constraint may vary but the maximum sum is given. If you practice questions from both of these types, scoring sliding window questions becomes really easy.


Learning Hashing questions, especially hash maps, are a must for coding interviews. It is often seen that interviewers ask at least one hashing question. To prepare for hashing, divide it into two parts: theory and practice. In theory, you should learn how hashing works in the backend, what linear probing, coordinated probing, collision handling, and so on are. Once you have grasped the theory part, your second focus should be on the question. You can search for hashing questions on leetcode and solve at least 10 to 12 questions for good practice.

Binary Search Algorithm

Binary search questions are generally on the tougher side of coding interviews. However, there is no need to be afraid of such questions because the important thing is to identify them. You can do this by remembering a few clues. For example, if interviewers ask for minimizing or maximizing, it is based on a binary search. To get a good grasp of such questions, you must practice the binary search algorithm thoroughly.


Recursion is arguably the most important algorithm you should prepare for coding interviews. Questions based on recursion are not asked directly, but if you have practiced recursion properly, you can attempt many related questions such as those involving trees, graphs, dynamic programming, and also linear string questions. So once you have mastered recursion, multiple topics can be easily covered with it. The only catch with recursion questions is that you have to be intuitive to identify them. For example, if there is a question related to finding the sum of numbers, just try it with a base case to confirm whether recursion can be used or not. Again, thorough practice is needed to identify and attempt recursion. Once you have good knowledge of recursion, you can attempt other related questions as explained above.

Reversing a Linked list

Reversing a linked list has varying questions and various approaches. Whenever you are learning to reverse a linked list, practice it with the multiple methods that are available on leetcode. Reversing linked list questions help you learn many basic concepts such as traversing, maintaining previous pointers, etc. Learning how to reverse linked lists is considered very important for mastering linked lists.

Tree Traversal

As mentioned above, trees are closely related to recursion; this is why learning recursion helps a lot if you are preparing for trees. There are usually two parts to trees: one is a binary tree, and the other is a binary search tree. Tree traversal has many concepts, such as inorder, preorder, and postorder, which are important to master and help a lot with tougher questions. Many companies, such as Amazon, focus specifically on tree traversal questions. Practicing 10–20 questions about trees can give you the required knowledge about the concept.

Graph Algorithms

Graph algorithms are harder than the other topics discussed above. There are usually 2 parts to graphs. The first is depth-first search, or DFS. If you have practiced recursion properly and know how to form graphs using any method of your choice, DFS can be done very easily. The second part is breadth-first search, or BFS, which uses queues for traversal. BFS is a relatively advanced topic, which is why you need to properly study this algorithm before attempting its questions. BFS is usually used to derive the minimum path in an unweighted graph. For a weighted graph, we use Dijkstra’s algorithm, which is a derivative of BFS.

Dynamic Programming

Dynamic programming, or DP, is actually considered the villain of DSA, as it is considered a very advanced concept. What really helps with DP is recursion; the more you practice recursion, the more your fear of DP will diminish. Basically, DP is an optimization over plain recursion. In a DP question, first you write the brute-force recursion, and then you just need to memoize it. A pro tip here is to not write the tabular recursion directly, as it gets very complicated. If you have to attempt a DP question in a coding interview, start by writing a brute-force recursion and then memoizing it by capturing the states.

Priority Queue

Lastly, we have a priority queue. It has little relevance in comparison to the preceding topics, but priority queue questions in coding interviews are typically very exclusive, and it is also very important in coding grounds. There are two parts to focus on in the priority queue, the first of which is theory. For the theory part, you must study concepts such as heap building in the back-end, heap sort, heapify, and others. The second part is using the Standard Template Library, or STL, of the priority queue. You can practice such questions separately on LeetCode. Practicing roughly 10–12 questions will be enough for priority queues, and priority queue questions are usually of a similar pattern. However, make sure that you have studied and learned the theory part thoroughly before practicing the questions.

For more such informative articles, stay tuned!

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