what is amortized complexity

Amortized complexity is a way of analyzing the average time complexity of an algorithm over a series of operations, rather than just the worst-case time complexity of a single operation. It considers the total cost of a sequence of operations and divides it by the number of operations, resulting in an average cost per operation. This approach is useful in cases where some operations may be more expensive than others, but the overall cost of the sequence of operations is still reasonable. For example, when using a dynamic array, the cost of resizing the array can be high, but if the resizing occurs infrequently, the amortized cost of each operation is still low. Amortized complexity is denoted using the big-O notation, just like worst-case complexity.