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Definition: An array is a data structure that stores a collection of elements, each identified by at least one array index or key. It is a contiguous block of memory, where each element is of the same data type and occupies a fixed amount of memory space.

Representation: Arrays can be represented in various programming languages using different syntax. Here’s a general representation:

# Syntax in Python

array_name = [element1, element2, element3, ...]

For example:

# An array of integers in Python

int_array = [1, 2, 3, 4, 5]

# An array of strings in Python
str_array = [“apple”, “banana”, “orange”]


  1. Time Complexity:
    • Access: Accessing an element in an array by index typically takes constant time, O(1), since it involves simple arithmetic to calculate the memory address where the desired element is stored.
    • Search: Searching for a specific element in an unsorted array usually requires linear time, O(n), as each element needs to be checked until the target element is found or the end of the array is reached. If the array is sorted, binary search can be applied, which has a time complexity of O(log n).
    • Insertion and Deletion:
      • At the End: Insertion or deletion at the end of the array typically takes constant time, O(1), as it involves appending or removing an element.
      • At the Beginning or Middle: Insertion or deletion at the beginning or middle of the array requires shifting elements, resulting in a time complexity of O(n), as it may involve moving elements to create space or fill gaps.
    • Sorting: Sorting an array using comparison-based algorithms like quicksort or mergesort generally takes O(n log n) time complexity.
  2. Space Complexity:
    • The space complexity of an array is O(n), where n is the number of elements in the array, as it allocates contiguous memory space for all elements regardless of whether they are currently used or not.
  3. Trade-offs:
    • Arrays provide fast access to elements by index and are efficient in terms of memory usage.
    • However, they have limitations such as fixed size (static arrays) or inefficient insertion and deletion operations due to shifting elements.
    • Dynamic arrays (e.g., ArrayList in Java, vector in C++) mitigate some of these limitations by automatically resizing themselves as needed, but they may incur overhead in terms of memory management and occasional resizing operations.