Arrays and lists are fundamental data structures in programming. They store collections of elements and support various operations like insertion, deletion, and searching. Understanding these operations is crucial for efficient data manipulation and algorithm design.
Sorting algorithms organize array elements in a specific order, with common methods including Bubble Sort, Selection Sort, and Insertion Sort. These algorithms have different time complexities and are chosen based on the specific problem requirements and data characteristics.
Array and List Operations
Operations on arrays and lists
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Complexities of Sorting Algorithms and Data Structure Operations View original
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Insertion adds elements at beginning, end, or specific position with varying time complexities (O(1) for end, O(n) for beginning/middle)
Deletion removes elements from beginning, end, or specific position requiring array size adjustment or list structure modification
Searching locates elements using linear search (O(n)) or binary search for sorted arrays (O(log n))
Sorting algorithms for arrays
Bubble Sort repeatedly swaps adjacent elements if they're in wrong order, time complexity O(n^2)
Selection Sort finds minimum element and places it at beginning of unsorted portion, time complexity O(n^2)
Insertion Sort builds sorted array one element at a time, time complexity O(n^2)
Comparison of sorting algorithms considers best-case (O(n) for Insertion Sort), average-case, and worst-case scenarios along with space complexity (O(1) for in-place sorts)
Traversal techniques for elements
Sequential access iterates through elements using loops or accessing by index in arrays
Iterator-based access uses iterators in lists providing abstraction and flexibility
Reverse traversal techniques navigate arrays and lists from end to beginning
Problem-solving with array manipulations
Finding maximum/minimum element involves linear search or tracking current max/min while traversing
Reversing order of elements uses in-place reversal algorithm or additional data structures
Removing duplicates employs hash set for efficient removal or in-place techniques for sorted arrays
Merging sorted arrays or lists utilizes two-pointer approach with time complexity O(n+m) and space complexity O(n+m)