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Assume you have a 2D matrix. Values are sorted in ascending order from left to write and top to bottom, e.g., 1 7 16 21 34 4 9 20 25 41 6 16 31 33 44 11 19 49 50 61 I'm curious if my value x is in this matrix. I could take a brute force approach, considering all cells via the following code: def find in matrix(m, num_rows, num cols, x): for į in range(num_rows): for j in range(num cols): if m[i]i]==x: return True return False What would be the big O estimate of the run-time for this brute force approach? How could I take a divide-and-conquer approach? Briefly describe (in words) how you could use what is known about the structure of the 2D matrix to divide and conquer.

Assume you have a 2D matrix. Values are sorted in ascending order from left to write and top to bottom, e.g., 1 7 16 21 34 4 9 20 25 41 6 16 31 33 44 11 19 49 50 61 I'm curious if my value x is in this matrix. I could take a brute force approach, considering all cells via the following code: def find in matrix(m, num_rows, num cols, x): for į in range(num_rows): for j in range(num cols): if m[i]i]==x: return True return False What would be the big O estimate of the run-time for this brute force approach? How could I take a divide-and-conquer approach? Briefly describe (in words) how you could use what is known about the structure of the 2D matrix to divide and conquer.

Database System Concepts
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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Please use python if applicable and comment on code, thank you

Assume you have a 2D matrix. Values are sorted in ascending order from left to write and top to bottom, e.g., 1 7 16 21 34 4 9 20 25 41 16 31 33 44 11 19 49 50 61 I'm curious if my value x is in this matrix. I could take a brute force approach, considering all cells via the following code: def find in matrix(m, num rows, num cols, x): for į in range(num rows): for j in range(num cols): if m[i]i)==x: return True return False What would be the big O estimate of the run-time for this brute force approach? How could I take a divide-and-conquer approach? Briefly describe (in words) how you could use what is known about the structure of the 2D matrix to divide and conquer.
Transcribed Image Text:Assume you have a 2D matrix. Values are sorted in ascending order from left to write and top to bottom, e.g., 1 7 16 21 34 4 9 20 25 41 16 31 33 44 11 19 49 50 61 I'm curious if my value x is in this matrix. I could take a brute force approach, considering all cells via the following code: def find in matrix(m, num rows, num cols, x): for į in range(num rows): for j in range(num cols): if m[i]i)==x: return True return False What would be the big O estimate of the run-time for this brute force approach? How could I take a divide-and-conquer approach? Briefly describe (in words) how you could use what is known about the structure of the 2D matrix to divide and conquer.
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