Turn a recursive method into an iterative method - java

I have to create two methods that do the same thing. The methods have to calculate the L(n) of the numbers from 0 - 30 where L(n) is defined as
L(0) = 1
L(1) = 1
L(n) = L(n - 1) + L(n - 2) + 1;
when n > 1
The first method has to be written using recursion which I successfully did and the second one has to be made using iteration ( arrays and for loops )
First method)
public static int rec(int x) {
if (x == 0) return 1;
if (x == 1) return 1;
else return rec(x - 1) + rec(x - 2) + 1;
}
and i added this in main for the first method
int x = 0;
while (x <= 30) {
System.out.println(rec(x));
x++;
}
and this is all i have been able to do with the second method , while i know it is wrong , bare in mind im a beginner , be gentle
Second method)
public static long iter(long [] x){
long result = 0 ;
int length = x.length;
for ( int i = 0 ; i < length ; i++){
if ( i == 0 ) result = 1;
if ( i == 1 ) result = 1;
else result += x[i-1]+x[i-2]+1;
}
return result ;
}


Think about what your code here is doing -
for ( int i = 0 ; i < x.length ; i++){
long returnvalue = x[i-1]+x[i-2]+1; // every iteration you are resetting returnvalue.
}
In every iteration you are creating a new variable and then losing what you have just computed.
You need to add this result from each iteration so you will have to do this -
for ( int i = 0 ; i < x.length ; i++){
returnvalue = returnvalue + x[i-1]+x[i-2]+1;
}
Or you can also do this -
returnvalue += x[i-1]+x[i-2]+1;
Notice that in the iterative version returnValue is defined only once before your loop starts.


How about treating L as an array, then performing the following assignments:
L(0) = 1
L(1) = 1
For the 3rd step, you will have to write a loop calculating and storing the values of L[2] to L[30]. At each iteration of the loop, the previous 2 values will already be in L, so you can just use them.


You are very close - you need to hold a history in your iterating solution:
public static long iter(long x) {
long result = 0;
// Make a 2-length array for my history.
long[] history = new long[2];
for (int i = 0; i <= x; i++) {
if (i < 2) {
result = 1;
} else {
result = history[0] + history[1] + 1;
}
// Maintain my history.
history[0] = history[1];
history[1] = result;
}
return result;
}


So I was able to finally solve it : ( Thanks for all the help , really really appreciate it )
public class Aufgabe1 {
// invokes iter as well as rec with all integers from 0 to 30 and prints the results
// (without empty lines or other output)
public static void main(String[] args) {
// TODO: Implementation is your task
int x = 0;
while (x <= 30) {
System.out.println(rec(x));
x++;
}
long [] longArr = new long[31];
iter(longArr);
}
public static int rec(int x) {
if (x == 0) return 1;
if (x == 1) return 1;
else return rec(x - 1) + rec(x - 2) + 1;
}
public static void iter(long[] n) {
for (int i = 0; i < n.length; i++) {
if (i == 0 || i == 1) {
n[i] = 1;
} else {
n[i] = n[i - 1] + n[i - 2] + 1;
}
System.out.println(n[i]);
}
}
}

Related

how to determine if a number is a smart number in java?

I have this question I am trying to solve. I have tried coding for the past 4 hours.
An integer is defined to be a Smart number if it is an element in the infinite sequence
1, 2, 4, 7, 11, 16 …
Note that 2-1=1, 4-2=2, 7-4=3, 11-7=4, 16-11=5 so for k>1, the kth element of the sequence is equal to the k-1th element + k-1. For example, for k=6, 16 is the kth element and is equal to 11 (the k-1th element) + 5 ( k-1).
Write function named isSmart that returns 1 if its argument is a Smart number, otherwise it returns 0. So isSmart(11) returns 1, isSmart(22) returns 1 and isSmart(8) returns 0
I have tried the following code to
import java.util.Arrays;
public class IsSmart {
public static void main(String[] args) {
// TODO Auto-generated method stub
int x = isSmart(11);
System.out.println(x);
}
public static int isSmart(int n) {
int[] y = new int[n];
int j = 0;
for (int i = 1; i <= n; i++) {
y[j] = i;
j++;
}
System.out.println(Arrays.toString(y));
for (int i = 0; i <= y.length; i++) {
int diff = 0;
y[j] = y[i+1] - y[i] ;
y[i] = diff;
}
System.out.println(Arrays.toString(y));
for (int i = 0; i < y.length; i++) {
if(n == y[i])
return 1;
}
return 0;
}
}
When I test it with 11 it is giving me 0 but it shouldn't. Any idea how to correct my mistakes?

It can be done in a simpler way as follows
import java.util.Arrays;
public class IsSmart {
public static void main(String[] args) {
int x = isSmart(11);
System.out.println("Ans: "+x);
}
public static int isSmart(int n) {
//------------ CHECK THIS LOGIC ------------//
int[] y = new int[n];
int diff = 1;
for (int i = 1; i < n; i++) {
y[0] =1;
y[i] = diff + y[i-1];
diff++;
}
//------------ CHECK THIS LOGIC ------------//
System.out.println(Arrays.toString(y));
for (int i = 0; i < y.length; i++) {
if(n == y[i])
return 1;
}
return 0;
}
}

One of the problems is the way that your populating your array.
The array can be populated as such
for(int i = 0; i < n; i++) {
y[i] = (i == 0) ? 1 : y[i - 1] + i;
}
The overall application of the function isSmart can be simplified to:
public static int isSmart(int n) {
int[] array = new int[n];
for(int i = 0; i < n; i++) {
array[i] = (i == 0) ? 1 : array[i - 1] + i;
}
for (int i = 0; i < array.length; i++) {
if (array[i] == n) return 1;
}
return 0;
}

Note that you don't need to build an array:
public static int isSmart(int n) {
int smart = 1;
for (int i = 1; smart < n; i++) {
smart = smart + i;
}
return smart == n ? 1 : 0;
}

Here is a naive way to think of it to get you started - you need to fill out the while() loop. The important thing to notice is that:
The next value of the sequence will be the number of items in the sequence + the last item in the sequence.
import java.util.ArrayList;
public class Test {
public static void main(String[] args) {
System.out.println(isSmart(11));
}
public static int isSmart(int n) {
ArrayList<Integer> sequence = new ArrayList<Integer>();
// Start with 1 in the ArrayList
sequence.add(1);
// You need to keep track of the index, as well as
// the next value you're going to add to your list
int index = 1; // or number of elements in the sequence
int nextVal = 1;
while (nextVal < n) {
// Three things need to happen in here:
// 1) set nextVal equal to the sum of the current index + the value at the *previous* index
// 2) add nextVal to the ArrayList
// 3) incriment index by 1
}
// Now you can check to see if your ArrayList contains n (is Smart)
if (sequence.contains(n)) { return 1; }
return 0;
}
}

First think of a mathematical solution.
Smart numbers form a sequence:
a0 = 1
an+1 = n + an
This gives a function for smart numbers:
f(x) = ax² + bx + c
f(x + 1) = f(x) + x = ...
So the problem is to find for a given y a matching x.
You can do this by a binary search.
int isSmart(int n) {
int xlow = 1;
int xhigh = n; // Exclusive. For n == 0 return 1.
while (xlow < xhigh) {
int x = (xlow + xhigh)/2;
int y = f(x);
if (y == n) {
return 1;
}
if (y < n) {
xlow = x + 1;
} else {
xhigh = x;
}
}
return 0;
}
Yet smarter would be to use the solution for x and look whether it is an integer:
ax² + bx + c' = 0 where c' = c - n
x = ...

I was playing around with this and I noticed something. The smart numbers are
1 2 4 7 11 16 22 29 ...
If you subtract one you get
0 1 3 6 10 15 21 28 ...
0 1 2 3 4 5 6 7 ...
The above sequence happens to be the sum of the first n numbers starting with 0 which is n*(n+1)/2. So add 1 to that and you get a smart number.
Since n and n+1 are next door to each other you can derive them by reversing the process.
Take 29, subtract 1 = 28, * 2 = 56. The sqrt(56) rounded up is 8. So the 8th smart number (counting from 0) is 29.
Using that information you can detect a smart number without a loop by simply reversing the process.
public static int isSmart(int v) {
int vv = (v-1)*2;
int sq = (int)Math.sqrt(vv);
int chk = (sq*(sq+1))/2 + 1;
return (chk == v) ? 1 : 0;
}
Using a version which supports longs have verified this against the iterative process from 1 to 10,000,000,000.

Java Large Number Operations Shortest Path to One

A week ago I was given a challenge from my professor to make a program that has three operations for large numbers, given as as strings. I could only pass five of the ten test cases and got an A anyway, but I still want to know what you guys would do for this problem, as far as programming techniques or an approach I didn't think of..
You are given a String representation of a number that is up to 309 digits long. You can preform three operations:
1) Add 1 to the number
2) Subtract 1
3) Divide by 2
the purpose of the program is to find the shortest path, or smallest amount of operations that can be performed on this number so that the result is 1.
ex: given "11"
1 -> 2 -> 3 -> 6 -> 12 -> 11
result: 5 steps
I had two approaches that didn't work 100%:
1: start from one or the number itself and recursively step through each possible answer until number is reached within a maximum number of steps (eg. 11, 20).
2: define all possible answers with the help of a 2-d boolean array with all possible permutaions, then step through the possible movesets one by one. this array works as a map conceptually.
Both of these approaches had limited success, wether i encountered a stackoverflow error or just ran out of memory with my large arrays. This forced me to limit the number of steps so the code could function somewhat successfully. What would be your approach?
EDIT 1:30pm
attempt 1(sorry, it has been edited severely, hence why it wasn't shown earlier...):
import java.math.BigInteger;
import java.util.Scanner;
public class Answer {
public static void main(String[] args) {
// TODO Auto-generated method stub
String str;
Scanner sc = new Scanner(System.in);
while (true) {
str = sc.nextLine();
System.out.println(answer(str));
}
// System.out.println(answer("15"));
}
private static BigInteger minNumOfJumps;
private static BigInteger big2 = BigInteger.valueOf(2);
/** smallest Number of jumps reached so far */
private static BigInteger smallestAmountOfJumps;
public static int answer(String string) {
// TODO Auto-generated method stub
BigInteger src = new BigInteger(string);
// BigInteger currentJump = BigInteger.ZERO; //used to initialize the
// nodes
// minNumOfJumps = src.divide(big2).add(BigInteger.ONE); //this must
// execute...
minNumOfJumps = new BigInteger("14"); // this must execute...
smallestAmountOfJumps = new BigInteger(minNumOfJumps.toString());
// System.out.println(minNumOfJumps);
Node n = new Node(src); // ...before this
return Integer.parseInt(getSmallestAmountOfJumps().toString());
// System.out.println(n.getSmallestAmountOfJumps().toString());
}
public static BigInteger getBig2() {
return big2;
}
public static void setBig2(BigInteger big2) {
Answer.big2 = big2;
}
public static BigInteger getMinNumOfJumps() {
return minNumOfJumps;
}
public static BigInteger getSmallestAmountOfJumps() {
return smallestAmountOfJumps;
}
public static void setSmallestAmountOfJumps(String smallestAmountOfJumps) {
Answer.smallestAmountOfJumps = new BigInteger(smallestAmountOfJumps);
}
}
/*
* I have never made a shortest path algorithm before, so i hope this is toyour
* satisfaction
*/
class Node {
/** number of nodes per creation */
private static final int NUMBER_OF_NODES_PER_NODE = 3;
/** if this number is exceeded, no more jumps are necessary. */ // SAVE THAT
// THINKING
// JUICE!
// private static BigInteger POSSIBLE_MINIMUM_NUMBER_OF_JUMPS;
private static boolean lastTransformWasRemoveOne;
private static boolean lastTransformWasAddOne;
// if one is the given value(src)
// private boolean isOneReached;
/** if the current path isn't valid */
// private boolean threadIsBroken;
// value passed during creation
private BigInteger src;
// current jump
private BigInteger currentJump;
// all possible transformations during next jump
// private Node[] path;
private Node(BigInteger src, BigInteger jump) {
currentJump = jump;
this.src = src;
// POSSIBLE_MINIMUM_NUMBER_OF_JUMPS = Answer.getMinNumOfJumps();
// this.path = new Node[NUMBER_OF_NODES_PER_NODE];
// 0 = remove | 1 = add | 2 = divide
for (int i = 0; i < NUMBER_OF_NODES_PER_NODE; i++) {
// System.out.println("i: " + i);
// System.out.println("src: " + src);
// System.out.println("compare: " +
// currentJump.compareTo(smallestAmountOfJumps));
// System.out.println("currentJump: " + currentJump);
// System.out.println("smallestAmountOfJumps: " +
// smallestAmountOfJumps);
if (src.compareTo(BigInteger.ONE) == 0) {
if (currentJump.subtract(Answer.getSmallestAmountOfJumps()).compareTo(BigInteger.ZERO) == -1) {
Answer.setSmallestAmountOfJumps(currentJump.toString());
// this below may break the code, but i think it fits with
// the logic
break;
}
} else if (i == 0) { // remove 1
// System.out.println(lastTransformWasAddOne);
// System.out.println("compare: " +
// currentJump.compareTo(smallestAmountOfJumps));
// System.out.println("currentJump: " + currentJump);
// System.out.println("smallestAmountOfJumps: " +
// smallestAmountOfJumps);
if (!lastTransformWasAddOne && currentJump.compareTo(Answer.getSmallestAmountOfJumps()) < 0) {
lastTransformWasRemoveOne = true;
Node n = new Node(transform(i), currentJump.add(BigInteger.ONE));
}
} else if (i == 1 && !lastTransformWasRemoveOne
&& currentJump.compareTo(Answer.getSmallestAmountOfJumps()) < 0) { // add
// 1
lastTransformWasAddOne = true;
Node n = new Node(transform(i), currentJump.add(BigInteger.ONE));
} else if (src.mod(Answer.getBig2()) == BigInteger.ZERO
&& currentJump.compareTo(Answer.getSmallestAmountOfJumps()) < 0) { // divide
// by
// 2
lastTransformWasRemoveOne = false;
lastTransformWasAddOne = false;
Node n = new Node(transform(i), currentJump.add(BigInteger.ONE));
} else if (currentJump.compareTo(Answer.getSmallestAmountOfJumps()) == 0)
break;
}
}
private BigInteger transform(int i) {
// TODO Auto-generated method stub
return (i == 0) ? src.subtract(BigInteger.ONE)
: (i == 1) ? src.add(BigInteger.ONE) : (i == 2) ? src.divide(Answer.getBig2()) : BigInteger.ZERO;
}
/**
* To be called once and only once.
*/
public Node(BigInteger src) {
this(src, BigInteger.ZERO);
}
}`
and this is another attempt:
import java.math.BigInteger;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.HashSet;
import java.util.Scanner;
import java.util.Set;
public class AnswerLessProficient {
public static void main(String[] args) {
// TODO Auto-generated method stub
String str;
Scanner sc = new Scanner(System.in);
while (true) {
str = sc.nextLine();
System.out.println(answer(str));
}
// System.out.println(answer("15"));
}
private static boolean notFirstCall;
private static boolean pathIsSet;
private static boolean[][] boolArray;
private static final String ZERO = "0";
private static final BigInteger TWO = BigInteger.ONE.add(BigInteger.ONE);
private static int maximumSteps;
private static int maximumPermutations;
private static ArrayList<byte[]> listOfPaths;
private static Set<byte[]> setOfPaths;
// private static final int maximumPermutations = halfMaximumPermutations *
// 2;
// private static byte[][] path;
private static BigInteger src;
private static int steps;
private static BigInteger tempSrc;
private static byte[] tempPath;
// private static boolean followThePathsWithAlternateRoutesWasCalledOnce;
public static int answer(String s) {
// listOfPaths = new ArrayList<>();
src = new BigInteger(s);
tempSrc = new BigInteger(s);
maximumSteps = 9;
steps = maximumSteps;
maximumPermutations = (int) Math.pow(2, maximumSteps);
if (!notFirstCall) {
tempPath = new byte[maximumSteps];
setOfPaths = new HashSet<>();
int mercyVar = (int) Math.pow(2, maximumSteps);
// path = new byte[maximumPermutations][maximumSteps];
// boolArray = new boolean[maximumPermutations][maximumSteps];
for (int i = 0; i < mercyVar; i++) {
listOfPaths = new ArrayList<>();
String bin = (Integer.toBinaryString(i));
while (bin.length() < maximumSteps)
bin = (ZERO + bin);
char[] chars = bin.toString().toCharArray();
byte[] tempPath = new byte[maximumSteps];
for (int j = 0; j < maximumSteps; j++) {
// if (!pathIsSet)
// path[j] = -1;
if (chars[j] == '0') {
tempPath[j] = 2;
// path[i][j] = 2;
// boolArray[i][j] = true;
} else {
tempPath[j] = -1;
// path[i][j] = -1;
}
}
//System.out.println(Arrays.toString(tempPath));
listOfPaths.add(tempPath);
setOfPaths.add(tempPath);
findAltRoute(listOfPaths.size() - 1, maximumSteps - 1);
}
/*
* for (int i = mercyVar, j = 0; i < maximumPermutations; i++, j++)
* { for (int k = 0; k < maximumSteps; k++) { if (path[j][k] == -1)
* { path[i][k] = 1; } else { path[i][k] = 2; } } }
*/
// for (byte[] bs : setOfPaths) {
// System.out.println(Arrays.toString(bs));
// }
/*
* for (int i = maximumSteps - 1, k = 0; i >= 0 &&
* tempSrc.compareTo(BigInteger.ZERO) > 0; i--, k++) { if
* (tempSrc.compareTo(BigInteger.ONE) <= 0) if (k < steps) { steps =
* k; maximumSteps = steps; System.out.println(Arrays.toString(bs));
* break; } else break; if (bs[i] == 2 && tempSrc.mod(TWO) !=
* BigInteger.ZERO) break; tempSrc = transform(tempSrc, bs[i]); }
* tempSrc = src.add(BigInteger.ZERO);
*/
// }
// System.out.println(bin);
/*
* for (int j = 0; j < maximumSteps && i >= halfMaximumPermutations;
* j++) { // if (!pathIsSet) // path[j] = -1; if (chars[j + 1] ==
* '0') { path[i][j] = 2; // boolArray[i][j] = true; } else {
* path[i][j] = 1; } }
*/
// System.out.println(bin);
// System.out.println(Arrays.toString(path[i]));
// pathIsSet = true;
notFirstCall = true;
}
justFollowThePath();
// System.out.println(Arrays.toString(path[0]));
// System.out.println
// (Arrays.toString(path[(int) (maximumPermutations/2)-1]));
// System.out.println(Arrays.toString(path[maximumPermutations-1]));
/**
* 561-508-2204 george rubio debt forgiveness; 305-709-8255
*/
// for (int i = 0; i < maximumPermutations; i++) {
// followThePathsWithAlternateRoutes(path[i], maximumSteps - 1);
// }
// followThePathsWithAlternateRoutesWasCalledOnce = false;
/*
* for (int i = 0; i < maximumPermutations; i++) { for (int k = 0; k <
* maximumSteps; k++) {
*
* }
*
* for (int k = maximumSteps - 1; k > 0; k--) {
*
* } }
*/
// for (boolean[] bs : boolArray) {
// System.out.println(Arrays.toString(bs));
// }
// System.out.println(Arrays.toString(boolArray[maximumPermutations -
// 1]));
// System.out.println(Arrays.toString(path));
return steps;
}
private static void findAltRoute(int listIndex, int startingSearchIndex) {
if (listOfPaths.get(listIndex)[startingSearchIndex] == -1) {
// followThePathsWithAlternateRoutesWasCalledOnce = true;
// recurAlt(tempPath, maximumSteps - 1, maximumSteps - 1, (byte) 1,
// maximumSteps - 1);
for (int i = startingSearchIndex - 1; i >= 0; i--) {
if (listOfPaths.get(listIndex)[i] == 2) {
returnAltRoute(listIndex, i + 1, startingSearchIndex, (byte) 1, i);
findAltRoute(listIndex + 1, i);
return;
}
else if (i == 0) {
returnAltRoute(listIndex, i, startingSearchIndex, (byte) 1);
return;
}
}
}
for (int i = startingSearchIndex - 1; i >= 0; i--) {
if (listOfPaths.get(listIndex)[i] == -1 && listOfPaths.get(listIndex)[i + 1] == 2) {
if (i != 0) {
for (int k = i - 1; k >= 0; k--) {
if (listOfPaths.get(listIndex)[k] == 2 && listOfPaths.get(listIndex)[k + 1] == -1) {
// recurAlt(tempPath, i, k + 1, (byte) 1, k);
returnAltRoute(listIndex, k + 1, i, (byte) 1, k);
findAltRoute(listIndex, i);
}
// returnAltRoute(listIndex, 0, i, (byte)1);
// return;
}
} else {
returnAltRoute(listIndex, 0, i, (byte) 1);
return;
}
}
}
}
private static void returnAltRoute(int listIndex, int tempStart, int tempEnd, byte adjust, int returnSearchInt) {
byte[] tempPath = new byte[listOfPaths.get(listIndex).length];
for (int i = maximumSteps - 1; i >= 0; i--) {
if (i >= tempStart && i <= tempEnd) {
tempPath[i] = adjust;
} else {
tempPath[i] = listOfPaths.get(listIndex)[i];
}
}
System.out.println(Arrays.toString(tempPath));
setOfPaths.add(tempPath);
listOfPaths.add(tempPath);
maximumPermutations = setOfPaths.size();
findAltRoute(listIndex, returnSearchInt);
}
private static void returnAltRoute(int listIndex, int tempStart, int tempEnd, byte adjust) {
byte[] tempPath = new byte[listOfPaths.get(listIndex).length];
for (int i = maximumSteps - 1; i >= 0; i--) {
if (i >= tempStart && i <= tempEnd) {
tempPath[i] = adjust;
} else {
tempPath[i] = listOfPaths.get(listIndex)[i];
}
}
System.out.println(Arrays.toString(tempPath));
setOfPaths.add(tempPath);
listOfPaths.add(tempPath);
maximumPermutations = setOfPaths.size();
}
private static void justFollowThePath() {
for (byte[] bs : setOfPaths) {
//System.out.println(tempSrc.toString());
for (int i = 0; i < maximumSteps && tempSrc.compareTo(BigInteger.ZERO) > 0; i++) {
if (tempSrc.compareTo(BigInteger.ONE) == 0)
if (i < steps) {
steps = i;
maximumSteps = steps;
//System.out.println(i);
// System.out.println(Arrays.toString(tempPath));
break;
} else
break;
if (bs[i] == 2 && tempSrc.mod(TWO) != BigInteger.ZERO)
break;
tempSrc = transform(tempSrc, bs[i]);
}
tempSrc = src.add(BigInteger.ZERO);
}
}
private static void followThePathsWithAlternateRoutes(byte[] tempPath, int startingSearchIndex) {
if (tempPath[maximumSteps - 1] == -1) {
// followThePathsWithAlternateRoutesWasCalledOnce = true;
recurAlt(tempPath, maximumSteps - 1, maximumSteps - 1, (byte) 1, maximumSteps - 1);
}
for (int i = startingSearchIndex - 1; i >= 0; i--) {
if (tempPath[i] == -1 && tempPath[i + 1] == 2) {
for (int k = i - 1; k > 0; k--) {
if (tempPath[k] == 2) {
recurAlt(tempPath, i, k + 1, (byte) 1, k);
}
}
}
}
System.out.println();
for (int i = maximumSteps - 1, k = 0; i >= 0 && tempSrc.compareTo(BigInteger.ZERO) > 0; i--, k++) {
if (tempSrc.compareTo(BigInteger.ONE) <= 0)
if (k < steps) {
steps = k;
maximumSteps = steps;
System.out.println(Arrays.toString(tempPath));
break;
} else
break;
if (tempPath[i] == 2 && tempSrc.mod(TWO) != BigInteger.ZERO)
break;
tempSrc = transform(tempSrc, tempPath[i]);
}
tempSrc = src.add(BigInteger.ZERO);
}
private static BigInteger transform(BigInteger temp, byte i) {
// TODO Auto-generated method stub
return (i == -1) ? tempSrc.subtract(BigInteger.ONE)
: (i == 1) ? tempSrc.add(BigInteger.ONE) : (i == 2) ? tempSrc.divide(TWO) : null;
}
private static void recurAlt(byte[] tempPath, int tempStart, int tempEnd, byte adjust, int returnSearchInt) {
// TODO Auto-generated method stub
byte[] temp = new byte[tempPath.length];
for (int i = 0; i < temp.length; i++) {
if (i >= tempStart && i <= tempEnd)
temp[i] = adjust;
else
temp[i] = tempPath[i];
}
followThePathsWithAlternateRoutes(temp, returnSearchInt);
}
}
there are other things i've tried, but you can see where i'm going. Any pointers?

If the number is even, divide by 2. If the number is 3 mod 4, add one unless the number is actually 3. Otherwise, subtract one. Repeat until you get to 1.
Here's a proof.
First note that if the number is even, it only makes sense to divide by 2. Because if you perform some number (say 2k) of +1 or -1, then divide by 2 that's the same as dividing by two and then adding or subtracting k 1's. So by dividing by two first, you save operations.
So the only question is whether to add or subtract 1 when the number is odd. You can prove by induction that the given strategy is correct.
An odd number n is either 4x+1 or 4x+3. Note that any sequence of operations (when we're dividing by 2 whenever possible) will at some point reach either x or x+1.
We'll consider each of these in turn, and count shortest paths to x and x+1. (Checking that I've correctly identified shortest paths is omitted).
In the first case (4x+1), by subtracting one first we can get to x in 3 steps (4x+1->4x->2x->x) and x+1 in 4 steps (4x+1->4x->2x->x->x+1). By adding one first, we can get to x in 4 steps (4x+1->4x+2->2x+1->2x->x) and x+1 in 4 steps (4x+1->4x+2->2x+1->2x+2->x+1). So we might as well always subtract 1 first.
In the second case (4x+3), by subtracting one first we can get to x in 4 steps (4x+3->4x+2->2x+1->2x->x), and x+1 in 4 steps (4x+3->4x+2->2x+1->2x+2->x+1). By adding one first, we can get to x+1 in 3 steps (4x+3->4x+4->2x+2->x+1), and x in 4 steps (4x+3->4x+4->2x+2->x+1->x). So we might as well always add 1 first in this case.
In the second case, if x=0 (that is n=4*0+3=3), then our reasoning doesn't quite work, since we won't, in fact, reach x. In this case we should subtract one and divide by 2 to reach 1.
The question is labelled java, but here's some pseudocode (actually Python) to produce optimal chains:
def chain(n):
while n:
print n,
if n % 2 == 0:
n //= 2
elif n % 4 == 3 and n != 3:
n += 1
else:
n -= 1
chain(11)

My first approach will be using BFS.
There are only 2 or 3 state transition ( I assume we can't divide odd number).
But this approach only fast enough for small number.
The second approach will be using A* with smallest number as heuristic function. For example when I start with "12", I can go to:
"11", "13", "6". I will choose "6" for the next state because it closer to "1".
However this approach still not fast enough.
My third approach will be generate the answer from "1" to "100" then looking for the pattern / formula.
Edit: remove wrong formula.

Assigning variables instead of direct references inside a loop resulting in different results

So I have been trying for the past 2 hours to figure out why the following two methods are giving different results. Both of them are methods that take an integer array, remove any consecutive duplicates in it and put a "-1" at the end for each duplicate removed.
Method 1 gives correct output, while method 2 turns into an infinite loop.
//Method 1
private static void smoosh1(int[] ints) {
for (int i=0; i<ints.length-1; i++) {
while (ints[i] == ints[i+1] && ints[i] != -1) {
for (int x=i; x<ints.length-1; x++) {
ints[x] = ints[x+1]; }
ints[ints.length-1] = -1;
}
}
}
//Method 2
public static void smoosh(int[] ints) {
for (int i = 0; i < ints.length - 1; i++) {
int curVal=ints[i];
int nextVal=ints[i+1];
while (curVal == nextVal && curVal !=-1) {
for (int x = i; x < ints.length-1; x++) {
ints[x] = ints[x + 1];
}
ints[ints.length-1] = -1;
}
}
Kindly explain to me the reason why declaring the variables inside the loop is affecting the output. Thanks.
Note:- This problem is from Part 1, Homework 3 of MOOC 61B at Berkeley.
Link:- https://people.eecs.berkeley.edu/~jrs/61b/hw/hw3/

In order for the second snippet to behave the same as the first snippet, the while loop must modify the values of curVal and nextVal in each iteration:
public static void smoosh(int[] ints) {
for (int i = 0; i < ints.length - 1; i++) {
int curVal=ints[i];
int nextVal=ints[i+1];
while (curVal == nextVal && curVal !=-1) {
for (int x = i; x < ints.length-1; x++) {
ints[x] = ints[x + 1];
}
ints[ints.length-1] = -1;
curVal=ints[i];
nextVal=ints[i+1];
}
}
}
Otherwise the vaule of the expression curVal == nextVal && curVal !=-1 always remains the same, and the while loop either never executes or never terminates.

One you get in the while loop (consecutive duplicate found in the array) you will never get out, because the curVal and nextVal never change.
I suugest you to write a debug line like this :
//Method 2
public static void smoosh(int[] ints) {
for (int i = 0; i < ints.length - 1; i++) {
int curVal=ints[i];
int nextVal=ints[i+1];
while (curVal == nextVal && curVal !=-1) {
System.out.println(curVal + " "+ nextVal);
for (int x = i; x < ints.length-1; x++) {
ints[x] = ints[x + 1];
}
ints[ints.length-1] = -1;
}
}

NumberOfDiscIntersections overflow in codility test

In the codility test NumberOfDiscIntersections I am getting perf 100% and correctness 87% with the one test failing being
overflow
arithmetic overflow tests
got -1 expected 2
I can't see what is causing that given that I am using long which is 64-bit. And even if I can get it to 100% perf 100% correctness I am wondering if there is a better way to do this that is not as verbose in Java.
edit: figured out a much better way to do with with two arrays rather than a pair class
// you can also use imports, for example:
import java.util.*;
// you can use System.out.println for debugging purposes, e.g.
// System.out.println("this is a debug message");
class Solution {
public int solution(int[] A) {
int j = 0;
Pair[] arr = new Pair[A.length * 2];
for (int i = 0; i < A.length; i++) {
Pair s = new Pair(i - A[i], true);
arr[j] = s;
j++;
Pair e = new Pair(i + A[i], false);
arr[j] = e;
j++;
}
Arrays.sort(arr, new Pair(0, true));
long numIntersect = 0;
long currentCount = 0;
for (Pair p: arr) {
if (p.start) {
numIntersect += currentCount;
if (numIntersect > 10000000) {
return -1;
}
currentCount++;
} else {
currentCount--;
}
}
return (int) numIntersect;
}
static private class Pair implements Comparator<Pair> {
private long x;
private boolean start;
public Pair(long x, boolean start) {
this.x = x;
this.start = start;
}
public int compare(Pair p1, Pair p2) {
if (p1.x < p2.x) {
return -1;
} else if (p1.x > p2.x) {
return 1;
} else {
if (p1.start && p2.start == false) {
return -1;
} else if (p1.start == false && p2.start) {
return 1;
} else {
return 0;
}
}
}
}
}

Look at this line:
Pair s = new Pair(i + A[i], true);
This is equivalent with Pair s = new Pair((long)(i + A[i]) , true);
As i is integer, and A[i] is also integer, so this can cause overflow, as value in A[i] can go up to Integer.MAX_VALUE, and the cast to long happened after add operation is completed.
To fix:
Pair s = new Pair((long)i + (long)A[i], true);
Note: I have submitted with my fixed and got 100%
https://codility.com/demo/results/demoRRBY3Q-UXH/

My todays solution. O(N) time complexity. Simple assumption that number of availble pairs in next point of the table is difference between total open circle to that moment (circle) and circles that have been processed before. Maybe it's to simple :)
public int solution04(int[] A) {
final int N = A.length;
final int M = N + 2;
int[] left = new int[M]; // values of nb of "left" edges of the circles in that point
int[] sleft = new int[M]; // prefix sum of left[]
int il, ir; // index of the "left" and of the "right" edge of the circle
for (int i = 0; i < N; i++) { // counting left edges
il = tl(i, A);
left[il]++;
}
sleft[0] = left[0];
for (int i = 1; i < M; i++) {// counting prefix sums for future use
sleft[i]=sleft[i-1]+left[i];
}
int o, pairs, total_p = 0, total_used=0;
for (int i = 0; i < N; i++) { // counting pairs
ir = tr(i, A, M);
o = sleft[ir]; // nb of open till right edge
pairs = o -1 - total_used;
total_used++;
total_p += pairs;
}
if(total_p > 10000000){
total_p = -1;
}
return total_p;
}
int tl(int i, int[] A){
int tl = i - A[i]; // index of "begin" of the circle
if (tl < 0) {
tl = 0;
} else {
tl = i - A[i] + 1;
}
return tl;
}
int tr(int i, int[] A, int M){
int tr; // index of "end" of the circle
if (Integer.MAX_VALUE - i < A[i] || i + A[i] >= M - 1) {
tr = M - 1;
} else {
tr = i + A[i] + 1;
}
return tr;
}

My take on this, O(n):
public int solution(int[] A) {
int[] startPoints = new int[A.length];
int[] endPoints = new int[A.length];
int tempPoint;
int currOpenCircles = 0;
long pairs = 0;
//sum of starting and end points - how many circles open and close at each index?
for(int i = 0; i < A.length; i++){
tempPoint = i - A[i];
startPoints[tempPoint < 0 ? 0 : tempPoint]++;
tempPoint = i + A[i];
if(A[i] < A.length && tempPoint < A.length) //first prevents int overflow, second chooses correct point
endPoints[tempPoint]++;
}
//find all pairs of new circles (combinations), then make pairs with exiting circles (multiplication)
for(int i = 0; i < A.length; i++){
if(startPoints[i] >= 2)
pairs += (startPoints[i] * (startPoints[i] - 1)) / 2;
pairs += currOpenCircles * startPoints[i];
currOpenCircles += startPoints[i];
currOpenCircles -= endPoints[i];
if(pairs > 10000000)
return -1;
}
return (int) pairs;
}

The explanation to Helsing's solution part:
if(startPoints[i] >= 2) pairs += (startPoints[i] * (startPoints[i] - 1)) / 2;
is based on mathematical combinations formula:
Cn,m = n! / ((n-m)!.m!
for pairs, m=2 then:
Cn,2 = n! / ((n-2)!.2
Equal to:
Cn,2 = n.(n-1).(n-2)! / ((n-2)!.2
By simplification:
Cn,2 = n.(n-1) / 2

Not a very good performance, but using streams.
List<Long> list = IntStream.range(0, A.length).mapToObj(i -> Arrays.asList((long) i - A[i], (long) i + A[i]))
.sorted((o1, o2) -> {
int f = o1.get(0).compareTo(o2.get(0));
return f == 0 ? o1.get(1).compareTo(o2.get(1)) : f;
})
.collect(ArrayList<Long>::new,
(acc, val) -> {
if (acc.isEmpty()) {
acc.add(0l);
acc.add(val.get(1));
} else {
Iterator it = acc.iterator();
it.next();
while (it.hasNext()) {
long el = (long) it.next();
if (val.get(0) <= el) {
long count = acc.get(0);
acc.set(0, ++count);
} else {
it.remove();
}
}
acc.add(val.get(1));
}
},
ArrayList::addAll);
return (int) (list.isEmpty() ? 0 : list.get(0) > 10000000 ? -1 : list.get(0));

This one in Python passed all "Correctness tests" and failed all "Performance tests" due to O(n²), so I got 50% score. But it is very simple to understand. I just used the right radius (maximum) and checked if it was bigger or equal to the left radius (minimum) of the next circles. I also avoided to use sort and did not check twice the same circle. Later I will try to improve performance, but the problem here for me was the algorithm. I tried to find a very easy solution to help explain the concept. Maybe this will help someone.
def solution(A):
n = len(A)
cnt = 0
for j in range(1,n):
for i in range(n-j):
if(i+A[i]>=i+j-A[i+j]):
cnt+=1
if(cnt>1e7):
return -1
return cnt

java codility Frog-River-One

I have been trying to solve a Java exercise on a Codility web page.
Below is the link to the mentioned exercise and my solution.
https://codility.com/demo/results/demoH5GMV3-PV8
Can anyone tell what can I correct in my code in order to improve the score?
Just in case here is the task description:
A small frog wants to get to the other side of a river. The frog is currently located at position 0, and wants to get to position X. Leaves fall from a tree onto the surface of the river.
You are given a non-empty zero-indexed array A consisting of N integers representing the falling leaves. A[K] represents the position where one leaf falls at time K, measured in minutes.
The goal is to find the earliest time when the frog can jump to the other side of the river. The frog can cross only when leaves appear at every position across the river from 1 to X.
For example, you are given integer X = 5 and array A such that:
A[0] = 1
A[1] = 3
A[2] = 1
A[3] = 4
A[4] = 2
A[5] = 3
A[6] = 5
A[7] = 4
In minute 6, a leaf falls into position 5. This is the earliest time when leaves appear in every position across the river.
Write a function:
class Solution { public int solution(int X, int[] A); }
that, given a non-empty zero-indexed array A consisting of N integers and integer X, returns the earliest time when the frog can jump to the other side of the river.
If the frog is never able to jump to the other side of the river, the function should return −1.
For example, given X = 5 and array A such that:
A[0] = 1
A[1] = 3
A[2] = 1
A[3] = 4
A[4] = 2
A[5] = 3
A[6] = 5
A[7] = 4
the function should return 6, as explained above. Assume that:
N and X are integers within the range [1..100,000];
each element of array A is an integer within the range [1..X].
Complexity:
expected worst-case time complexity is O(N);
expected worst-case space complexity is O(X), beyond input storage (not counting the storage required for input arguments).
Elements of input arrays can be modified.
And here is my solution:
import java.util.ArrayList;
import java.util.List;
class Solution {
public int solution(int X, int[] A) {
int list[] = A;
int sum = 0;
int searchedValue = X;
List<Integer> arrayList = new ArrayList<Integer>();
for (int iii = 0; iii < list.length; iii++) {
if (list[iii] <= searchedValue && !arrayList.contains(list[iii])) {
sum += list[iii];
arrayList.add(list[iii]);
}
if (list[iii] == searchedValue) {
if (sum == searchedValue * (searchedValue + 1) / 2) {
return iii;
}
}
}
return -1;
}
}

You are using arrayList.contains inside a loop, which will traverse the whole list unnecessarily.
Here is my solution (I wrote it some time ago, but I believe it scores 100/100):
public int frog(int X, int[] A) {
int steps = X;
boolean[] bitmap = new boolean[steps+1];
for(int i = 0; i < A.length; i++){
if(!bitmap[A[i]]){
bitmap[A[i]] = true;
steps--;
if(steps == 0) return i;
}
}
return -1;
}

Here is my solution. It got me 100/100:
public int solution(int X, int[] A)
{
int[] B = A.Distinct().ToArray();
return (B.Length != X) ? -1 : Array.IndexOf<int>(A, B[B.Length - 1]);
}

100/100
public static int solution (int X, int[] A){
int[]counter = new int[X+1];
int ans = -1;
int x = 0;
for (int i=0; i<A.length; i++){
if (counter[A[i]] == 0){
counter[A[i]] = A[i];
x += 1;
if (x == X){
return i;
}
}
}
return ans;
}

A Java solution using Sets (Collections Framework) Got a 100%
import java.util.Set;
import java.util.TreeSet;
public class Froggy {
public static int solution(int X, int[] A){
int steps=-1;
Set<Integer> values = new TreeSet<Integer>();
for(int i=0; i<A.length;i++){
if(A[i]<=X){
values.add(A[i]);
}
if(values.size()==X){
steps=i;
break;
}
}
return steps;
}

Better approach would be to use Set, because it only adds unique values to the list. Just add values to the Set and decrement X every time a new value is added, (Set#add() returns true if value is added, false otherwise);
have a look,
public static int solution(int X, int[] A) {
Set<Integer> values = new HashSet<Integer>();
for (int i = 0; i < A.length; i++) {
if (values.add(A[i])) X--;
if (X == 0) return i;
}
return -1;
}
do not forget to import,
import java.util.HashSet;
import java.util.Set;

Here's my solution, scored 100/100:
import java.util.HashSet;
class Solution {
public int solution(int X, int[] A) {
HashSet<Integer> hset = new HashSet<Integer>();
for (int i = 0 ; i < A.length; i++) {
if (A[i] <= X)
hset.add(A[i]);
if (hset.size() == X)
return i;
}
return -1;
}
}

Simple solution 100%
public int solution(final int X, final int[] A) {
Set<Integer> emptyPosition = new HashSet<Integer>();
for (int i = 1; i <= X; i++) {
emptyPosition.add(i);
}
// Once all the numbers are covered for position, that would be the
// moment when the frog will jump
for (int i = 0; i < A.length; i++) {
emptyPosition.remove(A[i]);
if (emptyPosition.size() == 0) {
return i;
}
}
return -1;
}

Here's my solution.
It isn't perfect, but it's good enough to score 100/100.
(I think that it shouldn't have passed a test with a big A and small X)
Anyway, it fills a new counter array with each leaf that falls
counter has the size of X because I don't care for leafs that fall farther than X, therefore the try-catch block.
AFTER X leafs fell (because it's the minimum amount of leafs) I begin checking whether I have a complete way - I'm checking that every int in count is greater than 0.
If so, I return i, else I break and try again.
public static int solution(int X, int[] A){
int[] count = new int[X];
for (int i = 0; i < A.length; i++){
try{
count[A[i]-1]++;
} catch (ArrayIndexOutOfBoundsException e){ }
if (i >= X - 1){
for (int j = 0; j< count.length; j++){
if (count[j] == 0){
break;
}
if (j == count.length - 1){
return i;
}
}
}
}
return -1;
}

Here's my solution with 100 / 100.
public int solution(int X, int[] A) {
int len = A.length;
if (X > len) {
return -1;
}
int[] isFilled = new int[X];
int jumped = 0;
Arrays.fill(isFilled, 0);
for (int i = 0; i < len; i++) {
int x = A[i];
if (x <= X) {
if (isFilled[x - 1] == 0) {
isFilled[x - 1] = 1;
jumped += 1;
if (jumped == X) {
return i;
}
}
}
}
return -1;
}

Here's what I have in C#. It can probably still be refactored.
We throw away numbers greater than X, which is where we want to stop, and then we add numbers to an array if they haven't already been added.
When the count of the list has reached the expected number, X, then return the result. 100%
var tempArray = new int[X+1];
var totalNumbers = 0;
for (int i = 0; i < A.Length; i++)
{
if (A[i] > X || tempArray.ElementAt(A[i]) != 0)
continue;
tempArray[A[i]] = A[i];
totalNumbers++;
if (totalNumbers == X)
return i;
}
return -1;

below is my solution. I basically created a set which allows uniques only and then go through the array and add every element to set and keep a counter to get the sum of the set and then using the sum formula of consecutive numbers then I got 100% . Note : if you add up the set using java 8 stream api the solution is becoming quadratic and you get %56 .
public static int solution2(int X, int[] A) {
long sum = X * (X + 1) / 2;
Set<Integer> set = new HashSet<Integer>();
int setSum = 0;
for (int i = 0; i < A.length; i++) {
if (set.add(A[i]))
setSum += A[i];
if (setSum == sum) {
return i;
}
}
return -1;
}

My JavaScript solution that got 100 across the board. Since the numbers are assumed to be in the range of the river width, simply storing booleans in a temporary array that can be checked against duplicates will do. Then, once you have amassed as many numbers as the quantity X, you know you have all the leaves necessary to cross.
function solution(X, A) {
covered = 0;
tempArray = [];
for (let i = 0; i < A.length; i++) {
if (!tempArray[A[i]]) {
tempArray[A[i]] = true;
covered++
if(covered === X) return i;
}
}
return -1;
}

Here is my answer in Python:
def solution(X, A):
# write your code in Python 3.6
values = set()
for i in range (len(A)):
if A[i]<=X :
values.add(A[i])
if len(values)==X:
return i
return -1

Just tried this problem as well and here is my solution. Basically, I just declared an array whose size is equal to position X. Then, I declared a counter to monitor if the necessary leaves have fallen at the particular spots. The loop exits when these leaves have been met and if not, returns -1 as instructed.
class Solution {
public int solution(int X, int[] A) {
int size = A.length;
int[] check = new int[X];
int cmp = 0;
int time = -1;
for (int x = 0; x < size; x++) {
int temp = A[x];
if (temp <= X) {
if (check[temp-1] > 0) {
continue;
}
check[temp - 1]++;
cmp++;
}
if ( cmp == X) {
time = x;
break;
}
}
return time;
}
}
It got a 100/100 on the evaluation but I'm not too sure of its performance. I am still a beginner when it comes to programming so if anybody can critique the code, I would be grateful.

Maybe it is not perfect but its straightforward. Just made a counter Array to track the needed "leaves" and verified on each iteration if the path was complete. Got me 100/100 and O(N).
public static int frogRiver(int X, int[] A)
{
int leaves = A.Length;
int[] counter = new int[X + 1];
int stepsAvailForTravel = 0;
for(int i = 0; i < leaves; i++)
{
//we won't get to that leaf anyway so we shouldnt count it,
if (A[i] > X)
{
continue;
}
else
{
//first hit!, keep a count of the available leaves to jump
if (counter[A[i]] == 0)
stepsAvailForTravel++;
counter[A[i]]++;
}
//We did it!!
if (stepsAvailForTravel == X)
{
return i;
}
}
return -1;
}

This is my solution. I think it's very simple. It gets 100/100 on codibility.
set.contains() let me eliminate duplicate position from table.
The result of first loop get us expected sum. In the second loop we get sum of input values.
class Solution {
public int solution(int X, int[] A) {
Set<Integer> set = new HashSet<Integer>();
int sum1 = 0, sum2 = 0;
for (int i = 0; i <= X; i++){
sum1 += i;
}
for (int i = 0; i < A.length; i++){
if (set.contains(A[i])) continue;
set.add(A[i]);
sum2 += A[i];
if (sum1 == sum2) return i;
}
return -1;
}
}

Your algorithm is perfect except below code
Your code returns value only if list[iii] matches with searchedValue.
The algorithm must be corrected in such a way that, it returns the value if sum == n * ( n + 1) / 2.
import java.util.ArrayList;
import java.util.List;
class Solution {
public int solution(int X, int[] A) {
int list[] = A;
int sum = 0;
int searchedValue = X;
int sumV = searchedValue * (searchedValue + 1) / 2;
List<Integer> arrayList = new ArrayList<Integer>();
for (int iii = 0; iii < list.length; iii++) {
if (list[iii] <= searchedValue && !arrayList.contains(list[iii])) {
sum += list[iii];
if (sum == sumV) {
return iii;
}
arrayList.add(list[iii]);
}
}
return -1;
}
}
I think you need to check the performance as well. I just ensured the output only

This solution I've posted today gave 100% on codility, but respectivly #rafalio 's answer it requires K times less memory
public class Solution {
private static final int ARRAY_SIZE_LOWER = 1;
private static final int ARRAY_SIZE_UPPER = 100000;
private static final int NUMBER_LOWER = ARRAY_SIZE_LOWER;
private static final int NUMBER_UPPER = ARRAY_SIZE_UPPER;
public static class Set {
final long[] buckets;
public Set(int size) {
this.buckets = new long[(size % 64 == 0 ? (size/64) : (size/64) + 1)];
}
/**
* number should be greater than zero
* #param number
*/
public void put(int number) {
buckets[getBucketindex(number)] |= getFlag(number);
}
public boolean contains(int number) {
long flag = getFlag(number);
// check if flag is stored
return (buckets[getBucketindex(number)] & flag) == flag;
}
private int getBucketindex(int number) {
if (number <= 64) {
return 0;
} else if (number <= 128) {
return 1;
} else if (number <= 192) {
return 2;
} else if (number <= 256) {
return 3;
} else if (number <= 320) {
return 4;
} else if (number <= 384) {
return 5;
} else
return (number % 64 == 0 ? (number/64) : (number/64) + 1) - 1;
}
private long getFlag(int number) {
if (number <= 64) {
return 1L << number;
} else
return 1L << (number % 64);
}
}
public static final int solution(final int X, final int[] A) {
if (A.length < ARRAY_SIZE_LOWER || A.length > ARRAY_SIZE_UPPER) {
throw new RuntimeException("Array size out of bounds");
}
Set set = new Set(X);
int ai;
int counter = X;
final int NUMBER_REAL_UPPER = min(NUMBER_UPPER, X);
for (int i = 0 ; i < A.length; i++) {
if ((ai = A[i]) < NUMBER_LOWER || ai > NUMBER_REAL_UPPER) {
throw new RuntimeException("Number out of bounds");
} else if (ai <= X && !set.contains(ai)) {
counter--;
if (counter == 0) {
return i;
}
set.put(ai);
}
}
return -1;
}
private static int min(int x, int y) {
return (x < y ? x : y);
}
}

This is my solution it got me 100/100 and O(N).
public int solution(int X, int[] A) {
Map<Integer, Integer> leaves = new HashMap<>();
for (int i = A.length - 1; i >= 0 ; i--)
{
leaves.put(A[i] - 1, i);
}
return leaves.size() != X ? -1 : Collections.max(leaves.values());
}

This is my solution
public func FrogRiverOne(_ X : Int, _ A : inout [Int]) -> Int {
var B = [Int](repeating: 0, count: X+1)
for i in 0..<A.count {
if B[A[i]] == 0 {
B[A[i]] = i+1
}
}
var time = 0
for i in 1...X {
if( B[i] == 0 ) {
return -1
} else {
time = max(time, B[i])
}
}
return time-1
}
A = [1,2,1,4,2,3,5,4]
print("FrogRiverOne: ", FrogRiverOne(5, &A))

Actually I re-wrote this exercise without seeing my last answer and came up with another solution 100/100 and O(N).
public int solution(int X, int[] A) {
Set<Integer> leaves = new HashSet<>();
for(int i=0; i < A.length; i++) {
leaves.add(A[i]);
if (leaves.contains(X) && leaves.size() == X) return i;
}
return -1;
}
I like this one better because it is even simpler.

This one works good on codality 100% out of 100%. It's very similar to the marker array above but uses a map:
public int solution(int X, int[] A) {
int index = -1;
Map<Integer, Integer> map = new HashMap();
for (int i = 0; i < A.length; i++) {
if (!map.containsKey(A[i])) {
map.put(A[i], A[i]);
X--;
if (X == 0) {index = i;break;}
}
}
return index;
}

%100 with js
function solution(X, A) {
let leafSet = new Set();
for (let i = 0; i < A.length; i += 1) {
if(A[i] <= 0)
continue;
if (A[i] <= X )
leafSet.add(A[i]);
if (leafSet.size == X)
return i;
}
return -1;
}

With JavaScript following solution got 100/100.
Detected time complexity: O(N)
function solution(X, A) {
let leaves = new Set();
for (let i = 0; i < A.length; i++) {
if (A[i] <= X) {
leaves.add(A[i])
if (leaves.size == X) {
return i;
}
}
}
return -1;
}

100% Solution using Javascript.
function solution(X, A) {
if (A.length === 0) return -1
if (A.length < X) return -1
let steps = X
const leaves = {}
for (let i = 0; i < A.length; i++) {
if (!leaves[A[i]]) {
leaves[A[i]] = true
steps--
}
if (steps === 0) {
return i
}
}
return -1
}

C# Solution with 100% score:
using System;
using System.Collections.Generic;
class Solution {
public int solution(int X, int[] A) {
// go through the array
// fill a hashset, until the size of hashset is X
var set = new HashSet<int>();
int i = 0;
foreach (var a in A)
{
if (a <= X)
{
set.Add(a);
}
if (set.Count == X)
{
return i;
}
i++;
}
return -1;
}
}

https://app.codility.com/demo/results/trainingXE7QFJ-TZ7/
I have a very simple solution (100% / 100%) using HashSet. Lots of people check unnecessarily whether the Value is less than or equal to X. This task cannot be otherwise.
public static int solution(int X, int[] A) {
Set<Integer> availableFields = new HashSet<>();
for (int i = 0; i < A.length; i++) {
availableFields.add(A[i]);
if (availableFields.size() == X){
return i;
}
}
return -1;
}

public static int solutions(int X, int[] A) {
Set<Integer> values = new HashSet<Integer>();
for (int i = 0; i < A.length; i++) {
if (values.add(A[i])) {
X--;
}
if (X == 0) {
return i;
}
}
return -1;
}

This is my solution. It uses 3 loops but is constant time and gets 100/100 on codibility.
class FrogLeap
{
internal int solution(int X, int[] A)
{
int result = -1;
long max = -1;
var B = new int[X + 1];
//initialize all entries in B array with -1
for (int i = 0; i <= X; i++)
{
B[i] = -1;
}
//Go through A and update B with the location where that value appeared
for (int i = 0; i < A.Length; i++)
{
if( B[A[i]] ==-1)//only update if still -1
B[A[i]] = i;
}
//start from 1 because 0 is not valid
for (int i = 1; i <= X; i++)
{
if (B[i] == -1)
return -1;
//The maxValue here is the earliest time we can jump over
if (max < B[i])
max = B[i];
}
result = (int)max;
return result;
}
}

Short and sweet C++ code. Gets perfect 100%... Drum roll ...
#include <set>
int solution(int X, vector<int> &A) {
set<int> final;
for(unsigned int i =0; i< A.size(); i++){
final.insert(A[i]);
if(final.size() == X) return i;
}
return -1;
}

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