What is algorithm? Characteristics of an Algorithm, Different Types of Algorithms

 What is algorithm?

An algorithm is a sequence of steps designed to complete a specific task. It processes one or more inputs systematically and generates one or more outputs. Algorithms are fundamental in computing and play a key role in programming. They help solve computational problems, such as performing calculations or retrieving data from databases.

Beyond programming, algorithms can also be applied manually by individuals or executed automatically by machines. For instance, long division can be done by hand or solved using a calculator. Users do not need to understand how an algorithm functions to benefit from it. Many companies keep their algorithms confidential, preventing users from accessing their internal workings.

Characteristics of an Algorithm:

1. Well-Defined Steps – Each step must be clear and unambiguous.
2. Input – It takes one or more inputs to process.
3. Output – Produces one or more outputs after execution.
4. Finiteness – Must terminate after a finite number of steps.
5. Effectiveness – Each step must be simple enough to be executed in a limited amount of time.

Examples of Algorithms:

• A recipe for cooking a dish (step-by-step procedure).
• A long division method in mathematics.
• A navigation system finding the shortest route.
• A sorting algorithm arranging numbers in ascending order.

Different Types of Algorithms

There are various types of algorithms, each designed for different problem-solving approaches. Some of the key types include:

1. Brute Force Algorithm:
   This is the most straightforward method for solving a problem. It systematically checks all possible solutions until the correct one is found.

2. Recursive Algorithm:
   This algorithm follows the principle of recursion, where a problem is divided into smaller subproblems, and the same function is repeatedly called until the base condition is met.

3. Backtracking Algorithm:
   This method explores possible solutions step by step. If a certain approach leads to failure, it backtracks to the previous step and attempts a different path until a solution is found or all possibilities are exhausted.

4. Searching Algorithm:
   These algorithms are used to locate an element or a group of elements within a data structure. The approach may vary depending on the data structure and the search method applied.

5. Sorting Algorithm:
   Sorting algorithms arrange data in a specific order, typically in ascending or descending sequence, as per requirements. These algorithms enhance data organization and retrieval efficiency.

6. Hashing Algorithm:
   Hashing is similar to searching but uses an index with a unique key ID for faster data retrieval. A key is assigned to each data element, enabling efficient access.

7. Divide and Conquer Algorithm:
   This technique involves breaking a problem into smaller subproblems, solving each independently, and then combining their results to derive the final solution. It consists of three steps:

   • Divide: Split the problem into smaller parts.
   • Solve: Address each subproblem separately.
   • Combine: Merge the results to get the final outcome.

8. Greedy Algorithm:
   This approach builds a solution piece by piece, selecting the option that provides the most immediate benefit at each step. It prioritizes locally optimal choices to construct a globally optimal solution.

9. Dynamic Programming Algorithm:
   This technique avoids redundant computations by storing previously solved subproblems. It divides the problem into smaller, overlapping subproblems and reuses the results to optimize efficiency.

10. Randomized Algorithm:
    This algorithm incorporates random numbers to determine its next step, often leading to faster or more efficient solutions in specific cases. The randomness influences the outcome dynamically.

Example:

Algorithm for Finding the Maximum Number in a List

This algorithm finds the largest number in a given list of numbers.

Algorithm (Step-by-Step):

1. Start
2. Define an array (list) of numbers
3. Assume the first element is the maximum (store it in a variable)
4. Loop through the list:
5.   Compare each element with the current maximum
6.   If an element is greater than the current maximum, update the maximum
7.   After the loop ends, the variable holds the largest number
8. Print the maximum number
9. End

Pseudocode:

BEGIN  

   DEFINE List as an array of numbers  

   SET Max = List[0]  

   FOR each number in List:  

      IF number > Max THEN  

         Max = number  

   END FOR  

   PRINT "Maximum Number is:", Max  

END  

Execution:

Input: [10, 25, 6, 78, 45]

Output: Maximum Number is: 78

Pseudocode for adding two numbers:

BEGIN  

    PRINT "Enter first number: "  

    READ A  

    PRINT "Enter second number: "  

    READ B  

    SUM ← A + B  

    PRINT "The sum is: ", SUM  

END