Recursive function that takes the sum of odd integers - c++

The program runs but it also spews out some other stuff and I am not too sure why. The very first output is correct but from there I am not sure what happens. Here is my code:
#include <iostream>
using namespace std;
const int MAX = 10;
int sum(int arrayNum[], int n)
{
int total = 0;
if (n <= 0)
return 0;
else
for(int i = 0; i < MAX; i ++)
{
if(arrayNum[i] % 2 != 0)
total += arrayNum[i];
}
cout << "Sum of odd integers in the array: " << total << endl;
return arrayNum[0] + sum(arrayNum+1,n-1);
}
int main()
{
int x[MAX] = {13,14,8,7,45,89,22,18,6,10};
sum(x,MAX);
system("pause");
return 0;
}

The term recursion means (in the simplest variation) solving a problem by reducing it to a simpler version of the same problem until becomes trivial. In your example...
To compute the num of the odd values in an array of n elements we have these cases:
the array is empty: the result is trivially 0
the first element is even: the result will be the sum of odd elements of the rest of the array
the first element is odd: the result will be this element added to the sum of odd elements of the rest of the array
In this problem the trivial case is computing the result for an empty array and the simpler version of the problem is working on a smaller array. It is important to understand that the simpler version must be "closer" to a trivial case for recursion to work.
Once the algorithm is clear translation to code is simple:
// Returns the sums of all odd numbers in
// the sequence of n elements pointed by p
int oddSum(int *p, int n) {
if (n == 0) {
// case 1
return 0;
} else if (p[0] % 2 == 0) {
// case 2
return oddSum(p + 1, n - 1);
} else {
// case 3
return p[0] + oddSum(p + 1, n - 1);
}
}
Recursion is a powerful tool to know and you should try to understand this example until it's 100% clear how it works. Try starting rewriting it from scratch (I'm not saying you should memorize it, just try rewriting it once you read and you think you understood the solution) and then try to solve small variations of this problem.
No amount of reading can compensate for writing code.

You are passing updated n to recursive function as argument but not using it inside.
change MAX to n in this statement
for(int i = 0; i < n; i ++)

so this doesnt really answer your question but it should help.
So, your code is not really recursive. If we run through your function
int total = 0; //Start a tally, good.
if (n <= 0)
return 0; //Check that we are not violating the array, good.
else
for(int i = 0; i < MAX; i ++)
{
if(arrayNum[i] % 2 != 0) //THIS PART IS WIERD
total += arrayNum[i];
}
And the reason it is wierd is because you are solving the problem right there. That for loop will run through the list and add all the odd numbers up anyway.
What you are doing by recursing could be to do this:
What is the sum of odd numbers in:
13,14,8,7,45,89,22,18,6,10
+
14,8,7,45,89,22,18,6
+
8,7,45,89,22,18
+
7,45,89,22 ... etc
And if so then you only need to change:
for(int i = 0; i < MAX; i ++)
to
for(int i = 0; i < n; i ++)
But otherwise you really need to rethink your approach to this problem.

It's not recursion if you use a loop.
It's also generally a good idea to separate computation and output.
int sum(int arrayNum[], int n)
{
if (n <= 0) // Base case: the sum of an empty array is 0.
return 0;
// Recursive case: If the first number is odd, add it to the sum of the rest of the array.
// Otherwise just return the sum of the rest of the array.
if(arrayNum[0] % 2 != 0)
return arrayNum[0] + sum(arrayNum + 1, n - 1);
else
return sum(arrayNum + 1, n - 1);
}
int main()
{
int x[MAX] = {13,14,8,7,45,89,22,18,6,10};
cout << sum(x,MAX);
}

Related

Minimum Cost to reduce the size of array to 1

Given an array of N numbers (not necessarily sorted). We can merge any two numbers into one and the cost of merging the two numbers is equal to the sum of the two values. The task is to find the total minimum cost of merging all the numbers.
Example:
Let the array A = [1,2,3,4]
Then, we can remove 1 and 2, add both of them and keep the sum back in array. Cost of this step would be (1+2) = 3.
Now, A = [3,3,4], Cost = 3
In second step, we can 3 and 3, add both of them and keep the sum back in array. Cost of this step would be (3+3) = 6.
Now, A = [4,6], Cost = 6
In third step, we can remove both elements from the array and keep the sum back in array again. Cost of this step would be (4+6) = 6.
Now, A = [10], Cost = 10
So, total cost turns out to be 19 (10+6+3).
We will have to pick the 2 smallest elements to minimize our total cost. A simple way to do this is using a min heap structure. We will be able to get the minimum element in O(1) and insertion will be O(log n).
The time complexity of this approach is O(n log n).
But I tried another approach, and wasn't able to find the cases where it fails. The basic idea was that the sum of two smallest elements that we will choose at any time will always be greater than the sum of the pair of elements chosen before. So the "temp" array will always be sorted, and we will be able to access the minimum elements in O(1).
As I am sorting the input array and then simply traversing the array, the complexity of my approach is O(n log n).
int minCost(vector<int>& arr) {
sort(arr.begin(), arr.end());
// temp array will contain the sum of all the pairs of minimum elements
vector<int> temp;
// index for arr
int i = 0;
// index for temp
int j = 0;
int cost = 0;
// while we have more than 1 element combined in both the input and temp array
while(arr.size() - i + temp.size() - j > 1) {
int num1, num2;
// selecting num1 (minimum element)
if(i < arr.size() && j < temp.size()) {
if(arr[i] <= temp[j])
num1 = arr[i++];
else
num1 = temp[j++];
}
else if(i < arr.size())
num1 = arr[i++];
else if(j < temp.size())
num1 = temp[j++];
// selecting num2 (second minimum element)
if(i < arr.size() && j < temp.size()) {
if(arr[i] <= temp[j])
num2 = arr[i++];
else
num2 = temp[j++];
}
else if(i < arr.size())
num2 = arr[i++];
else if(j < temp.size())
num2 = temp[j++];
// appending the sum of the minimum elements in the temp array
int sum = num1 + num2;
temp.push_back(sum);
cost += sum;
}
return cost;
}
Is this approach correct? If not, please let me know what I am missing, and the test cases in which this algorithm fails.
SPOJ Link for the same problem
The logic seems very solid to me... all the computed sums will never be decreasing and therefore you only need to add up either oldest two computed sums, next two elements or oldest sum and next element.
I would just simplify the code:
#include <vector>
#include <algorithm>
#include <stdio.h>
int hsum(std::vector<int> arr) {
int ni = arr.size(), nj = 0, i = 0, j = 0, res = 0;
std::sort(arr.begin(), arr.end());
std::vector<int> temp;
auto get = [&]()->int {
if (j == nj || (i < ni && arr[i] < temp[j])) return arr[i++];
return temp[j++];
};
while ((ni-i)+(nj-j)>1) {
int a = get(), b = get();
res += a+b;
temp.push_back(a + b); nj++;
}
return res;
}
int main() {
fprintf(stderr, "%i\n", hsum(std::vector<int>{1,4,2,3}));
return 0;
}
Very nice idea!
Another improvement is noting that the cumulative length of the two arrays being processed (the original one and the temporary one holding the sums) will decrease at every step.
Since the first step will use two input elements, the fact that the temporary array grows one element at each step will still not be enough for a "walking queue" allocated in the array itself to reach the reading pointer.
This means that there is no need of a temporary array and the space for the sums can be found in the array itself...
int hsum(std::vector<int> arr) {
int ni = arr.size(), nj = 0, i = 0, j = 0, res = 0;
std::sort(arr.begin(), arr.end());
auto get = [&]()->int {
if (j == nj || (i < ni && arr[i] < arr[j])) return arr[i++];
return arr[j++];
};
while ((ni-i)+(nj-j)>1) {
int a = get(), b = get();
res += a+b;
arr[nj++] = a + b;
}
return res;
}
About the error on SPOJ... I tried briefly to search for the problem but I didn't succeed. I tried however generating random arrays of random lengths and checking this solution with what finds a "brute-force" one implemented directly from the specs and I'm reasonably confident that the algorithm is correct.
I know at least one programming arena (Topcoder) where sometimes the problems are carefully crafted so that the computation gives correct results if using unsigned but not if using int (or if using unsigned long long but not if using long long) because of integer overflow.
I don't know if SPOJ also does this kind of nonsense(1)... may be that is the reason some hidden test case fails...
EDIT
Checking with SPOJ the algorithm passes if using long long values... this is the entry I used:
#include <stdio.h>
#include <algorithm>
#include <vector>
int main(int argc, const char *argv[]) {
int n;
scanf("%i", &n);
for (int testcase=0; testcase<n; testcase++) {
int sz; scanf("%i", &sz);
std::vector<long long> arr(sz);
for (int i=0; i<sz; i++) scanf("%lli", &arr[i]);
int ni = arr.size(), nj = 0, i = 0, j = 0;
long long res = 0;
std::sort(arr.begin(), arr.end());
auto get = [&]() -> long long {
if (j == nj || (i < ni && arr[i] < arr[j])) return arr[i++];
return arr[j++];
};
while ((ni-i)+(nj-j)>1) {
long long a = get(), b = get();
res += a+b;
arr[nj++] = a + b;
}
printf("%lli\n", res);
}
return 0;
}
PS: This very kind of computation is also what is needed to build an Huffman tree for entropy coding given the symbols frequency table and thus it's not a mere random exercise but it has practical applications.
(1) I'm saying "nonsense" because in Topcoder they never give problems that require 65 bits; thus it's not a genuine care about overflows, but just setting traps for novices.
Another that I think is a bad practice I saw on TC is that some problems are carefully designed so that the correct algorithm if using C++ will barely fit in the timeout limit: just use another language (and get e.g. a 2× slowdown) and you cannot solve the problem.
First of all, think simple!
When using a priority queue, the problem is easy!
In the first test case :
1 6 3 20
// after pushing to Q
1 3 6 20
// and sum two top items and pop and push!
(1 + 3) 6 20 cost = 4
(4 + 6) 20 cost = 10 + 4
(10 + 20) cost = 30 + 14
30 cost = 44
#include<iostream>
#include<queue>
using namespace std;
int main()
{
int t;
cin >> t;
while (t--) {
int n;
cin >> n;
priority_queue<long long int, vector<long long int>, greater<long long int>> q;
for (int i = 0; i < n; ++i) {
int k;
cin >> k;
q.push(k);
}
long long int sum = 0;
while (q.size() > 1) {
long long int a = q.top();
q.pop();
long long int b = q.top();
q.pop();
q.push(a + b);
sum += a + b;
}
cout << sum << "\n";
}
}
Basically we need to sort the list in desc order and then find its cost like this.
A.sort(reverse=True)
cost = 0
for i in range(len(A)):
cost += A[i] * (i+1)
return cost

Improving optimization of nested loop

I'm making a simple program to calculate the number of pairs in an array that are divisible by 3 array length and values are user determined.
Now my code is perfectly fine. However, I just want to check if there is a faster way to calculate it which results in less compiling time?
As the length of the array is 10^4 or less compiler takes less than 100ms. However, as it gets more to 10^5 it spikes up to 1000ms so why is this? and how to improve speed?
#include <iostream>
using namespace std;
int main()
{
int N, i, b;
b = 0;
cin >> N;
unsigned int j = 0;
std::vector<unsigned int> a(N);
for (j = 0; j < N; j++) {
cin >> a[j];
if (j == 0) {
}
else {
for (i = j - 1; i >= 0; i = i - 1) {
if ((a[j] + a[i]) % 3 == 0) {
b++;
}
}
}
}
cout << b;
return 0;
}
Your algorithm has O(N^2) complexity. There is a faster way.
(a[i] + a[j]) % 3 == ((a[i] % 3) + (a[j] % 3)) % 3
Thus, you need not know the exact numbers, you need to know their remainders of division by three only. Zero remainder of the sum can be received with two numbers with zero remainders (0 + 0) and with two numbers with remainders 1 and 2 (1 + 2).
The result will be equal to r[1]*r[2] + r[0]*(r[0]-1)/2 where r[i] is the quantity of numbers with remainder equal to i.
int r[3] = {};
for (int i : a) {
r[i % 3]++;
}
std::cout << r[1]*r[2] + (r[0]*(r[0]-1)) / 2;
The complexity of this algorithm is O(N).
I've encountered this problem before, and while I don't find my particular solution, you could improve running times by hashing.
The code would look something like this:
// A C++ program to check if arr[0..n-1] can be divided
// in pairs such that every pair is divisible by k.
#include <bits/stdc++.h>
using namespace std;
// Returns true if arr[0..n-1] can be divided into pairs
// with sum divisible by k.
bool canPairs(int arr[], int n, int k)
{
// An odd length array cannot be divided into pairs
if (n & 1)
return false;
// Create a frequency array to count occurrences
// of all remainders when divided by k.
map<int, int> freq;
// Count occurrences of all remainders
for (int i = 0; i < n; i++)
freq[arr[i] % k]++;
// Traverse input array and use freq[] to decide
// if given array can be divided in pairs
for (int i = 0; i < n; i++)
{
// Remainder of current element
int rem = arr[i] % k;
// If remainder with current element divides
// k into two halves.
if (2*rem == k)
{
// Then there must be even occurrences of
// such remainder
if (freq[rem] % 2 != 0)
return false;
}
// If remainder is 0, then there must be two
// elements with 0 remainder
else if (rem == 0)
{
if (freq[rem] & 1)
return false;
}
// Else number of occurrences of remainder
// must be equal to number of occurrences of
// k - remainder
else if (freq[rem] != freq[k - rem])
return false;
}
return true;
}
/* Driver program to test above function */
int main()
{
int arr[] = {92, 75, 65, 48, 45, 35};
int k = 10;
int n = sizeof(arr)/sizeof(arr[0]);
canPairs(arr, n, k)? cout << "True": cout << "False";
return 0;
}
That works for a k (in your case 3)
But then again, this is not my code, but the code you can find in the following link. with a proper explanation. I didn't just paste the link since it's bad practice I think.

basic nestled loop calculate prime numbers between 1 - 239, inclusive

I am working on a program in which I must print out the number of primes, including 1 and 239, from 1 - 239 ( I know one and or two may not be prime numbers, but we will consider them as such for this program) It must be a pretty simple program because we have only gone over some basics. So far my code is as such, which seems like decent logical flow to me, but doesnt produce output.
#include <iostream>
using namespace std;
int main()
{
int x;
int n = 1;
int y = 1;
int i = 0;
while (n<=239)
{x = n % y;
if (x = 0)
i++;
if (y < n)
y++;
n++;
while (i == 2)
cout << n;
}
return 0;
}
The way I want this to work is to take n, as long as n is 239 or less, and preform modulus division with every number from 1 leading up to n. Every time a number y goes evenly into n, a counter will be increased by 1. if the counter is equal to 2, then the number is prime and we print it to the screen. Any help would be so greatly appreciated. Thanks
std::cout << std::to_string(2) << std::endl;
for (unsigned int i = 3; i<240; i += 2) {
unsigned int j = 3;
int sq = sqrt(i);
for (; j <= sq; j += 2) if (!(i%j)) break;
if (j>sq) std::cout << std::to_string(i) << std::endl;
}
first of all, the prime definition: A prime number (or a prime) is a natural number greater than 1 that has no positive divisors other than 1 and itself.
so you can skip all the even numbers (and hence ... i+=2).
Moreover no point to try to divide for a number greater than sqrt(i), because then it will have a divisor less than sqrt(i) and the code finds that and move to the next number.
Considering only odd numbers, means that we can skip even numbers as divisors (hence ... j+=2).
In your code there are clearly beginner errors, like (x = 0) instead of x==0. but also the logic doesn't convince. I agree with #NathanOliver, you need to learn to use a debugger to find all the errors. For the rest, good luck with the studies.
lets start with common errors:
first you want to take input from user using cin
cin>>n; // write it before starting your while loop
then,
if (x = 0)
should be:
if (x == 0)
change your second while loop to:
while (i == 2){
cout << n;
i++;
}

Need a function to continue decreasing a value once it runs out of valid values

So Im writing a function that is supposed to count up all the first N even numbers in an array where the user picks N. Which is fine, however if there are fewer than N even numbers in the array, then the function should just add them all which is the part I am having difficulty with.
function call:
cout << "The sum of the first " << userSum << " even numbers is: " <<
SumEvens(list, SIZE, userSum) << endl;
function definition:
int SumEvens(int arr[], const int size, int evensAdd)
{
int sum = 0;
for (int i = 0; i < size; i++){
if (arr[i] % 2 == 0 && arr[i] != 0){//if the number is even and not 0 then that number is added to the sum
evensAdd--;
sum += arr[i];
}
if(evensAdd == 0)//once evensAdd = 0(N as previously mentioned) then the function will return the sum
return sum;
}
}
So for example if I have an array: {1,2,3,4,5}
and ask for it to calculate the sum of the first 2 even numbers it would output 6
however if i ask for it to calculate say the first 3 or 4 or 5 even numbers it will output that the sum is 6
why would it subtract one?
If you finish the for loop before evensAdd reaches 0, you never reach the return sum statement and therefore not set the return value of the function. The value returned is then just a random number read from the stack. This is just a technical stuff, the correct approach should look like this:
int SumEvens(int arr[], const int size, int evensAdd)
{
int sum = 0;
for (int i = 0; i < size; i++)
{
if (arr[i] % 2 == 0 && arr[i] != 0)
{
evensAdd--;
sum += arr[i];
}
if (evensAdd == 0)
{
break;
}
}
return sum;
}
Using break will immediately jump to the end of the for loop and the return value will be set if in all cases.
EDIT: Check your compiler warnings, I'm pretty sure that every compiler gives a "Control may reach end of non-void function".
int SumEvens(int arr[], const int size, int evensAdd)
{
int sum = 0;
for (int i = 0; i < size && evensAdd > 0; i++)
{
if (arr[i] % 2 == 0 && arr[i] != 0)
{
evensAdd--;
sum += arr[i];
}
}
return sum;
}
This will work but like #πάντα ῥεῖ said using vectors would be a better idea.
You can just stop the loop with set condition, which is in this case better style than breaking.
Working example!

My Sieve of Eratosthenes takes too long

I have implemented Sieve of Eratosthenes to solve the SPOJ problem PRIME1. Though the output is fine, my submission exceeds the time limit. How can I reduce the run time?
int main()
{
vector<int> prime_list;
prime_list.push_back(2);
vector<int>::iterator c;
bool flag=true;
unsigned int m,n;
for(int i=3; i<=32000;i+=2)
{
flag=true;
float s = sqrt(static_cast<float>(i));
for(c=prime_list.begin();c<=prime_list.end();c++)
{
if(*c>s)
break;
if(i%(*c)==0)
{
flag=false;
break;
}
}
if(flag==true)
{
prime_list.push_back(i);
}
}
int t;
cin>>t;
for (int times = 0; times < t; times++)
{
cin>> m >> n;
if (t) cout << endl;
if (m < 2)
m=2;
unsigned int j;
vector<unsigned int> req_list;
for(j=m;j<=n;j++)
{
req_list.push_back(j);
}
vector<unsigned int>::iterator k;
flag=true;
int p=0;
for(j=m;j<=n;j++)
{
flag=true;
float s = sqrt(static_cast<float>(j));
for(c=prime_list.begin();c<=prime_list.end();c++)
{
if((*c)!=j)
{
if((*c)>s)
break;
if(j%(*c)==0)
{
flag=false;
break;
}
}
}
if(flag==false)
{
req_list.erase (req_list.begin()+p);
p--;
}
p++;
}
for(k=req_list.begin();k<req_list.end();k++)
{
cout<<*k;
cout<<endl;
}
}
}
Your code is slow because you did not implement the Sieve of Eratosthenes algorithm. The algorithm works that way:
1) Create an array with size n-1, representing the numbers 2 to n, filling it with boolean values true (true means that the number is prime; do not forget we start counting from number 2 i.e. array[0] is the number 2)
2) Initialize array[0] = false.
3) Current_number = 2;
3) Iterate through the array by increasing the index by Current_number.
4) Search for the first number (except index 0) with true value.
5) Current_number = index + 2;
6) Continue steps 3-5 until search is finished.
This algorithm takes O(nloglogn) time.
What you do actually takes alot more time (O(n^2)).
Btw in the second step (where you search for prime numbers between n and m) you do not have to check if those numbers are prime again, ideally you will have calculated them in the first phase of the algorithm.
As I see in the site you linked the main problem is that you can't actually create an array with size n-1, because the maximum number n is 10^9, causing memory problems if you do it with this naive way. This problem is yours :)
I'd throw out what you have and start over with a really simple implementation of a sieve, and only add more complexity if really needed. Here's a possible starting point:
#include <vector>
#include <iostream>
int main() {
int number = 32000;
std::vector<bool> sieve(number,false);
sieve[0] = true; // Not used for now,
sieve[1] = true; // but you'll probably need these later.
for(int i = 2; i<number; i++) {
if(!sieve[i]) {
std::cout << "\t" << i;
for (int temp = 2*i; temp<number; temp += i)
sieve[temp] = true;
}
}
return 0;
}
For the given range (up to 32000), this runs in well under a second (with output directed to a file -- to the screen it'll generally be slower). It's up to you from there though...
I am not really sure that you have implemented the sieve of Erasthotenes. Anyway a couple of things that could speed up to some extent your algorithm would be: Avoid multiple rellocations of the vector contents by preallocating space (lookup std::vector<>::reserve). The operation sqrt is expensive, and you can probably avoid it altogether by modifying the tests (stop when the x*x > y instead of checking x < sqrt(y).
Then again, you will get a much better improvement by revising the actual algorithm. From a cursory look it seems as if you are iterating over all candidates and for each one of them, trying to divide with all the known primes that could be factors. The sieve of Erasthotenes takes a single prime and discards all multiples of that prime in a single pass.
Note that the sieve does not perform any operation to test whether a number is prime, if it was not discarded before then it is a prime. Each not prime number is visited only once for each unique factor. Your algorithm on the other hand is processing every number many times (against the existing primes)
I think one way to slightly speed up your sieve is the prevention of using the mod operator in this line.
if(i%(*c)==0)
Instead of the (relatively) expensive mod operation, maybe if you iterated forward in your sieve with addition.
Honestly, I don't know if this is correct. Your code is difficult to read without comments and with single letter variable names.
The way I understand the problem is that you have to generate all primes in a range [m,n].
A way to do this without having to compute all primes from [0,n], because this is most likely what's slowing you down, is to first generate all the primes in the range [0,sqrt(n)].
Then use the result to sieve in the range [m,n]. To generate the initial list of primes, implement a basic version of the sieve of Eratosthenes (Pretty much just a naive implementation from the pseudo code in the Wikipedia article will do the trick).
This should enable you to solve the problem in very little time.
Here's a simple sample implementation of the sieve of Eratosthenes:
std::vector<unsigned> sieve( unsigned n ) {
std::vector<bool> v( limit, true ); //Will be used for testing numbers
std::vector<unsigned> p; //Will hold the prime numbers
for( unsigned i = 2; i < n; ++i ) {
if( v[i] ) { //Found a prime number
p.push_back(i); //Stuff it into our list
for( unsigned j = i + i; j < n; j += i ) {
v[i] = false; //Isn't a prime/Is composite
}
}
}
return p;
}
It returns a vector containing only the primes from 0 to n. Then you can use this to implement the method I mentioned. Now, I won't provide the implementation for you, but, you basically have to do the same thing as in the sieve of Eratosthenes, but instead of using all integers [2,n], you just use the result you found. Not sure if this is giving away too much?
Since the SPOJ problem in the original question doesn't specify that it has to be solved with the Sieve of Eratosthenes, here's an alternative solution based on this article. On my six year old laptop it runs in about 15 ms for the worst single test case (n-m=100,000).
#include <set>
#include <iostream>
using namespace std;
int gcd(int a, int b) {
while (true) {
a = a % b;
if(a == 0)
return b;
b = b % a;
if(b == 0)
return a;
}
}
/**
* Here is Rowland's formula. We define a(1) = 7, and for n >= 2 we set
*
* a(n) = a(n-1) + gcd(n,a(n-1)).
*
* Here "gcd" means the greatest common divisor. So, for example, we find
* a(2) = a(1) + gcd(2,7) = 8. The prime generator is then a(n) - a(n-1),
* the so-called first differences of the original sequence.
*/
void find_primes(int start, int end, set<int>* primes) {
int an; // a(n)
int anm1 = 7; // a(n-1)
int diff;
for (int n = start; n < end; n++) {
an = anm1 + gcd(n, anm1);
diff = an - anm1;
if (diff > 1)
primes->insert(diff);
anm1 = an;
}
}
int main() {
const int end = 100000;
const int start = 2;
set<int> primes;
find_primes(start, end, &primes);
ticks = GetTickCount() - ticks;
cout << "Found " << primes.size() << " primes:" << endl;
set<int>::iterator iter = primes.begin();
for (; iter != primes.end(); ++iter)
cout << *iter << endl;
}
Profile your code, find hotspots, eliminate them. Windows, Linux profiler links.