The count_crossings_and_nestings function has a computational complexity of O(n²), where n is the number of arcs in the input. This complexity arises from the nested loops iterating over pairs of arcs to check for crossings and nestings. As the number of arcs (n) increases: • The runtime of the function will grow quadratically, making it inefficient for large values of n. • The memory requirement of the function grows linearly with the number of arcs since it doesn't store any additional data structures. For large inputs, the function may become impractical due to its quadratic time complexity. To improve efficiency for larger inputs, alternative algorithms or optimizations should be considered.
The count_crossings_and_nestings function has a computational complexity of O(n²), where n is the number of arcs in the input. This complexity arises from the nested loops iterating over pairs of arcs to check for crossings and nestings. As the number of arcs (n) increases: • The runtime of the function will grow quadratically, making it inefficient for large values of n. • The memory requirement of the function grows linearly with the number of arcs since it doesn't store any additional data structures. For large inputs, the function may become impractical due to its quadratic time complexity. To improve efficiency for larger inputs, alternative algorithms or optimizations should be considered.
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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The module timeit (imported above) allows you to compute the time a function call takes. Verify your answer about the time complexity from Exercise I have attached by computing the run time for randomly chosen arc diagrams of suitable sizes and producing an appropriate plot of the average run times against the lengths of the matchings.
Interpret your results.
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