Count the steps at each line of code, and write them out into their time complexity...

 

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Count the "steps" at each line of code, and write them out into their time complexity (t(n)), and estimate the Big O based on the time complexity. Code Snippet #1: input n = len (input) converted = [] for i in range(n): [2,1,7,0,4,6,3] t(n) = converted.append(input[i] * 2) input[i] = 0 for k in range(n): converted [k] = converted[k] + 1 #You can type comments over here! #You can even press enter to go down a line. O( ) Count the "steps" at each line of code, and write them out into their time complexity (t(n)), and estimate the Big O based on the time complexity. Code Snippet #1: input n = len (input) converted = [] for i in range(n): [2,1,7,0,4,6,3] t(n) = converted.append(input[i] * 2) input[i] = 0 for k in range(n): converted [k] = converted[k] + 1 #You can type comments over here! #You can even press enter to go down a line. O( )