7 Programming Algorithms Every Programmer Must Learn

7 Programming Algorithms

To solve a specific problem, we have to use a formula or follow a procedure. This formula or procedure that we follow to solve a problem is a programming algorithm. The programming algorithms consist of a sequence of the specified actions. This sequence of actions describes how to do something. We have to make up the programming algorithms with inputs. Precision, uniqueness, input, output and generality are some important characteristics of the algorithms. Here, we will discuss 7 programming algorithms that every programmer must learn.

Sort Algorithms

We have to usually study sorting in Computer Science. The main idea behind this concept is to arrange the things in a list by following a specific order. When you will go to learn a specific programming language, you will find its sorting libraries. If you will know the use of these sorting libraries, you will get lots of benefits. Merge sort, quick sort and counting sort are the most important examples of the sort programming algorithms. Anyhow, dissertation writing service firm says that if you want to use them perfectly, you should learn when and how to use these sorts of algorithms. The most important use of the sorting algorithms is in e-commerce. In e-commerce, you will have to sort them by price and popularity.

Search Algorithms

Search algorithms are also the most important programming algorithms. For example, we can make use of the binary search. By using binary search, we can easily perform the search on the sorted dataset. Here, we should also keep in mind time complexity. If we have a list, it will repeatedly divide this list in half. After narrowing down this list, we can easily reach one item. If you will have to search for a specific song in a list, you can use binary search. After sorting down the list, it can easily provide the required results. The search engines are also using this technique for web crawling. If we want to build bots in artificial intelligence, we can also use search algorithms. To find the shortest path on the map, we can also use it.

Hashing

If we have to find appropriate data by a key or an ID, we can use hashing programming algorithms. It also allows the users to get access to data by using the indexing technique. Hash-Map, Hash-Table or Dictionary are the most important examples of hashing techniques in programming. When we will use keys, we can easily perform the value lookups. If we want to get the best results, we have to use the appropriate hash functions. Anyhow, we should choose the best hash functions based on the scenario. We can use these hashing functions in the routers to store IP addresses. Sometimes, we have to check the existence of a value in the list. If we use the linear search technique to find this value, it is very expensive. That’s why we use this technique to find this value.

Dynamic Programming

Sometimes, we have to solve complex problems. By using programming algorithms, we can easily solve these complex problems by breaking them into sub-problems. They are dynamic programming algorithms. After breaking a complex problem into sub-problems, it gets results of these sub-problems. When it gets the results of these sub-problems, it remembers their results. This is the best way to quickly solve complex problems. No doubt, there are various applications of dynamic programming. The most important example is the Duckworth-Lewis method. Due to the rain during the cricket match, we can use this method to decide the winning team, remaining over and runs etc.

Exponentiation by Squaring

For example, if we want to solve 2^16, we have to iterate 2 for 16 times. After iterating 2 for 16 times, we can get the results. No doubt, it is a time taking task and sometimes, we may make some mistakes. Anyhow, if we want to complete these kinds of problems just within a second, we can use exponentiation by squaring programming algorithms. By using this method, we can easily find the results of the large positive powers of the integers. Along with finding these results, we can also use this technique to compute the powers of polynomials.

7 Programming Algorithms 1

String Matching and Parsing

Pattern matching or pattern searching has become the most important example in computer science. The programmers can use these programming algorithms for various purposes. First, we can use it for string matching. We can easily use this algorithm where we have to match the short pattern in the long string. For this reason, we have to enter Ctrl + F. After that, we have to search keywords in the document. As a result, we can easily perform pattern matching in the document. Secondly, we can also use it for string parsing. By using this technique, we have to validate a string. While validating this string, we have to define a string. The developers are heavily using it in web development.

Primality Testing Algorithms

Sometimes, we have to determine either a number is prime or not. For this reason, we can use deterministic and probabilistic ways. If we have to impose a condition on the numbers, we can use a deterministic way. For example, we can impose a condition to find prime numbers between 200 to 2,000. Here, we have to allocate a certain memory to the algorithms. The most important use of these programming algorithms is in Cryptography. For example, we can easily use it for the encryption and decryption of the data. We can also use them along with Hash functions in the hashing algorithms.

Conclusion

The programming students should learn different programming algorithms. These algorithms are the sets of well-defined instructions that we can use to solve specific problems. In the algorithms, we have to provide some inputs to get the required outputs. For example, if you will have to add two numbers, you can use these algorithms. You just need to take two numbers as inputs. The operators will add these numbers to display the results. Anyhow, the inputs and outputs of the algorithms should be properly defined. Sort algorithms, search algorithms and hashing are the most important algorithms.