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1. • • The key to success is breaking the project into manageable parts, a strategy known as 'divide and conquer.' By segmenting the work, you can focus on completing each section to the best of your ability, without becoming overwhelmed by the scale of the overall project.
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2. Top results related to divide & conquer strategy

   • Divide and conquer strategy python

     Top Answer

     Answered Apr 26, 2020 · 1 votes

     This is my python version code for the algorithm in its "closest larger right" version. Obviously, as you can see it is recursive. Recursion is really elegant but a bit tricky because few lines of code condense lots of concepts regarding to algorithms design and the own language they are coded. In my opinion 4 relevant moments are happening:

     • 1) Recursive calls. Function is call to itself. During this step the list progresible slice into halves. Once the atomic unit is reached the base algorithm will be executed over them firstly (step 3). if not solution is reached greater list sizes will be involved in the calculation in further recursions.
     • 2) Termination condition. Previous step is not run forever, it allows stop recursion and going to the next step (base algorithm). Now the code has len(arr) > 1: that means that the atomic unit will be pairs of numbers (or one of three in case of odd list). You can increase the number so that the recursive function will stay less time slicing the list and summarizing the results, but the counterpart is that in a parallelized environment "workers" will have to digest a bigger list.
     • 3) Base algorithm. It makes the essential calculation. Whatever the size of the list, it returns the indexes of its elements to the right closest larger number
     • 4) "Calculation saving". The base algorithm no need to calculated indexes on those numbers resolved in previous recursions. There is also a break to stop calculations once the number gets the index in the current recursion list.

     Other algorithms models could be design, more efficient for sure. It occurs to me ones based on dictionaries or on different slicing strategies.

     def closest_larger_right(arr):- len_total = len(arr) result = [None] * len_total- def recursive(arr, len_total, position=0):- # 2) Termination condition if len(arr) > 1:- mid = len(arr) // 2 left = arr[:mid] right = arr[mid:]- position_left = 0 + position position_right = len(left) + position- # 1) Recursive calls recursive(left, len_total, position_left) recursive(right, len_total, position_right)- # 3) Base algorithm for i in range(len(arr)-1): # 4) Calculation saving if result[i + position] is None: for j in range(i+1, len(arr), 1): if (arr[i] < arr[j]): result[i + position] = j + position break return result- return recursive(arr, len_total)-# output: [2, 2, 3, 7, 5, 7, 7, None]print(closest_larger_right([5, 2, 6, 8, 1, 4, 3, 9]))--

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     1/5

   • Divide and conquer strategy to merge multiple sorted arrays

     Top Answer

     Answered Aug 26, 2015 · 4 votes

     A divide and conquer approach would be to have a recursive function k-way-merge(), that gets a list of lists as input, and at each step:

     • If you currently have 1 array, return it (stop clause)
     • Otherwise, split the list of lists to two, and for each half - recursively invoke k-way-merge(). merge the two resulting lists.

     The main aspect you need to change in your code is in:

     int[] first_Half = new int[half]; int[] second_Half = new int[lists.length - half]; -

     Here, you need first_half and second_half to be int[][], as they are actually list of lists.

     In addition, in the last line:

     return merge(merge(first_half),merge(second_half));-

     Note that the outer merge() is different, it's not a recursive call - but a call to "regular" merge(), that merges two arrays into one (as the logic on how to do it is missing from the code, I assume you have such merge() implemented).

     Other than that, the approach looks correct, but a bit inefficient, since you copy the int[][] object every iteration, rather than using indices to "remember where you are".

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     2/5

   • Divide and Conquer algorithm in C++

     Top Answer

     Answered Jan 26, 2017 · 0 votes

     Got accepted (finally) using two binary search (each for lower bound, and upper bound) with this code:

     #include<bits/stdc++.h>using namespace std;-long long n,m,i,l,r,mid1,mid2,ans,tmp,cnt,haha,k;long long ar[26214400];long long func(long long x){ haha = 0; for (k = 0; k < n; k++) haha += x/ar[k]; return haha;}int main(){ cin >> n >> m; for(i = 0; i < n; i++) cin >> ar[i]; sort(ar,ar+n); l = ar[0]; r = ar[0]*m; mid1 = (l+r)/2; tmp = func(mid1); while (l < r){ mid1 = (l+r)/2; tmp = func(mid1); if (tmp < m) l = mid1+1; else if (tmp > m) r = mid1-1; else r = mid1-1; } mid1 = l; //lower bound l = ar[0]; r = ar[0]*m; mid2 = (l+r)/2; tmp = func(mid2); while (l < r){ mid2 = (l+r)/2; tmp = func(mid2); if (tmp < m) l = mid2+1; else if (tmp > m) r = mid2-1; else l = mid2+1; } mid2 = r; //upper bound while (mid1 <= mid2 and func(mid1) != m) mid1 += 1; while (mid2 >= mid1 and func(mid2) != m) mid2 -= 1; ans = mid2-mid1+1; cout << ans << endl;}

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     3/5

   • divide and conquer approach for exponentiation?

     Top Answer

     Answered May 13, 2011 · 8 votes

     There are a couple of algorithms grouped together under the name square and multiply. You could get some inspiration from them.

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     4/5

   • Divide-and-conquer algorithms' property example

     Top Answer

     Answered Jan 30, 2014 · 2 votes

     You're not missing anything. The theorem and its proof are wrong. The error is here:

     T(n) = T(k) + T(n-k) + 1-

     The constant term of 1 should be 2, as the function makes one recursive call for each of the two pieces into which it divides the problem. The correct bound is 2N-1, rather than N. Hopefully, this error will be fixed in the next edition of your textbook, or at least in the errata.

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     5/5

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3. www.reddit.com › r › totalwarDivide and Conquer medieval 2 total war : r/totalwar - Reddit

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   A subreddit for the Total War strategy game series, made by Creative Assembly. Discussions, strategies, stories, crude cave-drawings, and more for Medieval 2, Empire, Shogun 2, Rome 2, Attila, Thrones of Britannia, Warhammer, Three Kingdoms, Troy, Pharaoh and others.

4. Videos

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     Divide and conquer strategy || general method || merge sort with an example and algorithm || DAA

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     Divide and Conquer Strategy

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5. www.geeksforgeeks.org › c-cpp-divide-and-conquerC/C++ Divide and Conquer Programs - GeeksforGeeks

   www.geeksforgeeks.org › c-cpp-divide-and-conquer

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   4 days ago · C/C++ Divide and Conquer Programs. The divide and conquer is an algorithmic approach to solve problems by dividing them into smaller sub-problems, solving them, and then constructing the complete solution using the solution of smaller sub-problems. This approach uses the recursion to divide the problem into smaller subproblems and it can only ...

6. www.testingxperts.com › blog › optimize-businessHow to Optimize Business Security with DevSecOps?

   www.testingxperts.com › blog › optimize-business

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   5 days ago · Implement Segmentation Strategy: Another way to ensure the success of DevSecOps implementation is by avoiding hackers and attackers through segmentation. It is also known as the divide-and-conquer strategy.

7. www.nature.com › articles › s44333/024/00001-9Calibrated confidence learning for large-scale real-time ...

   www.nature.com › articles › s44333/024/00001-9

   4 days ago · By employing spatial divide-and-conquer modeling, our ensemble model produces an accurate solution with minimal false alarms. This approach can result in a sustainable solution that optimizes ...

8. countercurrents.org › 2024 › 05Christians, Muslims, And Jews For A Secular One-State ...

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   2 days ago · There is a way to create a safe homeland for the Jews, Muslims, and Christians currently living in the State of Israel and the Israeli-occupied State of Palestine . It is a secular one-state...

9. pasreport.com › Unmasking-Bidens-Strategy-toUnmasking Biden’s Strategy to Divide America for Political Gain

   pasreport.com › Unmasking-Bidens-Strategy-to

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   4 days ago · Episode Description. In this episode of The P.A.S. Report Podcast, Professor Nick Giordano exposes President Biden’s strategy to divide Americans for political gain. Over the weekend, President Biden delivered a speech at Morehouse College that sparked controversy, claiming his political opponents don’t see Black Americans “in the future ...