We Keep Coding

How would I allow this to go through every element to check if it is equal?

So I was trying to build a solitaire encryption program, but I keep running into a problem when it comes to this method. The char array a represents the word the user inputs (converted it into an array to make it easier) and the char array b represents the alphabets so it has 25 indexes. What I am trying to do is match the alphabet to its number. It seemed simple enough but I am having a hard time as it keeps throwing an ArrayIndexOutOfBoundsException. I have tried to use for loops, nested for loops and other tests but it keeps throwing the exception or just outputs unexpected results such as [0, 0, 0, 0, 0]. I have debugged it and it seems like b[i] never equals a[j] so j will always be 0.
public static int[] converter(char[] a, char[] b){
int[] res = new int[a.length];
int i = 0;
int j = 0;
while(i < a.length){
if(b[i] == Character.toUpperCase(a[j])){ //Does not run through the first loop at all
res[j] = i + 1;
j = j + 1;
} else {
i = i + 1;
}
}
return res;
}
Please do not link the similar question. It does not answer my question.

The code below is a solution. We want the wordCharacterIndex to iterate through the word to see the place where a character is. The characterIndex iterates through the characters to compare with the word's character present at the wordCharacterIndex. After setting the result, we need to reset the characterIndex so that it goes back to the first character in the character array to compare with the other word characters, if we didn't, the following characters of the word would need to be at a higher character index, which is not what we want. Naming variables actual words is very important to better understand what you are trying to do within your code. You were comparing i < a.length while you were iterating through b[i] which made it possible to go larger than b's bounds and therefore cause an ArrayIndexOutOfBoundsException. I hope this helps you better understand.
public static int[] converter(char[] word, char[] characters){
int[] result = new int[word.length];
int characterIndex = 0;
int wordCharacterIndex = 0;
while(wordCharacterIndex < word.length){
if(characters[characterIndex] == Character.toUpperCase(word[wordCharacterIndex])){
result[wordCharacterIndex] = characterIndex + 1;
wordCharacterIndex++;
characterIndex = 0;
} else {
characterIndex++;
}
}
return result;
}

Optimizing recursive backtrack

I solved a variation of the knapsack problem by backtracking all of the possible solutions. Basically 0 means that item is not in the backpack, 1 means that the item is in the backpack. Cost is the value of all items in the backpack, we are trying to achieve the lowest value possible while having items of every "class". Each time that a combination of all classes is found, I calculate the value of all items and if it's lower than globalBestValue, I save the value. I do this is verify().
Now I'm trying to optimize my recursive backtrack. My idea was to iterate over my array as it's being generated and return the generator if the "cost" of my generated numbers is already higher then my current best-value, therefore the combination currently being generated can't be the new best-value and can be skipped.
However with my optimization, my backtrack is not generating all the values and it actually skips the "best" value I'm trying to find. Could you tell me where the problem is?
private int globalBestValue = Integer.MAX_VALUE;
private int[] arr;
public KnapSack(int numberOfItems) {
arr = new int[numberOfItems];
}
private void generate(int fromIndex) {
int currentCost = 0; // my optimisation starts here
for (int i = 0; i < arr.length; i++) {
if (currentCost > globalBestValue) {
return;
}
if (arr[i] == 1) {
currentCost += allCosts.get(i);
}
} // ends here
if (fromIndex == arr.length) {
verify();
return;
}
for (int i = 0; i <= 1; i++) {
arr[fromIndex] = i;
generate(fromIndex + 1);
}
}
public void verify() {
// skipped the code verifying the arr if it's correct, it's long and not relevant
if (isCorrect == true && currentValue < globalBestValue) {
globalBestValue = currentValue;
}else{
return;
}
}

Pardon my bluntness, but your efforts at optimizing an inefficient algorithm can only be described as polishing the turd. You will not solve a knapsack problem of any decent size by brute force, and early return isn't enough. I have mentioned one approach to writing an efficient program on CodeReview SE; it requires a considerable effort, but you gotta do what you gotta do.
Having said that, I'd recommend you write the arr to console in order to troubleshoot the sequence. It looks like when you go back to the index i-1, the element at i remains set to 1, and you estimate the upper bound instead of the lower one. The following change might work: replace your code
for (int i = 0; i <= 1; i++) {
arr[fromIndex] = i;
generate(fromIndex + 1);
}
with
arr[fromIndex] = 1;
generate(fromIndex + 1);
arr[fromIndex] = 0;
generate(fromIndex + 1);
This turns it into a sort of greedy algorithm: instead of starting with 0000000, you effectively start with 1111111. And obviously, when you store the globalBestValue, you should store the actual data which gives it. But the main advice is: when your algorithm behaves weirdly, tracing is your friend.

How do I get my program to store every possible combination of 55 bits of an 81 bit BigInteger?

I'm making a Sudoku program, and I wanted to store every combination of x bits in an 81-bit integer into a list. I want to be able to then shuffle this list, iterate through it, and each on-bit will represent a cell that is to be removed from an existing Sudoku grid, x depending on difficulty. My program then tests this unique puzzle to see if it's solvable, if not, continue to the next combination. Do you guys understand? Is there a better way?
Currently I have a for-loop with a BigInteger, adding 1 every iteration, and testing to see if the resulting number has a number of bits on equal to 55. But this takes LOOOOOONG time. I don't think there's enough time in the universe to do it this way.
LOOP: for(BigInteger big = new BigInteger("36028797018963967");
big.compareTo(new BigInteger("2417851639229258349412351")) < 0;
big = big.add(big.ONE))
{
int count = 0;
for(int i = 0; i < 81; i++)
{
if(big.testBit(i)) count++;
if(count > 55) continue LOOP;
}
//just printing first, no arraylist yet
if(count == 55) System.out.println(big.toString(2));
}

As you already noticed, storing all combinations in a list and then shuffling them is not a viable option.
Instead, you can obtain a shuffled stream of all combinations, by using the Streamplify library.
import org.beryx.streamplify.combination.Combinations;
...
SudokuGrid grid = new SudokuGrid();
int[] solvedPuzzle = IntStream.range(0, 81).map(i -> grid.get(i)).toArray();
int k = 55;
new Combinations(81, k)
.shuffle()
.parallelStream()
.map(removals -> {
int[] puzzle = new int[81];
System.arraycopy(solvedPuzzle, 0, puzzle, 0, 81);
for(int i : removals) {
puzzle[i] = 0;
}
return puzzle;
})
.filter(puzzle -> resolveGrid(new SudokuSolver(new Candidates(puzzle))))
//.limit(10)
.forEach(puzzle -> System.out.println(Arrays.toString(puzzle)));
You probably don't want to generate all puzzles of a given difficulty, but only a few of them.
You can achieve this by putting a limit (see the commented line in the above code).

Certainly there are methods that will finish before you die of old age. For example:
Make an array (or BitSet, as David Choweller suggested in the comments) to represent the bits, and turn on as many as you need until you have enough. Then convert that back into a BigInteger.

I appreciate any feedback. The following seems to be a better option than my initial idea, since I believe having a list of all possible combinations would definitely give an out of memory error. It's not perfect, but this option takes out a random cell, tests to see if its solvable, if not put the last taken number back, and continue to remove the next random cell until enough cells have been taken out, or start over.
int[] candidates = new int[81];
SudokuGrid grid = new SudokuGrid();
LOOP: while(true)
{
ArrayList<Integer> removals = new ArrayList<Integer>();
for(int i = 0; i < 81; i++)
{
removals.add(i);
candidates[i] = grid.get(i);
}
Collections.shuffle(removals);
int k = 55;
for(int i = 0; i < k; i++)
{
int num = candidates[removals.get(i)];
candidates[removals.get(i)] = 0;
cand = new Candidates(candidates);
SudokuSolver solver = new SudokuSolver(cand);
if(!resolveGrid(solver))
{
candidates[removals.get(i)] = num;
k++;
if(k > removals.size())
continue LOOP;
}
}
break;
}
This takes about 5 seconds to solve. It's a bit slower than I wanted it to be, but a lot of it depends on the way I coded the solving strategies.

How would you find how many times one array is repeated in another one?

For example, if you were given {1,2} as the small array and {1,2,3,4,1,2,1,3} as the big one, then it would return 2.
This is probably horribly incorrect:
public static int timesOccur(int[] small, int big[]) {
int sum= 0;
for (int i=0; i<small.length; i++){
int currentSum = 0;
for (int j=0; j<big.length; j++){
if (small[i] == big[j]){
currentSum ++;
}
sum= currentSum ;
}
}
return sum;
}

As #AndyTurner mentioned, your task can be reduced to the set of well-known string matching algorithms.
As I can understand you want solution faster than O(n * m).
There are two main approaches. First involves preprocessing text (long array), second involves preprocessing search pattern (small array).
Preprocessing text. By this I mean creating suffix array or LCP from your longer array. Having this data structure constructed you can perform a binary search to find your your substring. The most efficient time you can achieve is O(n) to build LCP and O(m + log n) to perform the search. So overall time is O(n + m).
Preprocessing pattern. This means construction DFA from the pattern. Having DFA constructed it takes one traversal of the string (long array) to find all occurrences of substring (linear time). The hardest part here is to construct the DFA. Knuth-Morris-Pratt does this in O(m) time, so overall algorithm running time will be O(m + n). Actually KMP algorithm is most probably the best available solution for this task in terms of efficiency and implementation complexity. Check #JuanLopes's answer for concrete implementation.
Also you can consider optimized bruteforce, for example Boyer-Moore, it is good for practical cases, but it has O(n * m) running time in worst case.
UPD:
In case you don't need fast approaches, I corrected your code from description:
public static int timesOccur(int[] small, int big[]) {
int sum = 0;
for (int i = 0; i < big.length - small.length + 1; i++) {
int j = 0;
while (j < small.length && small[j] == big[i + j]) {
j++;
}
if (j == small.length) {
sum++;
}
}
return sum;
}
Pay attention on the inner while loop. It stops as soon as elements don't match. It's important optimization, as it makes running time almost linear for best cases.
upd2: inner loop explanation.
The purpose of inner loop is to find out if smaller array matches bigger array starting from position i. To perform that check index j is iterated from 0 to length of smaller array, comparing the element j of the smaller array with the corresponding element i + j of the bigger array. Loop proceeds when both conditions are true at the same time: j < small.length and corresponding elements of two arrays match.
So loop stops in two situations:
j < small.length is false. This means that j==small.length. Also it means that for all j=0..small.length-1 elements of the two arrays matched (otherwise loop would break earlier, see (2) below).
small[j] == big[i + j] is false. This means that match was not found. In this case loop will break before j reaches small.length
After the loop it's sufficient to check whether j==small.length to know which condition made loop to stop and hence know whether match was found or not for current position i.

This is a simple subarray matching problem. In Java you can use Collections.indexOfSublist, but you would have to box all the integers in your array. An option is to implement your own array matching algorithm. There are several options, most string searching algorithms can be adapted to this task.
Here is an optimized version based on the KMP algorithm. In the worst case it will be O(n + m), which is better than the trivial algorithm. But it has the downside of requiring extra space to compute the failure function (F).
public class Main {
public static class KMP {
private final int F[];
private final int[] needle;
public KMP(int[] needle) {
this.needle = needle;
this.F = new int[needle.length + 1];
F[0] = 0;
F[1] = 0;
int i = 1, j = 0;
while (i < needle.length) {
if (needle[i] == needle[j])
F[++i] = ++j;
else if (j == 0)
F[++i] = 0;
else
j = F[j];
}
}
public int countAt(int[] haystack) {
int count = 0;
int i = 0, j = 0;
int n = haystack.length, m = needle.length;
while (i - j <= n - m) {
while (j < m) {
if (needle[j] == haystack[i]) {
i++;
j++;
} else break;
}
if (j == m) count++;
else if (j == 0) i++;
j = F[j];
}
return count;
}
}
public static void main(String[] args) {
System.out.println(new KMP(new int[]{1, 2}).countAt(new int[]{1, 2, 3, 4, 1, 2, 1, 3}));
System.out.println(new KMP(new int[]{1, 1}).countAt(new int[]{1, 1, 1}));
}
}

Rather than posting a solution I'll provide some hints to get your moving.
It's worth breaking the problem down into smaller pieces, in general your algorithm should look like:
for each position in the big array
check if the small array matches that position
if it does, increment your counter
The smaller piece is then checking if the small array matches a given position
first check if there's enough room to fit the smaller array
if not then the arrays don't match
otherwise for each position in the smaller array
check if the values in the arrays match
if not then the arrays don't match
if you get to the end of the smaller array and they have all matched
then the arrays match

Though not thoroughly tested I believe this is a solution to your problem. I would highly recommend using Sprinters pseudocode to try and figure this out yourself before using this.
public static void main(String[] args)
{
int[] smallArray = {1,1};
int[] bigArray = {1,1,1};
int sum = 0;
for(int i = 0; i < bigArray.length; i++)
{
boolean flag = true;
if(bigArray[i] == smallArray[0])
{
for(int x = 0; x < smallArray.length; x++)
{
if(i + x >= bigArray.length)
flag = false;
else if(bigArray[i + x] != smallArray[x])
flag = false;
}
if(flag)
sum += 1;
}
}
System.out.println(sum);
}
}

finding the number of pairs of numbers in an array that add up to a number

I am trying to come up with a program that will search inside of an array that is given a length by the user that picks out whether there is a pair of numbers that sum to 7. The idea is that if there is k amount of dice being thrown, how many pairs of numbers out of those dice thrown add up to 7. So far this is all that I could come up with but I am very stuck.
This is the driver class for the program. I have to write a class that will make this driver function properly.
import java.util.Scanner;
public class SevenDriver{
public static void main(String[] args){
System.out.println("Enter number of dice to toss");
Scanner s = new Scanner(System.in);
int diceCount = s.nextInt();
SevenTally t = new SevenTally(diceCount);
int experiments = 1000000;
int wins = 0;
for(int j = 0; j < experiments; j++)
if(t.experiment()) wins++;
System.out.println((double)wins/experiments);
}
}
This is what I have so far. It does not currently work or compile. I am just looking for some ideas to get me going. Thanks!
public class SevenTally{
private int diceCount;
public SevenTally(int die){
diceCount = die;
}
public int genDice(){
return 1 + (int)(Math.random()*6);
}
public boolean experiment(){
boolean[] nums = new boolean[diceCount];
int ranNum;
int sum = 7;
for(int i = 0; i < nums.length; i++){
ranNum = genDice();
if (nums[ranNum] == sum){
return true;
}
}
int left = 0;
int right = nums.length - 1;
while(left<right){
int tempSum = nums[left] + nums[right];
if(tempSum == 7){
return true;
}
else if(tempSum>7){
right--;
}
return false;
}
}

First populate your array of length k with random int in [1;6]
The number of possible pairs in an array of length k is the number of 2-combinations in the array, which is (k-1)*k/2 (http://en.wikipedia.org/wiki/Combination)
You can test all the possible pairs (i,j) in your array like so:
int win = 0;
int tally = 7;
for(int i=0; i<k-1; i++){
for(int j=i+1; j<k; j++){
if(array[i]+array[j] == tally){
win++;
}
}
}
What this does is that it sets the first element of the pair to be the first element of the array, and sums it with the other elements one after the other.
It pairs array[0] with array[1] to array[k-1] at the first pass of the i for loop, that's k pairs.
Then k-1 pairs at second pass, and so on.
You end up with (k)+(k-1)+(k-2)+...+1 pairs, and that's exactly (k-1)*k/2 pairs.
done =]
edit: sorry, haven't read the whole thing. the method experiment() is supposed to return a boolean. you can return win>0?true:false; for example...

This Wiki page has some algorithms to do that. Its not a trivial problem...

You're generating a random number in ranNum, and then using it as an index into the array nums. Meanwhile, nums never gets filled, so no matter which box you index into, it never contains a 7.
What you want to do, if I understand your problem correctly, is fill each space in the array with the result of a die roll, then compare every two positions (rolls) to see if they sum to seven. You can do that using a nested for loop.
Essentially, you want to do this: (written in pseudocode as I'm not a java programmer)
int[] results[numrolls]
for (count = 0 to numrolls-1) { results[numrolls]=dieRoller() }
for (outer = 0 to numrolls-2)
for (inner = outer+1 to numrolls-1)
if (results[outer] + results[inner] == 7) return true
return false;
However, in this case there's an even easier way. You know that the only ways to get a sum of 7 on 2d6 are (1,6),(2,5),(3,4),(4,3),(5,2),(6,1). Set up a 6-length boolean array, roll your dice, and after each roll set res[result] to true. Then return (1-based array used for simplicity) ( (res[1] && res[6]) || (res[2] && res[5]) || (res[3] && res[4]) ).

ArrayIndexOutOfBoundsException means you are trying to access an element of the array that hasn't been allocated.
In your code, you create a new array d of length diceCount, but then you genDice() on always 6 elements.