Top 7 competitive programming algorithms every coder must know!

TechGig
3 min readFeb 16, 2022

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Programming is a difficult role, and once you enter it, you will face new challenges and may be required to solve problems that no one has solved before or whose solution does not exist anywhere.

Programming is a difficult role, and once you enter it, you will face new challenges and may be required to solve problems that no one has solved before or whose solution does not exist anywhere. At that point, you are expected to use your problem-solving and logical abilities to come up with a solution in the shortest amount of time possible.

Here comes competitive programming, a mental sport that requires you to code a given problem within given constraints. So, we have curated a list of top competitive programming algorithms for 2022.

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1. Search Algorithms
There are two types of search approaches under search algorithms:

  • Linear Search Methodology: A linear search is a straightforward method. The linear search has a time complexity of O. (n). Binary Search is another method for accomplishing the same task.
  • Approach to Binary Search: Binary Search is a searching algorithm that divides the search interval in half repeatedly in a sorted array. The idea behind binary search is to use the array’s sorted information to reduce the time complexity to O. (log n).

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2. Exponentiation by Squaring
Exponentiation by squaring, also known as binary exponentiation, is a general method for computing large positive integer powers of a number in O(1) time (log2N). Not only that but the method is also used to compute polynomial powers and square matrices.

3. String Parsing and Matching
One of the most important problems in computer science is pattern matching/searching. There has been a lot of research on the subject, but we’ll focus on only two requirements for any programmer.

4. Algorithms for Primality Testing
There are deterministic and probabilistic methods for determining whether or not a given number is prime. Here are examples of both deterministic and probabilistic (nondeterministic) approaches.

5. Algorithms for Sorting
Sorting is the most thoroughly studied concept in the field of computer science. The basic idea is to arrange the items on a list in a specific order. Though every major programming language has built-in sorting libraries, knowing how they work comes in handy. Depending on the situation, sorting methods include Merge Sort, Quick Sort, Bucket Sort, Heap Sort, and Counting Sort.

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6. Dynamic Programming
Dynamic programming (DP) is a technique for breaking down a complex problem into simpler subproblems. Programmers solve the subproblems, remember their results, and use them to solve the complex problem quickly.

7. Hashing
Hash lookup is currently the most widely used technique for locating relevant data based on a key or ID. Previously, programmers relied on sorting and binary search to find indexes, but now they use hashing. The data structure is known as a Hash-Map, Hash-Table, or Dictionary, and it efficiently maps keys to values. Keys can be used to perform value lookups. The idea is to use a suitable hash function to perform the key -> value mapping. The structure influences the selection of a good hash function.

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