Tag Archives: dynamic programming

C# || Counting Bits – How To Return The Number Of 1’s In Binary Representation Of X Using C#

The following is a module with functions which demonstrates how to return the number of 1’s in binary representation of X using C#.


1. Count Bits – Problem Statement

Given an integer n, return an array ans of length n + 1 such that for each i (0 <= i <= n), ans[i] is the number of 1‘s in the binary representation of i.

Example 1:


Input: n = 2
Output: [0,1,1]
Explanation:
0 --> 0
1 --> 1
2 --> 10

Example 2:


Input: n = 5
Output: [0,1,1,2,1,2]
Explanation:
0 --> 0
1 --> 1
2 --> 10
3 --> 11
4 --> 100
5 --> 101


2. Count Bits – Solution

The following is a solution which demonstrates how return the number of 1’s in binary representation of X.

In this problem, we can see a pattern start to form.

When the current n is even, we can get the answer by dividing by 2 (e.g result[n] = result[n / 2])

When the current n is odd, we can get the answer by getting the result at previous index and adding 1 (e.g result[n] = result[n – 1] + 1)

QUICK NOTES:
The highlighted lines are sections of interest to look out for.

The code is heavily commented, so no further insight is necessary. If you have any questions, feel free to leave a comment below.

Once compiled, you should get this as your output for the example cases:


[0,1,1]
[0,1,1,2,1,2]

C# || How To Find The Largest Divisible Subset In Array Using C#

The following is a module with functions which demonstrates how to find the largest divisible subset in an array using C#.


1. Largest Divisible Subset – Problem Statement

Given a set of distinct positive integers nums, return the largest subset answer such that every pair (answer[i], answer[j]) of elements in this subset satisfies:

  • answer[i] % answer[j] == 0, or
  • answer[j] % answer[i] == 0

If there are multiple solutions, return any of them.

Example 1:


Input: nums = [1,2,3]
Output: [1,2]
Explanation: [1,3] is also accepted.

Example 2:


Input: nums = [1,2,4,8]
Output: [1,2,4,8]


2. Largest Divisible Subset – Solution

The following is a solution which demonstrates how to find the largest divisible subset in an array.

This solution uses Dynamic Programming to find the largest divisible subset.

QUICK NOTES:
The highlighted lines are sections of interest to look out for.

The code is heavily commented, so no further insight is necessary. If you have any questions, feel free to leave a comment below.

Once compiled, you should get this as your output for the example cases:


[1,2]
[1,2,4,8]

C# || How To Find Longest Arithmetic Subsequence Of An Array Using C#

The following is a module with functions which demonstrates how to find the longest arithmetic subsequence of an array using C#.


1. Longest Arithmetic Subsequence Length – Problem Statement

Given an array nums of integers, return the length of the longest arithmetic subsequence in nums.

Recall that a subsequence of an array nums is a list nums[i1], nums[i2], …, nums[ik] with 0 <= i1 < i2 < … < ik <= nums.length – 1, and that a sequence seq is arithmetic if seq[i+1] – seq[i] are all the same value (for 0 <= i < seq.length – 1).

Example 1:


Input: nums = [3,6,9,12]
Output: 4
Explanation:
The whole array is an arithmetic sequence with steps of length = 3.

Example 2:


Input: nums = [9,4,7,2,10]
Output: 3
Explanation:
The longest arithmetic subsequence is [4,7,10].

Example 3:


Input: nums = [20,1,15,3,10,5,8]
Output: 4
Explanation:
The longest arithmetic subsequence is [20,15,10,5].


2. Longest Arithmetic Subsequence Length – Solution

The following is a solution which demonstrates how to find the longest arithmetic subsequence of an array.

The main idea in this solution is to maintain a dictionary map array of the differences seen at each index, where dp[index][diff] holds the frequency count at that index, for that specific diff.

Each item in the array is considered and checked against to their items to the left.

For each number (i,j) we determine the difference d = nums[i] – nums[j] and keep a count of the frequency the difference has been seen.

In the end, the max difference frequency is returned.

QUICK NOTES:
The highlighted lines are sections of interest to look out for.

The code is heavily commented, so no further insight is necessary. If you have any questions, feel free to leave a comment below.

Once compiled, you should get this as your output for the example cases:


4
3
4

C++ || Knapsack Problem Using Dynamic Programming

The following is another homework assignment which was presented in an Algorithm Engineering class. Using a custom timer class, the following is a program which reduces the problem of selecting which Debian Linux packages to include on installation media, to the classical knapsack problem.

The program demonstrated on this page extends the previously implemented Exhaustive Search algorithm, this time using Dynamic Programming to find a solution to this problem.

Debian Package Overview SelectShow

==== 1. THE PROBLEM ====

The Exhaustive Search algorithm ran in O(2n) time and was very slow.

The goal of this program is to implement a dynamic programming algorithm which runs in O(n2 • W) time, returning the optimal set of items/packages contained in the input file, which is fast enough to produce solutions to inputs of realistic size.

This program solves the following problem:

Input: A list of Debian packages, each with a size (in kilobytes) and number of votes, both of which are integers; and an integer W representing the capacity of the install media (in kilobytes).

Output: The set of packages with total size ≤ W , such that the total number of package votes is maximized.

In terms of the knapsack problem, the Debian package votes correspond to knapsack values, and our Debian package sizes correspond to knapsack weights.

==== 2. THE INPUT ====

The following file (knapsack_packages.txt) contains the name, size, and votes for approximately 36,000 binary Debian packages that are currently available on the amd64 platform, and have popcon information.

The file obeys the following format:

[ number of packages ]
[ name 0 ] [ space ] [ votes 0 ] [ space ] [ size 0 ] [ newline ]
[ name 1 ] [ space ] [ votes 1 ] [ space ] [ size 1 ] [ newline ]
[ name 2 ] [ space ] [ votes 2 ] [ space ] [ size 2 ] [ newline ]
...

The packages are arranged within the file in sorted order, from the largest number of votes to the smallest.

==== 3. FLOW OF CONTROL ====

A test harness program is created which executes the above function and measures the elapsed time of the code corresponding to the algorithm in question. The test program will perform the following steps:

1. Load the "knapsack_packages.txt" file into memory.

2. Input size "n" and weight "W" as variables.

3. Execute the dynamic knapsack algorithm. The output of this algorithm should be the best combination sequence of packages.

4. Print the first 20 packages from the solution. A solution is the best sequence of packages, displaying the name of the package, the votes, and the size of each package, as well as the total votes and total size of the entire solution.

A knapsack problem instances is created of varying input sizes “n” by using the first “n” entries in the file knapsack_packages.txt. In other words, to create a problem instance with n = 100, only use the first 100 packages listed in the file as input.

==== 4. TEST HARNESS ====

Note: This program uses two external header files (Timer.h and Project2.h).
• Code for the Timer class (Timer.h) can be found here.
• Code for “Project2.h” can be found here.
• “Project5.h” is listed below.

==== 5. THE ALGORITHMS – “include Project5.h” ====


QUICK NOTES:
The highlighted lines are sections of interest to look out for.

The code is heavily commented, so no further insight is necessary. If you have any questions, feel free to leave a comment below.

Note: Dont forget to include the input file!

The following is sample output:

=== RUN #1 ===

n = 36149, W = 65536

-- Dynamic Search Solution --

- Number of packages generated in this set: 764

- First 20 packages..

debianutils 90 128329
libgcc1 46 128327
debconf 168 121503
grep 595 121426
gzip 142 121346
sed 261 121220
findutils 805 121173
lsb-base 26 121121
sysv-rc 80 121092
sysvinit-utils 116 121078
base-files 65 121072
initscripts 93 121037
util-linux 846 121022
mount 272 120961
libselinux1 109 120918
cron 120 120872
base-passwd 49 120856
tzdata 488 120813
logrotate 64 120745
popularity-contest 67 120729

Total Size = 65536 -- Total Votes = 25250749

It took 33500 clicks (33.50 seconds)

=== RUN #2 ===

n = 36149, W = 800000

-- Dynamic Search Solution --

- Number of packages generated in this set: 4406

- First 20 packages..

debianutils 90 128329
libgcc1 46 128327
dpkg 2672 128294
perl-base 1969 127369
debconf 168 121503
grep 595 121426
gzip 142 121346
login 980 121332
coreutils 6505 121240
bash 1673 121229
sed 261 121220
findutils 805 121173
lsb-base 26 121121
sysv-rc 80 121092
sysvinit-utils 116 121078
base-files 65 121072
initscripts 93 121037
util-linux 846 121022
mount 272 120961
libselinux1 109 120918

Total Size = 800000 -- Total Votes = 41588693

It took 608760 clicks (608.76 seconds)