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DSA

1. GFG DSA Complete guide​

2. GFG DSA for Beginners​

3. GFG DSA Practice Problems​

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  1. Linear Data Structures:

    • Elements arranged sequentially.
    • Examples: Array, stack, queue, linked list.

  2. Static Data Structures:

    • Fixed memory size.
    • Example: Array.

  3. Dynamic Data Structures:

    • Size not fixed, can be updated during runtime.
    • Examples: Queue, stack.

  4. Non-linear Data Structures:

    • Elements not placed sequentially.
    • Examples: Trees, graphs.

Auxiliary​

refers to the extra space used in the program other than the input data structure.

Asymptotic analysis​

Method for describing the efficiency of an algorithm.

Big O Notation (O):​

It describes the worst-case scenario for the algorithm's time or space complexity in terms of a mathematical function. For example, O(n) represents linear complexity, O(n^2) represents quadratic complexity, and O(log n) represents logarithmic complexity.

Omega Notation (Ω):​

It describes the best-case scenario for the algorithm's time or space complexity. For example, Ω(n) represents linear complexity.

Theta Notation (Θ):​

Theta notation provides a tight bound on an algorithm's growth rate, both upper and lower bounds. If an algorithm has a time complexity of Θ(f(n)), it means the algorithm's performance grows exactly at the rate of the function f(n).

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Array​

ReverseArray​

    public static void reverseArray2(int[] inputArray) {
        int Start = 0;
        int end = inputArray.length - 1;

        while (Start < end) {
            int temp = inputArray[Start];
            inputArray[Start] = inputArray[end];
            inputArray[end] = temp;
            Start++;
        }
        end--;
    }