I'm trying to write an algorithm that will generate all strings of length nm, with exactly n of each number 1, 2, ... m,
For instance all strings of length 6, with exactly two 1's, two 2's and two 3's e.g. 112233, 121233,
I managed to do this with just 1's and 2's using a recursive method, but can't seem to get something that works when I introduce 3's.
When m = 2, the algorithm I have is:
generateAllStrings(int len, int K, String str)
{
if(len == 0)
{
output(str);
}
if(K > 0)
{
generateAllStrings(len - 1, K - 1, str + '2');
}
if(len > K)
{
generateAllStrings(len - 1, K, str + '1');
}
}
I've tried inserting similar conditions for the third number but the algorithm doesn't give a correct output. After that I wouldn't even know how to generalise for 4 numbers and above.
Is recursion the right thing to do? Any help would be appreciated.
One option would be to list off all distinct permutations of the string 111...1222...2...nnn....n. There are nice algorithms for enumerating all distinct permutations of a string in time proportional to the length of the string, and they'd probably be a good way to go about solving this problem.
To use a simple recursive algorithm, give each recursion the permutation so far (variable perm), and the number of occurances of each digit that is still available (array count).
Run the code snippet to generate all unique permutations for n=2 and m=4 (set: 11223344).
function permutations(n, m) {
var perm = "", count = []; // start with empty permutation
for (var i = 0; i < m; i++) count[i] = n; // set available number for each digit = n
permute(perm, count); // start recursion with "" and [n,n,n...]
function permute(perm, count) {
var done = true;
for (var i = 0; i < count.length; i++) { // iterate over all digits
if (count[i] > 0) { // more instances of digit i available
var c = count.slice(); // create hard copy of count array
--c[i]; // decrement count of digit i
permute(perm + (i + 1), c); // add digit to permutation and recurse
done = false; // digits left over: not the last step
}
}
if (done) document.write(perm + "<BR>"); // no digits left: complete permutation
}
}
permutations(2, 4);
You can easily do this using DFS (or BFS alternatively). We can define an graph such that each node contains one string and a node is connected to any node that holds a string with a pair of int swaped in comparison to the original string. This graph is connected, thus we can easily generate a set of all nodes; which will contain all strings that are searched:
set generated_strings
list nodes
nodes.add(generateInitialString(N , M))
generated_strings.add(generateInitialString(N , M))
while(!nodes.empty())
string tmp = nodes.remove(0)
for (int i in [0 , N * M))
for (int j in distinct([0 , N * M) , i))
string new = swap(tmp , i , j)
if (!generated_strings.contains(new))
nodes.add(new)
generated_strings.add(new)
//generated_strings now contains all strings that can possibly be generated.
Related
The below question was asked in the atlassian company online test ,I don't have test cases , this is the below question I took from this link
find the number of ways you can form a string on size N, given an unlimited number of 0s and 1s. But
you cannot have D number of consecutive 0s and T number of consecutive 1s. N, D, T were given as inputs,
Please help me on this problem,any approach how to proceed with it
My approach for the above question is simply I applied recursion and tried for all possiblity and then I memoized it using hash map
But it seems to me there must be some combinatoric approach that can do this question in less time and space? for debugging purposes I am also printing the strings generated during recursion, if there is flaw in my approach please do tell me
#include <bits/stdc++.h>
using namespace std;
unordered_map<string,int>dp;
int recurse(int d,int t,int n,int oldd,int oldt,string s)
{
if(d<=0)
return 0;
if(t<=0)
return 0;
cout<<s<<"\n";
if(n==0&&d>0&&t>0)
return 1;
string h=to_string(d)+" "+to_string(t)+" "+to_string(n);
if(dp.find(h)!=dp.end())
return dp[h];
int ans=0;
ans+=recurse(d-1,oldt,n-1,oldd,oldt,s+'0')+recurse(oldd,t-1,n-1,oldd,oldt,s+'1');
return dp[h]=ans;
}
int main()
{
int n,d,t;
cin>>n>>d>>t;
dp.clear();
cout<<recurse(d,t,n,d,t,"")<<"\n";
return 0;
}
You are right, instead of generating strings, it is worth to consider combinatoric approach using dynamic programming (a kind of).
"Good" sequence of length K might end with 1..D-1 zeros or 1..T-1 of ones.
To make a good sequence of length K+1, you can add zero to all sequences except for D-1, and get 2..D-1 zeros for the first kind of precursors and 1 zero for the second kind
Similarly you can add one to all sequences of the first kind, and to all sequences of the second kind except for T-1, and get 1 one for the first kind of precursors and 2..T-1 ones for the second kind
Make two tables
Zeros[N][D] and Ones[N][T]
Fill the first row with zero counts, except for Zeros[1][1] = 1, Ones[1][1] = 1
Fill row by row using the rules above.
Zeros[K][1] = Sum(Ones[K-1][C=1..T-1])
for C in 2..D-1:
Zeros[K][C] = Zeros[K-1][C-1]
Ones[K][1] = Sum(Zeros[K-1][C=1..T-1])
for C in 2..T-1:
Ones[K][C] = Ones[K-1][C-1]
Result is sum of the last row in both tables.
Also note that you really need only two active rows of the table, so you can optimize size to Zeros[2][D] after debugging.
This can be solved using dynamic programming. I'll give a recursive solution to the same. It'll be similar to generating a binary string.
States will be:
i: The ith character that we need to insert to the string.
cnt: The number of consecutive characters before i
bit: The character which was repeated cnt times before i. Value of bit will be either 0 or 1.
Base case will: Return 1, when we reach n since we are starting from 0 and ending at n-1.
Define the size of dp array accordingly. The time complexity will be 2 x N x max(D,T)
#include<bits/stdc++.h>
using namespace std;
int dp[1000][1000][2];
int n, d, t;
int count(int i, int cnt, int bit) {
if (i == n) {
return 1;
}
int &ans = dp[i][cnt][bit];
if (ans != -1) return ans;
ans = 0;
if (bit == 0) {
ans += count(i+1, 1, 1);
if (cnt != d - 1) {
ans += count(i+1, cnt + 1, 0);
}
} else {
// bit == 1
ans += count(i+1, 1, 0);
if (cnt != t-1) {
ans += count(i+1, cnt + 1, 1);
}
}
return ans;
}
signed main() {
ios_base::sync_with_stdio(false), cin.tie(nullptr);
cin >> n >> d >> t;
memset(dp, -1, sizeof dp);
cout << count(0, 0, 0);
return 0;
}
We need to find the maximum element in an array which is also equal to product of two elements in the same array. For example [2,3,6,8] , here 6=2*3 so answer is 6.
My approach was to sort the array and followed by a two pointer method which checked whether the product exist for each element. This is o(nlog(n)) + O(n^2) = O(n^2) approach. Is there a faster way to this ?
There is a slight better solution with O(n * sqrt(n)) if you are allowed to use O(M) memory M = max number in A[i]
Use an array of size M to mark every number while you traverse them from smaller to bigger number.
For each number try all its factors and see if those were already present in the array map.
Here is a pseudo code for that:
#define M 1000000
int array_map[M+2];
int ans = -1;
sort(A,A+n);
for(i=0;i<n;i++) {
for(j=1;j<=sqrt(A[i]);j++) {
int num1 = j;
if(A[i]%num1==0) {
int num2 = A[i]/num1;
if(array_map[num1] && array_map[num2]) {
if(num1==num2) {
if(array_map[num1]>=2) ans = A[i];
} else {
ans = A[i];
}
}
}
}
array_map[A[i]]++;
}
There is an ever better approach if you know how to find all possible factors in log(M) this just becomes O(n*logM). You have to use sieve and backtracking for that
#JerryGoyal 's solution is correct. However, I think it can be optimized even further if instead of using B pointer, we use binary search to find the other factor of product if arr[c] is divisible by arr[a]. Here's the modification for his code:
for(c=n-1;(c>1)&& (max==-1);c--){ // loop through C
for(a=0;(a<c-1)&&(max==-1);a++){ // loop through A
if(arr[c]%arr[a]==0) // If arr[c] is divisible by arr[a]
{
if(binary_search(a+1, c-1, (arr[c]/arr[a]))) //#include<algorithm>
{
max = arr[c]; // if the other factor x of arr[c] is also in the array such that arr[c] = arr[a] * x
break;
}
}
}
}
I would have commented this on his solution, unfortunately I lack the reputation to do so.
Try this.
Written in c++
#include <vector>
#include <algorithm>
using namespace std;
int MaxElement(vector< int > Input)
{
sort(Input.begin(), Input.end());
int LargestElementOfInput = 0;
int i = 0;
while (i < Input.size() - 1)
{
if (LargestElementOfInput == Input[Input.size() - (i + 1)])
{
i++;
continue;
}
else
{
if (Input[i] != 0)
{
LargestElementOfInput = Input[Input.size() - (i + 1)];
int AllowedValue = LargestElementOfInput / Input[i];
int j = 0;
while (j < Input.size())
{
if (Input[j] > AllowedValue)
break;
else if (j == i)
{
j++;
continue;
}
else
{
int Product = Input[i] * Input[j++];
if (Product == LargestElementOfInput)
return Product;
}
}
}
i++;
}
}
return -1;
}
Once you have sorted the array, then you can use it to your advantage as below.
One improvement I can see - since you want to find the max element that meets the criteria,
Start from the right most element of the array. (8)
Divide that with the first element of the array. (8/2 = 4).
Now continue with the double pointer approach, till the element at second pointer is less than the value from the step 2 above or the match is found. (i.e., till second pointer value is < 4 or match is found).
If the match is found, then you got the max element.
Else, continue the loop with next highest element from the array. (6).
Efficient solution:
2 3 8 6
Sort the array
keep 3 pointers C, B and A.
Keeping C at the last and A at 0 index and B at 1st index.
traverse the array using pointers A and B till C and check if A*B=C exists or not.
If it exists then C is your answer.
Else, Move C a position back and traverse again keeping A at 0 and B at 1st index.
Keep repeating this till you get the sum or C reaches at 1st index.
Here's the complete solution:
int arr[] = new int[]{2, 3, 8, 6};
Arrays.sort(arr);
int n=arr.length;
int a,b,c,prod,max=-1;
for(c=n-1;(c>1)&& (max==-1);c--){ // loop through C
for(a=0;(a<c-1)&&(max==-1);a++){ // loop through A
for(b=a+1;b<c;b++){ // loop through B
prod=arr[a]*arr[b];
if(prod==arr[c]){
System.out.println("A: "+arr[a]+" B: "+arr[b]);
max=arr[c];
break;
}
if(prod>arr[c]){ // no need to go further
break;
}
}
}
}
System.out.println(max);
I came up with below solution where i am using one array list, and following one formula:
divisor(a or b) X quotient(b or a) = dividend(c)
Sort the array.
Put array into Collection Col.(ex. which has faster lookup, and maintains insertion order)
Have 2 pointer a,c.
keep c at last, and a at 0.
try to follow (divisor(a or b) X quotient(b or a) = dividend(c)).
Check if a is divisor of c, if yes then check for b in col.(a
If a is divisor and list has b, then c is the answer.
else increase a by 1, follow step 5, 6 till c-1.
if max not found then decrease c index, and follow the steps 4 and 5.
Check this C# solution:
-Loop through each element,
-loop and multiply each element with other elements,
-verify if the product exists in the array and is the max
private static int GetGreatest(int[] input)
{
int max = 0;
int p = 0; //product of pairs
//loop through the input array
for (int i = 0; i < input.Length; i++)
{
for (int j = i + 1; j < input.Length; j++)
{
p = input[i] * input[j];
if (p > max && Array.IndexOf(input, p) != -1)
{
max = p;
}
}
}
return max;
}
Time complexity O(n^2)
This is a question from one of the online coding challenge (which has completed).
I just need some logic for this as to how to approach.
Problem Statement:
We have two strings A and B with the same super set of characters. We need to change these strings to obtain two equal strings. In each move we can perform one of the following operations:
1. swap two consecutive characters of a string
2. swap the first and the last characters of a string
A move can be performed on either string.
What is the minimum number of moves that we need in order to obtain two equal strings?
Input Format and Constraints:
The first and the second line of the input contains two strings A and B. It is guaranteed that the superset their characters are equal.
1 <= length(A) = length(B) <= 2000
All the input characters are between 'a' and 'z'
Output Format:
Print the minimum number of moves to the only line of the output
Sample input:
aab
baa
Sample output:
1
Explanation:
Swap the first and last character of the string aab to convert it to baa. The two strings are now equal.
EDIT : Here is my first try, but I'm getting wrong output. Can someone guide me what is wrong in my approach.
int minStringMoves(char* a, char* b) {
int length, pos, i, j, moves=0;
char *ptr;
length = strlen(a);
for(i=0;i<length;i++) {
// Find the first occurrence of b[i] in a
ptr = strchr(a,b[i]);
pos = ptr - a;
// If its the last element, swap with the first
if(i==0 && pos == length-1) {
swap(&a[0], &a[length-1]);
moves++;
}
// Else swap from current index till pos
else {
for(j=pos;j>i;j--) {
swap(&a[j],&a[j-1]);
moves++;
}
}
// If equal, break
if(strcmp(a,b) == 0)
break;
}
return moves;
}
Take a look at this example:
aaaaaaaaab
abaaaaaaaa
Your solution: 8
aaaaaaaaab -> aaaaaaaaba -> aaaaaaabaa -> aaaaaabaaa -> aaaaabaaaa ->
aaaabaaaaa -> aaabaaaaaa -> aabaaaaaaa -> abaaaaaaaa
Proper solution: 2
aaaaaaaaab -> baaaaaaaaa -> abaaaaaaaa
You should check if swapping in the other direction would give you better result.
But sometimes you will also ruin the previous part of the string. eg:
caaaaaaaab
cbaaaaaaaa
caaaaaaaab -> baaaaaaaac -> abaaaaaaac
You need another swap here to put back the 'c' to the first place.
The proper algorithm is probably even more complex, but you can see now what's wrong in your solution.
The A* algorithm might work for this problem.
The initial node will be the original string.
The goal node will be the target string.
Each child of a node will be all possible transformations of that string.
The current cost g(x) is simply the number of transformations thus far.
The heuristic h(x) is half the number of characters in the wrong position.
Since h(x) is admissible (because a single transformation can't put more than 2 characters in their correct positions), the path to the target string will give the least number of transformations possible.
However, an elementary implementation will likely be too slow. Calculating all possible transformations of a string would be rather expensive.
Note that there's a lot of similarity between a node's siblings (its parent's children) and its children. So you may be able to just calculate all transformations of the original string and, from there, simply copy and recalculate data involving changed characters.
You can use dynamic programming. Go over all swap possibilities while storing all the intermediate results along with the minimal number of steps that took you to get there. Actually, you are going to calculate the minimum number of steps for every possible target string that can be obtained by applying given rules for a number times. Once you calculate it all, you can print the minimum number of steps, which is needed to take you to the target string. Here's the sample code in JavaScript, and its usage for "aab" and "baa" examples:
function swap(str, i, j) {
var s = str.split("");
s[i] = str[j];
s[j] = str[i];
return s.join("");
}
function calcMinimumSteps(current, stepsCount)
{
if (typeof(memory[current]) !== "undefined") {
if (memory[current] > stepsCount) {
memory[current] = stepsCount;
} else if (memory[current] < stepsCount) {
stepsCount = memory[current];
}
} else {
memory[current] = stepsCount;
calcMinimumSteps(swap(current, 0, current.length-1), stepsCount+1);
for (var i = 0; i < current.length - 1; ++i) {
calcMinimumSteps(swap(current, i, i + 1), stepsCount+1);
}
}
}
var memory = {};
calcMinimumSteps("aab", 0);
alert("Minimum steps count: " + memory["baa"]);
Here is the ruby logic for this problem, copy this code in to rb file and execute.
str1 = "education" #Sample first string
str2 = "cnatdeiou" #Sample second string
moves_count = 0
no_swap = 0
count = str1.length - 1
def ends_swap(str1,str2)
str2 = swap_strings(str2,str2.length-1,0)
return str2
end
def swap_strings(str2,cp,np)
current_string = str2[cp]
new_string = str2[np]
str2[cp] = new_string
str2[np] = current_string
return str2
end
def consecutive_swap(str,current_position, target_position)
counter=0
diff = current_position > target_position ? -1 : 1
while current_position!=target_position
new_position = current_position + diff
str = swap_strings(str,current_position,new_position)
# p "-------"
# p "CP: #{current_position} NP: #{new_position} TP: #{target_position} String: #{str}"
current_position+=diff
counter+=1
end
return counter,str
end
while(str1 != str2 && count!=0)
counter = 1
if str1[-1]==str2[0]
# p "cross match"
str2 = ends_swap(str1,str2)
else
# p "No match for #{str2}-- Count: #{count}, TC: #{str1[count]}, CP: #{str2.index(str1[count])}"
str = str2[0..count]
cp = str.rindex(str1[count])
tp = count
counter, str2 = consecutive_swap(str2,cp,tp)
count-=1
end
moves_count+=counter
# p "Step: #{moves_count}"
# p str2
end
p "Total moves: #{moves_count}"
Please feel free to suggest any improvements in this code.
Try this code. Hope this will help you.
public class TwoStringIdentical {
static int lcs(String str1, String str2, int m, int n) {
int L[][] = new int[m + 1][n + 1];
int i, j;
for (i = 0; i <= m; i++) {
for (j = 0; j <= n; j++) {
if (i == 0 || j == 0)
L[i][j] = 0;
else if (str1.charAt(i - 1) == str2.charAt(j - 1))
L[i][j] = L[i - 1][j - 1] + 1;
else
L[i][j] = Math.max(L[i - 1][j], L[i][j - 1]);
}
}
return L[m][n];
}
static void printMinTransformation(String str1, String str2) {
int m = str1.length();
int n = str2.length();
int len = lcs(str1, str2, m, n);
System.out.println((m - len)+(n - len));
}
public static void main(String[] args) {
Scanner scan = new Scanner(System.in);
String str1 = scan.nextLine();
String str2 = scan.nextLine();
printMinTransformation("asdfg", "sdfg");
}
}
This Question was asked to me at the Google interview. I could do it O(n*n) ... Can I do it in better time.
A string can be formed only by 1 and 0.
Definition:
X & Y are strings formed by 0 or 1
D(X,Y) = Remove the things common at the start from both X & Y. Then add the remaining lengths from both the strings.
For e.g.
D(1111, 1000) = Only First alphabet is common. So the remaining string is 111 & 000. Therefore the result length("111") & length("000") = 3 + 3 = 6
D(101, 1100) = Only First two alphabets are common. So the remaining string is 01 & 100. Therefore the result length("01") & length("100") = 2 + 3 = 5
It is pretty that obvious that do find out such a crazy distance is going to be linear. O(m).
Now the question is
given n input, say like
1111
1000
101
1100
Find out the maximum crazy distance possible.
n is the number of input strings.
m is the max length of any input string.
The solution of O(n2 * m) is pretty simple. Can it be done in a better way?
Let's assume that m is fixed. Can we do this in better than O(n^2) ?
Put the strings into a tree, where 0 means go left and 1 means go right. So for example
1111
1000
101
1100
would result in a tree like
Root
1
0 1
0 1* 0 1
0* 0* 1*
where the * means that an element ends there. Constructing this tree clearly takes O(n m).
Now we have to find the diameter of the tree (the longest path between two nodes, which is the same thing as the "crazy distance"). The optimized algorithm presented there hits each node in the tree once. There are at most min(n m, 2^m) such nodes.
So if n m < 2^m, then the the algorithm is O(n m).
If n m > 2^m (and we necessarily have repeated inputs), then the algorithm is still O(n m) from the first step.
This also works for strings with a general alphabet; for an alphabet with k letters build a k-ary tree, in which case the runtime is still O(n m) by the same reasoning, though it takes k times as much memory.
I think this is possible in O(nm) time by creating a binary tree where each bit in a string encodes the path (0 left, 1 right). Then finding the maximum distance between nodes of the tree which can be done in O(n) time.
This is my solution, I think it works:
Create a binary tree from all strings. The tree will be constructed in this way:
at every round, select a string and add it to the tree. so for your example, the tree will be:
<root>
<1> <empty>
<1> <0>
<1> <0> <1> <0>
<1> <0> <0>
So each path from root to a leaf will represent a string.
Now the distance between each two leaves is the distance between two strings. To find the crazy distance, you must find the diameter of this graph, that you can do it easily by dfs or bfs.
The total complexity of this algorithm is:
O(n*m) + O(n*m) = O(n*m).
I think this problem is something like "find prefix for two strings", you can use trie(http://en.wikipedia.org/wiki/Trie) to accerlate searching
I have a google phone interview 3 days before, but maybe I failed...
Best luck to you
To get an answer in O(nm) just iterate across the characters of all string (this is an O(n) operation). We will compare at most m characters, so this will be done O(m). This gives a total of O(nm). Here's a C++ solution:
int max_distance(char** strings, int numstrings, int &distance) {
distance = 0;
// loop O(n) for initialization
for (int i=0; i<numstrings; i++)
distance += strlen(strings[i]);
int max_prefix = 0;
bool done = false;
// loop max O(m)
while (!done) {
int c = -1;
// loop O(n)
for (int i=0; i<numstrings; i++) {
if (strings[i][max_prefix] == 0) {
done = true; // it is enough to reach the end of one string to be done
break;
}
int new_element = strings[i][max_prefix] - '0';
if (-1 == c)
c = new_element;
else {
if (c != new_element) {
done = true; // mismatch
break;
}
}
}
if (!done) {
max_prefix++;
distance -= numstrings;
}
}
return max_prefix;
}
void test_misc() {
char* strings[] = {
"10100",
"10101110",
"101011",
"101"
};
std::cout << std::endl;
int distance = 0;
std::cout << "max_prefix = " << max_distance(strings, sizeof(strings)/sizeof(strings[0]), distance) << std::endl;
}
Not sure why use trees when iteration gives you the same big O computational complexity without the code complexity. anyway here is my version of it in javascript O(mn)
var len = process.argv.length -2; // in node first 2 arguments are node and program file
var input = process.argv.splice(2);
var current;
var currentCount = 0;
var currentCharLoc = 0;
var totalCount = 0;
var totalComplete = 0;
var same = true;
while ( totalComplete < len ) {
current = null;
currentCount = 0;
for ( var loc = 0 ; loc < len ; loc++) {
if ( input[loc].length === currentCharLoc) {
totalComplete++;
same = false;
} else if (input[loc].length > currentCharLoc) {
currentCount++;
if (same) {
if ( current === null ) {
current = input[loc][currentCharLoc];
} else {
if (current !== input[loc][currentCharLoc]) {
same = false;
}
}
}
}
}
if (!same) {
totalCount += currentCount;
}
currentCharLoc++;
}
console.log(totalCount);
Thinking about this question on testing string rotation, I wondered: Is there was such thing as a circular/cyclic hash function? E.g.
h(abcdef) = h(bcdefa) = h(cdefab) etc
Uses for this include scalable algorithms which can check n strings against each other to see where some are rotations of others.
I suppose the essence of the hash is to extract information which is order-specific but not position-specific. Maybe something that finds a deterministic 'first position', rotates to it and hashes the result?
It all seems plausible, but slightly beyond my grasp at the moment; it must be out there already...
I'd go along with your deterministic "first position" - find the "least" character; if it appears twice, use the next character as the tie breaker (etc). You can then rotate to a "canonical" position, and hash that in a normal way. If the tie breakers run for the entire course of the string, then you've got a string which is a rotation of itself (if you see what I mean) and it doesn't matter which you pick to be "first".
So:
"abcdef" => hash("abcdef")
"defabc" => hash("abcdef")
"abaac" => hash("aacab") (tie-break between aa, ac and ab)
"cabcab" => hash("abcabc") (it doesn't matter which "a" comes first!)
Update: As Jon pointed out, the first approach doesn't handle strings with repetition very well. Problems arise as duplicate pairs of letters are encountered and the resulting XOR is 0. Here is a modification that I believe fixes the the original algorithm. It uses Euclid-Fermat sequences to generate pairwise coprime integers for each additional occurrence of a character in the string. The result is that the XOR for duplicate pairs is non-zero.
I've also cleaned up the algorithm slightly. Note that the array containing the EF sequences only supports characters in the range 0x00 to 0xFF. This was just a cheap way to demonstrate the algorithm. Also, the algorithm still has runtime O(n) where n is the length of the string.
static int Hash(string s)
{
int H = 0;
if (s.Length > 0)
{
//any arbitrary coprime numbers
int a = s.Length, b = s.Length + 1;
//an array of Euclid-Fermat sequences to generate additional coprimes for each duplicate character occurrence
int[] c = new int[0xFF];
for (int i = 1; i < c.Length; i++)
{
c[i] = i + 1;
}
Func<char, int> NextCoprime = (x) => c[x] = (c[x] - x) * c[x] + x;
Func<char, char, int> NextPair = (x, y) => a * NextCoprime(x) * x.GetHashCode() + b * y.GetHashCode();
//for i=0 we need to wrap around to the last character
H = NextPair(s[s.Length - 1], s[0]);
//for i=1...n we use the previous character
for (int i = 1; i < s.Length; i++)
{
H ^= NextPair(s[i - 1], s[i]);
}
}
return H;
}
static void Main(string[] args)
{
Console.WriteLine("{0:X8}", Hash("abcdef"));
Console.WriteLine("{0:X8}", Hash("bcdefa"));
Console.WriteLine("{0:X8}", Hash("cdefab"));
Console.WriteLine("{0:X8}", Hash("cdfeab"));
Console.WriteLine("{0:X8}", Hash("a0a0"));
Console.WriteLine("{0:X8}", Hash("1010"));
Console.WriteLine("{0:X8}", Hash("0abc0def0ghi"));
Console.WriteLine("{0:X8}", Hash("0def0abc0ghi"));
}
The output is now:
7F7D7F7F
7F7D7F7F
7F7D7F7F
7F417F4F
C796C7F0
E090E0F0
A909BB71
A959BB71
First Version (which isn't complete): Use XOR which is commutative (order doesn't matter) and another little trick involving coprimes to combine ordered hashes of pairs of letters in the string. Here is an example in C#:
static int Hash(char[] s)
{
//any arbitrary coprime numbers
const int a = 7, b = 13;
int H = 0;
if (s.Length > 0)
{
//for i=0 we need to wrap around to the last character
H ^= (a * s[s.Length - 1].GetHashCode()) + (b * s[0].GetHashCode());
//for i=1...n we use the previous character
for (int i = 1; i < s.Length; i++)
{
H ^= (a * s[i - 1].GetHashCode()) + (b * s[i].GetHashCode());
}
}
return H;
}
static void Main(string[] args)
{
Console.WriteLine(Hash("abcdef".ToCharArray()));
Console.WriteLine(Hash("bcdefa".ToCharArray()));
Console.WriteLine(Hash("cdefab".ToCharArray()));
Console.WriteLine(Hash("cdfeab".ToCharArray()));
}
The output is:
4587590
4587590
4587590
7077996
You could find a deterministic first position by always starting at the position with the "lowest" (in terms of alphabetical ordering) substring. So in your case, you'd always start at "a". If there were multiple "a"s, you'd have to take two characters into account etc.
I am sure that you could find a function that can generate the same hash regardless of character position in the input, however, how will you ensure that h(abc) != h(efg) for every conceivable input? (Collisions will occur for all hash algorithms, so I mean, how do you minimize this risk.)
You'd need some additional checks even after generating the hash to ensure that the strings contain the same characters.
Here's an implementation using Linq
public string ToCanonicalOrder(string input)
{
char first = input.OrderBy(x => x).First();
string doubledForRotation = input + input;
string canonicalOrder
= (-1)
.GenerateFrom(x => doubledForRotation.IndexOf(first, x + 1))
.Skip(1) // the -1
.TakeWhile(x => x < input.Length)
.Select(x => doubledForRotation.Substring(x, input.Length))
.OrderBy(x => x)
.First();
return canonicalOrder;
}
assuming generic generator extension method:
public static class TExtensions
{
public static IEnumerable<T> GenerateFrom<T>(this T initial, Func<T, T> next)
{
var current = initial;
while (true)
{
yield return current;
current = next(current);
}
}
}
sample usage:
var sequences = new[]
{
"abcdef", "bcdefa", "cdefab",
"defabc", "efabcd", "fabcde",
"abaac", "cabcab"
};
foreach (string sequence in sequences)
{
Console.WriteLine(ToCanonicalOrder(sequence));
}
output:
abcdef
abcdef
abcdef
abcdef
abcdef
abcdef
aacab
abcabc
then call .GetHashCode() on the result if necessary.
sample usage if ToCanonicalOrder() is converted to an extension method:
sequence.ToCanonicalOrder().GetHashCode();
One possibility is to combine the hash functions of all circular shifts of your input into one meta-hash which does not depend on the order of the inputs.
More formally, consider
for(int i=0; i<string.length; i++) {
result^=string.rotatedBy(i).hashCode();
}
Where you could replace the ^= with any other commutative operation.
More examply, consider the input
"abcd"
to get the hash we take
hash("abcd") ^ hash("dabc") ^ hash("cdab") ^ hash("bcda").
As we can see, taking the hash of any of these permutations will only change the order that you are evaluating the XOR, which won't change its value.
I did something like this for a project in college. There were 2 approaches I used to try to optimize a Travelling-Salesman problem. I think if the elements are NOT guaranteed to be unique, the second solution would take a bit more checking, but the first one should work.
If you can represent the string as a matrix of associations so abcdef would look like
a b c d e f
a x
b x
c x
d x
e x
f x
But so would any combination of those associations. It would be trivial to compare those matrices.
Another quicker trick would be to rotate the string so that the "first" letter is first. Then if you have the same starting point, the same strings will be identical.
Here is some Ruby code:
def normalize_string(string)
myarray = string.split(//) # split into an array
index = myarray.index(myarray.min) # find the index of the minimum element
index.times do
myarray.push(myarray.shift) # move stuff from the front to the back
end
return myarray.join
end
p normalize_string('abcdef').eql?normalize_string('defabc') # should return true
Maybe use a rolling hash for each offset (RabinKarp like) and return the minimum hash value? There could be collisions though.