Profiling of inefficient recursive Fibonacci series function
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I am asked to profile an intentionally inefficient code. Following code will overtime with a huge input:
function f = fibo(n)
if n <= 2
f = 1;
else
f = fibo(n-2) + fibo(n-1);
end
end
I used a persistente variable, to create an array that reflects the recursion calls:
function [f, trace]=fibo_trace(n,v)%with persistent variable 'trc'
persistent trc;
if isempty(trc)
trc=v;
end
if n<=2
trc=[trc n];
f=1;
else
trc=[trc n];
f=fibo_trace(n-2)+fibo_trace(n-1);
end
trace=trc;
end
That works flawlessly when I run the function with followin code:
[f trace] = fibo_trace(6,[])
And this is what the code returns:
f = 8
trace = 6 4 2 3 1 2 5 3 1 2 4 2 3 1 2,
which is OK, since the trace vector shows how inefficient the original code is. Now my problem is, it is an assigment for a MOOC platform and the solution with the persistent variable won't work because the the automated grader will run the function a number of times with random inputs and it will not clear the function. Without the persistent variable I must split the recursive calls in two code lines and I am struggling now to compute the nth fibonacci number:

Can anyone give a clue? The creation of the array works but I honestly don't know how to deal with the two recursive call lines to compute the fibonacci.
Réponse acceptée
Plus de réponses (2)
Rajith
le 17 Déc 2023
function [f, v] = fibo_trace(n,v)
v(end+1) = n;
if n == 1 || n == 2
f = 1;
else
[f1, v] = fibo_trace(n-2,v);
[f2, v] = fibo_trace(n-1,v);
f = f1+f2;
end
end
Divyanshu
le 28 Juil 2024
0 votes
function [f, v] = fibo_trace(n,v)
v(end+1) = n;
if n == 1 || n == 2
f = 1;
else
[f1, v] = fibo_trace(n-2,v);
[f2, v] = fibo_trace(n-1,v);
f = f1+f2;
end
end
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