We Keep Coding

Power Set in Lexicographic order. Recursion and bactracking

I am new to recursion and backtracking. How the code after the recursive call is being executed?
class Solution {
// str : Stores input string
// n : Length of str.
// curr : Stores current permutation
// index : Index in current permutation, curr
static void permuteRec(String str, int n,
int index, String curr)
{
// base case
if (index == n) {
return;
}
System.out.println(curr);
for (int i = index + 1; i < n; i++) {
curr += str.charAt(i);
permuteRec(str, n, i, curr);
// backtracking
curr = curr.substring(0, curr.length() - 1);
}
return;
}
// Generates power set in lexicographic
// order.
static void powerSet(String str)
{
char[] arr = str.toCharArray();
Arrays.sort(arr);
permuteRec(new String(arr), str.length(), -1, "");
}
// Driver code
public static void main(String[] args)
{
String str = "abc";
powerSet(str);
}
}
I cannot understand how the backtracking is going on inside the for loop?
The output is:
a ab b c ca cab cb

Common characters in n strings

I m trying to make a function that prints the number of characters common in given n strings. (note that characters may be used multiple times)
I am struggling to perform this operation on n strings However I did it for 2 strings without any characters repeated more than once.
I have posted my code.
public class CommonChars {
public static void main(String[] args) {
String str1 = "abcd";
String str2 = "bcde";
StringBuffer sb = new StringBuffer();
// get unique chars from both the strings
str1 = uniqueChar(str1);
str2 = uniqueChar(str2);
int count = 0;
int str1Len = str1.length();
int str2Len = str2.length();
for (int i = 0; i < str1Len; i++) {
for (int j = 0; j < str2Len; j++) {
// found match stop the loop
if (str1.charAt(i) == str2.charAt(j)) {
count++;
sb.append(str1.charAt(i));
break;
}
}
}
System.out.println("Common Chars Count : " + count + "\nCommon Chars :" +
sb.toString());
}
public static String uniqueChar(String inputString) {
String outputstr="",temp="";
for(int i=0;i<inputstr.length();i++) {
if(temp.indexOf(inputstr.charAt(i))<0) {
temp+=inputstr.charAt(i);
}
}
System.out.println("completed");
return temp;
}
}
3
abcaa
bcbd
bgc
3
their may be chances that a same character can be present multiple times in
a string and you are not supposed to eliminate those characters instead
check the no. of times they are repeated in other strings. for eg
3
abacd
aaxyz
aatre
output should be 2
it will be better if i get solution in java

You have to convert all Strings to Set of Characters and retain all from the first one. Below solution has many places which could be optimised but you should understand general idea.
import java.util.Arrays;
import java.util.Collection;
import java.util.Collections;
import java.util.HashSet;
import java.util.List;
import java.util.Set;
public class Main {
public static void main(String[] args) {
List<String> input = Arrays.asList("jonas", "ton", "bonny");
System.out.println(findCommonCharsFor(input));
}
public static Collection<Character> findCommonCharsFor(List<String> strings) {
if (strings == null || strings.isEmpty()) {
return Collections.emptyList();
}
Set<Character> commonChars = convertStringToSetOfChars(strings.get(0));
strings.stream().skip(1).forEach(s -> commonChars.retainAll(convertStringToSetOfChars(s)));
return commonChars;
}
private static Set<Character> convertStringToSetOfChars(String string) {
if (string == null || string.isEmpty()) {
return Collections.emptySet();
}
Set<Character> set = new HashSet<>(string.length() + 10);
for (char c : string.toCharArray()) {
set.add(c);
}
return set;
}
}
Above code prints:
[n, o]

A better strategy for your problem is to use this method:
public int[] countChars(String s){
int[] count = new int[26];
for(char c: s.toCharArray()){
count[c-'a']++;
}
return count;
}
Now if you have n Strings (String[] strings) just find the min of common chars for each letter:
int[][] result = new int[n][26]
for(int i = 0; i<strings.length;i++){
result[i] = countChars(s);
}
// now if you sum the min common chars for each counter you are ready
int commonChars = 0;
for(int i = 0; i< 26;i++){
int min = result[0][i];
for(int i = 1; i< n;i++){
if(min>result[j][i]){
min = result[j][i];
}
}
commonChars+=min;
}

Get list of characters for each string:
List<Character> chars1 = s1.chars() // list of chars for first string
.mapToObj(c -> (char) c)
.collect(Collectors.toList());
List<Character> chars2 = s2.chars() // list of chars for second string
.mapToObj(c -> (char) c)
.collect(Collectors.toList());
Then use retainAll method:
chars1.retainAll(chars2); // retain in chars1 only the chars that are contained in the chars2 also
System.out.println(chars1.size());
If you want to get number of unique chars just use Collectors.toSet() instead of toList()

Well if one goes for hashing:
public static int uniqueChars(String first, String second) {
boolean[] hash = new boolean[26];
int count = 0;
//reduce first string to unique letters
for (char c : first.toLowerCase().toCharArray()) {
hash[c - 'a'] = true;
}
//reduce to unique letters in both strings
for(char c : second.toLowerCase().toCharArray()){
if(hash[c - 'a']){
count++;
hash[c - 'a'] = false;
}
}
return count;
}
This is using bucketsort which gives a n+m complexity but needs the 26 buckets(the "hash" array).
Imo one can't do better in regards of complexity as you need to look at every letter at least once which sums up to n+m.
Insitu the best you can get is imho somewhere in the range of O(n log(n) ) .
Your aproach is somewhere in the league of O(n²)
Addon: if you need the characters as a String(in essence the same as above with count is the length of the String returned):
public static String uniqueChars(String first, String second) {
boolean[] hash = new boolean[26];
StringBuilder sb = new StringBuilder();
for (char c : first.toLowerCase().toCharArray()) {
hash[c - 'a'] = true;
}
for(char c : second.toLowerCase().toCharArray()){
if(hash[c - 'a']){
sb.append(c);
hash[c - 'a'] = false;
}
}
return sb.toString();
}

public static String getCommonCharacters(String... words) {
if (words == null || words.length == 0)
return "";
Set<Character> unique = words[0].chars().mapToObj(ch -> (char)ch).collect(Collectors.toCollection(TreeSet::new));
for (String word : words)
unique.retainAll(word.chars().mapToObj(ch -> (char)ch).collect(Collectors.toSet()));
return unique.stream().map(String::valueOf).collect(Collectors.joining());
}
Another variant without creating temporary Set and using Character.
public static String getCommonCharacters(String... words) {
if (words == null || words.length == 0)
return "";
int[] arr = new int[26];
boolean[] tmp = new boolean[26];
for (String word : words) {
Arrays.fill(tmp, false);
for (int i = 0; i < word.length(); i++) {
int pos = Character.toLowerCase(word.charAt(i)) - 'a';
if (tmp[pos])
continue;
tmp[pos] = true;
arr[pos]++;
}
}
StringBuilder buf = new StringBuilder(26);
for (int i = 0; i < arr.length; i++)
if (arr[i] == words.length)
buf.append((char)('a' + i));
return buf.toString();
}
Demo
System.out.println(getCommonCharacters("abcd", "bcde")); // bcd

Java Method to find the occurencies of a certain character

my code should prompt the user to enter a string and a character, and tell where the character is located
for instance
"Welcome" and "e"
returns
"2, 7"
How can my code be fixed? Code is here. Thanks in advance (this is not homework, but some hint could be useful anyway if you don't want to post a solution).
import java.util.Scanner;
public class Test {
public static void main(String[] args) {
System.out.println("Please enter a string and a character");
Scanner input = new Scanner(System.in);
String s = input.nextLine();
char ch = input.next().charAt(0);
System.out.println(count(ch));
}
public static int count (String s, char a) {
int count = 0;
for (int i = 0; i < s.length(); i++) {
if (s.charAt(i) == a) {
count++;
}
}
return count;
}
}

Some mistakes:
Your code doesn't compile. Call:
System.out.println(count(s, ch));
instead of
System.out.println(count(ch));
You count the number of appearances. Instead, you should keep the indexes. You can use a String or you can add them to a list / array and convert it later to what you want.
public static String count(String s, char a) {
String result = "";
for (int i = 0; i < s.length(); i++) {
if (s.charAt(i) == a) {
result += (i+1) + ", ";
}
}
return result.substring(0, result.length() - 2);
}
I used i+1 instead of i because the indexes start at 0 in Java.
I also returned the string result.substring(0, result.length() - 2) without its last 2 characters, because I added , after every character.

Since Java 8, you can do this by using streams:
public static String count(String s, char a) {
return IntStream.range(0, s.length())
.filter(i -> a == s.charAt(i)).mapToObj(i -> i + "")
.collect(Collectors.joining(", "));
}
This code will print indexes of your Character, seprated by comma.
For more about streams, you can read here, in Java 8 documentation.

Just Change the count method :
public static ArrayList<Integer> count(String s, char a) {
ArrayList<Integer> positions = new ArrayList<>();
for (int i = 0; i < s.length(); i++) {
if (s.charAt(i) == a) {
positions.add(i+1);
}
}
return positions;
}

How to check if two words are anagrams

I have a program that shows you whether two words are anagrams of one another. There are a few examples that will not work properly and I would appreciate any help, although if it were not advanced that would be great, as I am a 1st year programmer. "schoolmaster" and "theclassroom" are anagrams of one another, however when I change "theclassroom" to "theclafsroom" it still says they are anagrams, what am I doing wrong?
import java.util.ArrayList;
public class AnagramCheck {
public static void main(String args[]) {
String phrase1 = "tbeclassroom";
phrase1 = (phrase1.toLowerCase()).trim();
char[] phrase1Arr = phrase1.toCharArray();
String phrase2 = "schoolmaster";
phrase2 = (phrase2.toLowerCase()).trim();
ArrayList<Character> phrase2ArrList = convertStringToArraylist(phrase2);
if (phrase1.length() != phrase2.length()) {
System.out.print("There is no anagram present.");
} else {
boolean isFound = true;
for (int i = 0; i < phrase1Arr.length; i++) {
for (int j = 0; j < phrase2ArrList.size(); j++) {
if (phrase1Arr[i] == phrase2ArrList.get(j)) {
System.out.print("There is a common element.\n");
isFound =;
phrase2ArrList.remove(j);
}
}
if (isFound == false) {
System.out.print("There are no anagrams present.");
return;
}
}
System.out.printf("%s is an anagram of %s", phrase1, phrase2);
}
}
public static ArrayList<Character> convertStringToArraylist(String str) {
ArrayList<Character> charList = new ArrayList<Character>();
for (int i = 0; i < str.length(); i++) {
charList.add(str.charAt(i));
}
return charList;
}
}

Two words are anagrams of each other if they contain the same number of characters and the same characters. You should only need to sort the characters in lexicographic order, and determine if all the characters in one string are equal to and in the same order as all of the characters in the other string.
Here's a code example. Look into Arrays in the API to understand what's going on here.
public boolean isAnagram(String firstWord, String secondWord) {
char[] word1 = firstWord.replaceAll("[\\s]", "").toCharArray();
char[] word2 = secondWord.replaceAll("[\\s]", "").toCharArray();
Arrays.sort(word1);
Arrays.sort(word2);
return Arrays.equals(word1, word2);
}

Fastest algorithm would be to map each of the 26 English characters to a unique prime number. Then calculate the product of the string. By the fundamental theorem of arithmetic, 2 strings are anagrams if and only if their products are the same.

If you sort either array, the solution becomes O(n log n). but if you use a hashmap, it's O(n). tested and working.
char[] word1 = "test".toCharArray();
char[] word2 = "tes".toCharArray();
Map<Character, Integer> lettersInWord1 = new HashMap<Character, Integer>();
for (char c : word1) {
int count = 1;
if (lettersInWord1.containsKey(c)) {
count = lettersInWord1.get(c) + 1;
}
lettersInWord1.put(c, count);
}
for (char c : word2) {
int count = -1;
if (lettersInWord1.containsKey(c)) {
count = lettersInWord1.get(c) - 1;
}
lettersInWord1.put(c, count);
}
for (char c : lettersInWord1.keySet()) {
if (lettersInWord1.get(c) != 0) {
return false;
}
}
return true;

Here's a simple fast O(n) solution without using sorting or multiple loops or hash maps. We increment the count of each character in the first array and decrement the count of each character in the second array. If the resulting counts array is full of zeros, the strings are anagrams. Can be expanded to include other characters by increasing the size of the counts array.
class AnagramsFaster{
private static boolean compare(String a, String b){
char[] aArr = a.toLowerCase().toCharArray(), bArr = b.toLowerCase().toCharArray();
if (aArr.length != bArr.length)
return false;
int[] counts = new int[26]; // An array to hold the number of occurrences of each character
for (int i = 0; i < aArr.length; i++){
counts[aArr[i]-97]++; // Increment the count of the character at i
counts[bArr[i]-97]--; // Decrement the count of the character at i
}
// If the strings are anagrams, the counts array will be full of zeros
for (int i = 0; i<26; i++)
if (counts[i] != 0)
return false;
return true;
}
public static void main(String[] args){
System.out.println(compare(args[0], args[1]));
}
}

Lots of people have presented solutions, but I just want to talk about the algorithmic complexity of some of the common approaches:
The simple "sort the characters using Arrays.sort()" approach is going to be O(N log N).
If you use radix sorting, that reduces to O(N) with O(M) space, where M is the number of distinct characters in the alphabet. (That is 26 in English ... but in theory we ought to consider multi-lingual anagrams.)
The "count the characters" using an array of counts is also O(N) ... and faster than radix sort because you don't need to reconstruct the sorted string. Space usage will be O(M).
A "count the characters" using a dictionary, hashmap, treemap, or equivalent will be slower that the array approach, unless the alphabet is huge.
The elegant "product-of-primes" approach is unfortunately O(N^2) in the worst case This is because for long-enough words or phrases, the product of the primes won't fit into a long. That means that you'd need to use BigInteger, and N times multiplying a BigInteger by a small constant is O(N^2).
For a hypothetical large alphabet, the scaling factor is going to be large. The worst-case space usage to hold the product of the primes as a BigInteger is (I think) O(N*logM).
A hashcode based approach is usually O(N) if the words are not anagrams. If the hashcodes are equal, then you still need to do a proper anagram test. So this is not a complete solution.
I would also like to highlight that most of the posted answers assume that each code-point in the input string is represented as a single char value. This is not a valid assumption for code-points outside of the BMP (plane 0); e.g. if an input string contains emojis.
The solutions that make the invalid assumption will probably work most of the time anyway. A code-point outside of the BMP will represented in the string as two char values: a low surrogate and a high surrogate. If the strings contain only one such code-point, we can get away with treating the char values as if they were code-points. However, we can get into trouble when the strings being tested contain 2 or more code-points. Then the faulty algorithms will fail to distinguish some cases. For example, [SH1, SL1, SH2, SL2] versus [SH1, SL2, SH2, SL1] where the SH<n> and SL<2> denote high and low surrogates respectively. The net result will be false anagrams.
Alex Salauyou's answer gives a couple of solutions that will work for all valid Unicode code-points.

O(n) solution without any kind of sorting and using only one map.
public boolean isAnagram(String leftString, String rightString) {
if (leftString == null || rightString == null) {
return false;
} else if (leftString.length() != rightString.length()) {
return false;
}
Map<Character, Integer> occurrencesMap = new HashMap<>();
for(int i = 0; i < leftString.length(); i++){
char charFromLeft = leftString.charAt(i);
int nrOfCharsInLeft = occurrencesMap.containsKey(charFromLeft) ? occurrencesMap.get(charFromLeft) : 0;
occurrencesMap.put(charFromLeft, ++nrOfCharsInLeft);
char charFromRight = rightString.charAt(i);
int nrOfCharsInRight = occurrencesMap.containsKey(charFromRight) ? occurrencesMap.get(charFromRight) : 0;
occurrencesMap.put(charFromRight, --nrOfCharsInRight);
}
for(int occurrencesNr : occurrencesMap.values()){
if(occurrencesNr != 0){
return false;
}
}
return true;
}
and less generic solution but a little bit faster one. You have to place your alphabet here:
public boolean isAnagram(String leftString, String rightString) {
if (leftString == null || rightString == null) {
return false;
} else if (leftString.length() != rightString.length()) {
return false;
}
char letters[] = {'a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'n', 'o', 'p', 'q', 'r', 's', 't', 'u', 'v', 'w', 'x', 'y', 'z'};
Map<Character, Integer> occurrencesMap = new HashMap<>();
for (char l : letters) {
occurrencesMap.put(l, 0);
}
for(int i = 0; i < leftString.length(); i++){
char charFromLeft = leftString.charAt(i);
Integer nrOfCharsInLeft = occurrencesMap.get(charFromLeft);
occurrencesMap.put(charFromLeft, ++nrOfCharsInLeft);
char charFromRight = rightString.charAt(i);
Integer nrOfCharsInRight = occurrencesMap.get(charFromRight);
occurrencesMap.put(charFromRight, --nrOfCharsInRight);
}
for(Integer occurrencesNr : occurrencesMap.values()){
if(occurrencesNr != 0){
return false;
}
}
return true;
}

We're walking two equal length strings and tracking the differences between them. We don't care what the differences are, we just want to know if they have the same characters or not. We can do this in O(n/2) without any post processing (or a lot of primes).
public class TestAnagram {
public static boolean isAnagram(String first, String second) {
String positive = first.toLowerCase();
String negative = second.toLowerCase();
if (positive.length() != negative.length()) {
return false;
}
int[] counts = new int[26];
int diff = 0;
for (int i = 0; i < positive.length(); i++) {
int pos = (int) positive.charAt(i) - 97; // convert the char into an array index
if (counts[pos] >= 0) { // the other string doesn't have this
diff++; // an increase in differences
} else { // it does have it
diff--; // a decrease in differences
}
counts[pos]++; // track it
int neg = (int) negative.charAt(i) - 97;
if (counts[neg] <= 0) { // the other string doesn't have this
diff++; // an increase in differences
} else { // it does have it
diff--; // a decrease in differences
}
counts[neg]--; // track it
}
return diff == 0;
}
public static void main(String[] args) {
System.out.println(isAnagram("zMarry", "zArmry")); // true
System.out.println(isAnagram("basiparachromatin", "marsipobranchiata")); // true
System.out.println(isAnagram("hydroxydeoxycorticosterones", "hydroxydesoxycorticosterone")); // true
System.out.println(isAnagram("hydroxydeoxycorticosterones", "hydroxydesoxycorticosterons")); // false
System.out.println(isAnagram("zArmcy", "zArmry")); // false
}
}
Yes this code is dependent on the ASCII English character set of lowercase characters but it shouldn't be hard to modify to other languages. You can always use a Map[Character, Int] to track the same information, it'll just be slower.

By using more memory (an HashMap of at most N/2 elements)we do not need to sort the strings.
public static boolean areAnagrams(String one, String two) {
if (one.length() == two.length()) {
String s0 = one.toLowerCase();
String s1 = two.toLowerCase();
HashMap<Character, Integer> chars = new HashMap<Character, Integer>(one.length());
Integer count;
for (char c : s0.toCharArray()) {
count = chars.get(c);
count = Integer.valueOf(count != null ? count + 1 : 1);
chars.put(c, count);
}
for (char c : s1.toCharArray()) {
count = chars.get(c);
if (count == null) {
return false;
} else {
count--;
chars.put(c, count);
}
}
for (Integer i : chars.values()) {
if (i != 0) {
return false;
}
}
return true;
} else {
return false;
}
}
This function is actually running in O(N) ... instead of O(NlogN) for the solution that sorts the strings. If I were to assume that you are going to use only alphabetic characters I could only use an array of 26 ints (from a to z without accents or decorations) instead of the hashmap.
If we define that :
N = |one| + |two|
we do one iteration over N (once over one to increment the counters, and once to decrement them over two).
Then to check the totals we iterate over at mose N/2.
The other algorithms described have one advantage: they do not use extra memory assuming that Arrays.sort uses inplace versions of QuickSort or merge sort. But since we are talking about anagrams I will assume that we are talking about human languages, thus words should not be long enough to give memory issues.

/*
* To change this template, choose Tools | Templates
* and open the template in the editor.
*/
package Algorithms;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.HashMap;
import javax.swing.JOptionPane;
/**
*
* #author Mokhtar
*/
public class Anagrams {
//Write aprogram to check if two words are anagrams
public static void main(String[] args) {
Anagrams an=new Anagrams();
ArrayList<String> l=new ArrayList<String>();
String result=JOptionPane.showInputDialog("How many words to test anagrams");
if(Integer.parseInt(result) >1)
{
for(int i=0;i<Integer.parseInt(result);i++)
{
String word=JOptionPane.showInputDialog("Enter word #"+i);
l.add(word);
}
System.out.println(an.isanagrams(l));
}
else
{
JOptionPane.showMessageDialog(null, "Can not be tested, \nYou can test two words or more");
}
}
private static String sortString( String w )
{
char[] ch = w.toCharArray();
Arrays.sort(ch);
return new String(ch);
}
public boolean isanagrams(ArrayList<String> l)
{
boolean isanagrams=true;
ArrayList<String> anagrams = null;
HashMap<String, ArrayList<String>> map = new HashMap<String, ArrayList<String>>();
for(int i=0;i<l.size();i++)
{
String word = l.get(i);
String sortedWord = sortString(word);
anagrams = map.get( sortedWord );
if( anagrams == null ) anagrams = new ArrayList<String>();
anagrams.add(word);
map.put(sortedWord, anagrams);
}
for(int h=0;h<l.size();h++)
{
if(!anagrams.contains(l.get(h)))
{
isanagrams=false;
break;
}
}
return isanagrams;
//}
}
}

I am a C++ developer and the code below is in C++. I believe the fastest and easiest way to go about it would be the following:
Create a vector of ints of size 26, with all slots initialized to 0, and place each character of the string into the appropriate position in the vector. Remember, the vector is in alphabetical order and so if the first letter in the string is z, it would go in myvector[26]. Note: This can be done using ASCII characters so essentially your code will look something like this:
string s = zadg;
for(int i =0; i < s.size(); ++i){
myvector[s[i] - 'a'] = myvector['s[i] - 'a'] + 1;
}
So inserting all the elements would take O(n) time as you would only traverse the list once. You can now do the exact same thing for the second string and that too would take O(n) time. You can then compare the two vectors by checking to see if the counters in each slot are the same. If they are, that means you had the same number of EACH character in both the strings and thus they are anagrams. The comparing of the two vectors should also take O(n) time as you are only traversing through it once.
Note: The code only works for a single word of characters. If you have spaces, and numbers and symbols, you can just create a vector of size 96 (ASCII characters 32-127) and instead of saying - 'a' you would say - ' ' as the space character is the first one in the ASCII list of characters.
I hope that helps. If i have made a mistake somewhere, please leave a comment.

So far all proposed solutions work with separate char items, not code points. I'd like to propose two solutions to properly handle surrogate pairs as well (those are characters from U+10000 to U+10FFFF, composed of two char items).
1) One-line O(n logn) solution which utilizes Java 8 CharSequence.codePoints() stream:
static boolean areAnagrams(CharSequence a, CharSequence b) {
return Arrays.equals(a.codePoints().sorted().toArray(),
b.codePoints().sorted().toArray());
}
2) Less elegant O(n) solution (in fact, it will be faster only for long strings with low chances to be anagrams):
static boolean areAnagrams(CharSequence a, CharSequence b) {
int len = a.length();
if (len != b.length())
return false;
// collect codepoint occurrences in "a"
Map<Integer, Integer> ocr = new HashMap<>(64);
a.codePoints().forEach(c -> ocr.merge(c, 1, Integer::sum));
// for each codepoint in "b", look for matching occurrence
for (int i = 0, c = 0; i < len; i += Character.charCount(c)) {
int cc = ocr.getOrDefault((c = Character.codePointAt(b, i)), 0);
if (cc == 0)
return false;
ocr.put(c, cc - 1);
}
return true;
}

Thanks for pointing out to make comment, while making comment I found that there was incorrect logic. I corrected the logic and added comment for each piece of code.
// Time complexity: O(N) where N is number of character in String
// Required space :constant space.
// will work for string that contains ASCII chars
private static boolean isAnagram(String s1, String s2) {
// if length of both string's are not equal then they are not anagram of each other
if(s1.length() != s2.length())return false;
// array to store the presence of a character with number of occurrences.
int []seen = new int[256];
// initialize the array with zero. Do not need to initialize specifically since by default element will initialized by 0.
// Added this is just increase the readability of the code.
Arrays.fill(seen, 0);
// convert each string to lower case if you want to make ABC and aBC as anagram, other wise no need to change the case.
s1 = s1.toLowerCase();
s2 = s2.toLowerCase();
// iterate through the first string and count the occurrences of each character
for(int i =0; i < s1.length(); i++){
seen[s1.charAt(i)] = seen[s1.charAt(i)] +1;
}
// iterate through second string and if any char has 0 occurrence then return false, it mean some char in s2 is there that is not present in s1.
// other wise reduce the occurrences by one every time .
for(int i =0; i < s2.length(); i++){
if(seen[s2.charAt(i)] ==0)return false;
seen[s2.charAt(i)] = seen[s2.charAt(i)]-1;
}
// now if both string have same occurrence of each character then the seen array must contains all element as zero. if any one has non zero element return false mean there are
// some character that either does not appear in one of the string or/and mismatch in occurrences
for(int i = 0; i < 256; i++){
if(seen[i] != 0)return false;
}
return true;
}

IMHO, the most efficient solution was provided by #Siguza, I have extended it to cover strings with space e.g: "William Shakespeare", "I am a weakish speller", "School master", "The classroom"
public int getAnagramScore(String word, String anagram) {
if (word == null || anagram == null) {
throw new NullPointerException("Both, word and anagram, must be non-null");
}
char[] wordArray = word.trim().toLowerCase().toCharArray();
char[] anagramArray = anagram.trim().toLowerCase().toCharArray();
int[] alphabetCountArray = new int[26];
int reference = 'a';
for (int i = 0; i < wordArray.length; i++) {
if (!Character.isWhitespace(wordArray[i])) {
alphabetCountArray[wordArray[i] - reference]++;
}
}
for (int i = 0; i < anagramArray.length; i++) {
if (!Character.isWhitespace(anagramArray[i])) {
alphabetCountArray[anagramArray[i] - reference]--;
}
}
for (int i = 0; i < 26; i++)
if (alphabetCountArray[i] != 0)
return 0;
return word.length();
}

// When this method returns 0 means strings are Anagram, else Not.
public static int isAnagram(String str1, String str2) {
int value = 0;
if (str1.length() == str2.length()) {
for (int i = 0; i < str1.length(); i++) {
value = value + str1.charAt(i);
value = value - str2.charAt(i);
}
} else {
value = -1;
}
return value;
}

Many complicated answers here. Base on the accepted answer and the comment mentioning the 'ac'-'bb' issue assuming A=65 B=66 C=67, we could simply use the square of each integer that represent a char and solve the problem:
public boolean anagram(String s, String t) {
if(s.length() != t.length())
return false;
int value = 0;
for(int i = 0; i < s.length(); i++){
value += ((int)s.charAt(i))^2;
value -= ((int)t.charAt(i))^2;
}
return value == 0;
}

A similar answer may have been posted in C++, here it is again in Java. Note that the most elegant way would be to use a Trie to store the characters in sorted order, however, that's a more complex solution. One way is to use a hashset to store all the words we are comparing and then compare them one by one. To compare them, make an array of characters with the index representing the ANCII value of the characters (using a normalizer since ie. ANCII value of 'a' is 97) and the value representing the occurrence count of that character. This will run in O(n) time and use O(m*z) space where m is the size of the currentWord and z the size for the storedWord, both for which we create a Char[].
public static boolean makeAnagram(String currentWord, String storedWord){
if(currentWord.length() != storedWord.length()) return false;//words must be same length
Integer[] currentWordChars = new Integer[totalAlphabets];
Integer[] storedWordChars = new Integer[totalAlphabets];
//create a temp Arrays to compare the words
storeWordCharacterInArray(currentWordChars, currentWord);
storeWordCharacterInArray(storedWordChars, storedWord);
for(int i = 0; i < totalAlphabets; i++){
//compare the new word to the current charList to see if anagram is possible
if(currentWordChars[i] != storedWordChars[i]) return false;
}
return true;//and store this word in the HashSet of word in the Heap
}
//for each word store its characters
public static void storeWordCharacterInArray(Integer[] characterList, String word){
char[] charCheck = word.toCharArray();
for(char c: charCheck){
Character cc = c;
int index = cc.charValue()-indexNormalizer;
characterList[index] += 1;
}
}

How a mathematician might think about the problem before writing any code:
The relation "are anagrams" between strings is an equivalence relation, so partitions the set of all strings into equivalence classes.
Suppose we had a rule to choose a representative (crib) from each class, then it's easy to test whether two classes are the same by comparing their representatives.
An obvious representative for a set of strings is "the smallest element by lexicographic order", which is easy to compute from any element by sorting. For example, the representative of the anagram class containing 'hat' is 'aht'.
In your example "schoolmaster" and "theclassroom" are anagrams because they are both in the anagram class with crib "acehlmoorsst".
In pseudocode:
>>> def crib(word):
... return sorted(word)
...
>>> crib("schoolmaster") == crib("theclassroom")
True

import java.util.ArrayList;
import java.util.List;
import java.util.Map;
import java.util.TreeMap;
/**
* Check if Anagram by Prime Number Logic
* #author Pallav
*
*/
public class Anagram {
public static void main(String args[]) {
System.out.println(isAnagram(args[0].toUpperCase(),
args[1].toUpperCase()));
}
/**
*
* #param word : The String 1
* #param anagram_word : The String 2 with which Anagram to be verified
* #return true or false based on Anagram
*/
public static Boolean isAnagram(String word, String anagram_word) {
//If length is different return false
if (word.length() != anagram_word.length()) {
return false;
}
char[] words_char = word.toCharArray();//Get the Char Array of First String
char[] anagram_word_char = anagram_word.toCharArray();//Get the Char Array of Second String
int words_char_num = 1;//Initialize Multiplication Factor to 1
int anagram_word_num = 1;//Initialize Multiplication Factor to 1 for String 2
Map<Character, Integer> wordPrimeMap = wordPrimeMap();//Get the Prime numbers Mapped to each alphabets in English
for (int i = 0; i < words_char.length; i++) {
words_char_num *= wordPrimeMap.get(words_char[i]);//get Multiplication value for String 1
}
for (int i = 0; i < anagram_word_char.length; i++) {
anagram_word_num *= wordPrimeMap.get(anagram_word_char[i]);//get Multiplication value for String 2
}
return anagram_word_num == words_char_num;
}
/**
* Get the Prime numbers Mapped to each alphabets in English
* #return
*/
public static Map<Character, Integer> wordPrimeMap() {
List<Integer> primes = primes(26);
int k = 65;
Map<Character, Integer> map = new TreeMap<Character, Integer>();
for (int i = 0; i < primes.size(); i++) {
Character character = (char) k;
map.put(character, primes.get(i));
k++;
}
// System.out.println(map);
return map;
}
/**
* get first N prime Numbers where Number is greater than 2
* #param N : Number of Prime Numbers
* #return
*/
public static List<Integer> primes(Integer N) {
List<Integer> primes = new ArrayList<Integer>();
primes.add(2);
primes.add(3);
int n = 5;
int k = 0;
do {
boolean is_prime = true;
for (int i = 2; i <= Math.sqrt(n); i++) {
if (n % i == 0) {
is_prime = false;
break;
}
}
if (is_prime == true) {
primes.add(n);
}
n++;
// System.out.println(k);
} while (primes.size() < N);
// }
return primes;
}
}

Here is my solution.First explode the strings into char arrays then sort them and then comparing if they are equal or not. I guess time complexity of this code is O(a+b).if a=b we can say O(2A)
public boolean isAnagram(String s1, String s2) {
StringBuilder sb1 = new StringBuilder();
StringBuilder sb2 = new StringBuilder();
if (s1.length() != s2.length())
return false;
char arr1[] = s1.toCharArray();
char arr2[] = s2.toCharArray();
Arrays.sort(arr1);
Arrays.sort(arr2);
for (char c : arr1) {
sb1.append(c);
}
for (char c : arr2) {
sb2.append(c);
}
System.out.println(sb1.toString());
System.out.println(sb2.toString());
if (sb1.toString().equals(sb2.toString()))
return true;
else
return false;
}

There are 3 solution i can think of :
Using sorting
# O(NlogN) + O(MlogM) time, O(1) space
def solve_by_sort(word1, word2):
return sorted(word1) == sorted(word2)
Using letter frequency count
# O(N+M) time, O(N+M) space
def solve_by_letter_frequency(word1, word2):
from collections import Counter
return Counter(word1) == Counter(word2)
Using the concept of prime factorization. (assign primes to each letter)
import operator
from functools import reduce
# O(N) time, O(1) space - prime factorization
def solve_by_prime_number_hash(word1, word2):
return get_prime_number_hash(word1) == get_prime_number_hash(word2)
def get_prime_number_hash(word):
letter_code = {'a': 2, 'b': 3, 'c': 5, 'd': 7, 'e': 11, 'f': 13, 'g': 17, 'h': 19, 'i': 23, 'j': 29, 'k': 31,'l': 37, 'm': 41, 'n': 43,'o': 47, 'p': 53, 'q': 59, 'r': 61, 's': 67, 't': 71, 'u': 73, 'v': 79, 'w': 83, 'x': 89, 'y': 97,'z': 101}
return 0 if not word else reduce(operator.mul, [letter_code[letter] for letter in word])
I have put more detailed analysis of these in my medium story.

Sorting approach is not the best one. It takes O(n) space and O(nlogn) time. Instead, make a hash map of characters and count them (increment characters that appear in the first string and decrement characters that appear in the second string). When some count reaches zero, remove it from hash. Finally, if two strings are anagrams, then the hash table will be empty in the end - otherwise it will not be empty.
Couple of important notes: (1) Ignore letter case and (2) Ignore white space.
Here is the detailed analysis and implementation in C#: Testing If Two Strings are Anagrams

Some other solution without sorting.
public static boolean isAnagram(String s1, String s2){
//case insensitive anagram
StringBuffer sb = new StringBuffer(s2.toLowerCase());
for (char c: s1.toLowerCase().toCharArray()){
if (Character.isLetter(c)){
int index = sb.indexOf(String.valueOf(c));
if (index == -1){
//char does not exist in other s2
return false;
}
sb.deleteCharAt(index);
}
}
for (char c: sb.toString().toCharArray()){
//only allow whitespace as left overs
if (!Character.isWhitespace(c)){
return false;
}
}
return true;
}

A simple method to figure out whether the testString is an anagram of the baseString.
private static boolean isAnagram(String baseString, String testString){
//Assume that there are no empty spaces in either string.
if(baseString.length() != testString.length()){
System.out.println("The 2 given words cannot be anagram since their lengths are different");
return false;
}
else{
if(baseString.length() == testString.length()){
if(baseString.equalsIgnoreCase(testString)){
System.out.println("The 2 given words are anagram since they are identical.");
return true;
}
else{
List<Character> list = new ArrayList<>();
for(Character ch : baseString.toLowerCase().toCharArray()){
list.add(ch);
}
System.out.println("List is : "+ list);
for(Character ch : testString.toLowerCase().toCharArray()){
if(list.contains(ch)){
list.remove(ch);
}
}
if(list.isEmpty()){
System.out.println("The 2 words are anagrams");
return true;
}
}
}
}
return false;
}

Sorry, the solution is in C#, but I think the different elements used to arrive at the solution is quite intuitive. Slight tweak required for hyphenated words but for normal words it should work fine.
internal bool isAnagram(string input1,string input2)
{
Dictionary<char, int> outChars = AddToDict(input2.ToLower().Replace(" ", ""));
input1 = input1.ToLower().Replace(" ","");
foreach(char c in input1)
{
if (outChars.ContainsKey(c))
{
if (outChars[c] > 1)
outChars[c] -= 1;
else
outChars.Remove(c);
}
}
return outChars.Count == 0;
}
private Dictionary<char, int> AddToDict(string input)
{
Dictionary<char, int> inputChars = new Dictionary<char, int>();
foreach(char c in input)
{
if(inputChars.ContainsKey(c))
{
inputChars[c] += 1;
}
else
{
inputChars.Add(c, 1);
}
}
return inputChars;
}

I saw that no one has used the "hashcode" approach to find out the anagrams. I found my approach little different than the approaches discussed above hence thought of sharing it. I wrote the below code to find the anagrams which works in O(n).
/**
* This class performs the logic of finding anagrams
* #author ripudam
*
*/
public class AnagramTest {
public static boolean isAnagram(final String word1, final String word2) {
if (word1 == null || word2 == null || word1.length() != word2.length()) {
return false;
}
if (word1.equals(word2)) {
return true;
}
final AnagramWrapper word1Obj = new AnagramWrapper(word1);
final AnagramWrapper word2Obj = new AnagramWrapper(word2);
if (word1Obj.equals(word2Obj)) {
return true;
}
return false;
}
/*
* Inner class to wrap the string received for anagram check to find the
* hash
*/
static class AnagramWrapper {
String word;
public AnagramWrapper(final String word) {
this.word = word;
}
#Override
public boolean equals(final Object obj) {
return hashCode() == obj.hashCode();
}
#Override
public int hashCode() {
final char[] array = word.toCharArray();
int hashcode = 0;
for (final char c : array) {
hashcode = hashcode + (c * c);
}
return hashcode;
}
}
}

Here is another approach using HashMap in Java
public static boolean isAnagram(String first, String second) {
if (first == null || second == null) {
return false;
}
if (first.length() != second.length()) {
return false;
}
return doCheckAnagramUsingHashMap(first.toLowerCase(), second.toLowerCase());
}
private static boolean doCheckAnagramUsingHashMap(final String first, final String second) {
Map<Character, Integer> counter = populateMap(first, second);
return validateMap(counter);
}
private static boolean validateMap(Map<Character, Integer> counter) {
for (int val : counter.values()) {
if (val != 0) {
return false;
}
}
return true;
}
Here is the test case
#Test
public void anagramTest() {
assertTrue(StringUtil.isAnagram("keep" , "PeeK"));
assertFalse(StringUtil.isAnagram("Hello", "hell"));
assertTrue(StringUtil.isAnagram("SiLeNt caT", "LisTen cat"));
}

private static boolean checkAnagram(String s1, String s2) {
if (s1 == null || s2 == null) {
return false;
} else if (s1.length() != s2.length()) {
return false;
}
char[] a1 = s1.toCharArray();
char[] a2 = s2.toCharArray();
int length = s2.length();
int s1Count = 0;
int s2Count = 0;
for (int i = 0; i < length; i++) {
s1Count+=a1[i];
s2Count+=a2[i];
}
return s2Count == s1Count ? true : false;
}

The simplest solution with complexity O(N) is using Map.
public static Boolean checkAnagram(String string1, String string2) {
Boolean anagram = true;
Map<Character, Integer> map1 = new HashMap<>();
Map<Character, Integer> map2 = new HashMap<>();
char[] chars1 = string1.toCharArray();
char[] chars2 = string2.toCharArray();
for(int i=0; i<chars1.length; i++) {
if(map1.get(chars1[i]) == null) {
map1.put(chars1[i], 1);
} else {
map1.put(chars1[i], map1.get(chars1[i])+1);
}
if(map2.get(chars2[i]) == null) {
map2.put(chars2[i], 1);
} else {
map2.put(chars2[i], map2.get(chars2[i])+1);
}
}
Set<Map.Entry<Character, Integer>> entrySet1 = map1.entrySet();
Set<Map.Entry<Character, Integer>> entrySet2 = map2.entrySet();
for(Map.Entry<Character, Integer> entry:entrySet1) {
if(entry.getValue() != map2.get(entry.getKey())) {
anagram = false;
break;
}
}
return anagram;
}

let's take a question: Given two strings s and t, write a function to determine if t is an anagram of s.
For example,
s = "anagram", t = "nagaram", return true.
s = "rat", t = "car", return false.
Method 1(Using HashMap ):
public class Method1 {
public static void main(String[] args) {
String a = "protijayi";
String b = "jayiproti";
System.out.println(isAnagram(a, b ));// output => true
}
private static boolean isAnagram(String a, String b) {
Map<Character ,Integer> map = new HashMap<>();
for( char c : a.toCharArray()) {
map.put(c, map.getOrDefault(c, 0 ) + 1 );
}
for(char c : b.toCharArray()) {
int count = map.getOrDefault(c, 0);
if(count == 0 ) {return false ; }
else {map.put(c, count - 1 ) ; }
}
return true;
}
}
Method 2 :
public class Method2 {
public static void main(String[] args) {
String a = "protijayi";
String b = "jayiproti";
System.out.println(isAnagram(a, b));// output=> true
}
private static boolean isAnagram(String a, String b) {
int[] alphabet = new int[26];
for(int i = 0 ; i < a.length() ;i++) {
alphabet[a.charAt(i) - 'a']++ ;
}
for (int i = 0; i < b.length(); i++) {
alphabet[b.charAt(i) - 'a']-- ;
}
for( int w : alphabet ) {
if(w != 0 ) {return false;}
}
return true;
}
}
Method 3 :
public class Method3 {
public static void main(String[] args) {
String a = "protijayi";
String b = "jayiproti";
System.out.println(isAnagram(a, b ));// output => true
}
private static boolean isAnagram(String a, String b) {
char[] ca = a.toCharArray() ;
char[] cb = b.toCharArray();
Arrays.sort( ca );
Arrays.sort( cb );
return Arrays.equals(ca , cb );
}
}
Method 4 :
public class AnagramsOrNot {
public static void main(String[] args) {
String a = "Protijayi";
String b = "jayiProti";
isAnagram(a, b);
}
private static void isAnagram(String a, String b) {
Map<Integer, Integer> map = new LinkedHashMap<>();
a.codePoints().forEach(code -> map.put(code, map.getOrDefault(code, 0) + 1));
System.out.println(map);
b.codePoints().forEach(code -> map.put(code, map.getOrDefault(code, 0) - 1));
System.out.println(map);
if (map.values().contains(0)) {
System.out.println("Anagrams");
} else {
System.out.println("Not Anagrams");
}
}
}
In Python:
def areAnagram(a, b):
if len(a) != len(b): return False
count1 = [0] * 256
count2 = [0] * 256
for i in a:count1[ord(i)] += 1
for i in b:count2[ord(i)] += 1
for i in range(256):
if(count1[i] != count2[i]):return False
return True
str1 = "Giniiii"
str2 = "Protijayi"
print(areAnagram(str1, str2))
Let's take another famous Interview Question: Group the Anagrams from a given String:
public class GroupAnagrams {
public static void main(String[] args) {
String a = "Gini Gina Protijayi iGin aGin jayiProti Soudipta";
Map<String, List<String>> map = Arrays.stream(a.split(" ")).collect(Collectors.groupingBy(GroupAnagrams::sortedString));
System.out.println("MAP => " + map);
map.forEach((k,v) -> System.out.println(k +" and the anagrams are =>" + v ));
/*
Look at the Map output:
MAP => {Giin=[Gini, iGin], Paiijorty=[Protijayi, jayiProti], Sadioptu=[Soudipta], Gain=[Gina, aGin]}
As we can see, there are multiple Lists. Hence, we have to use a flatMap(List::stream)
Now, Look at the output:
Paiijorty and the anagrams are =>[Protijayi, jayiProti]
Now, look at this output:
Sadioptu and the anagrams are =>[Soudipta]
List contains only word. No anagrams.
That means we have to work with map.values(). List contains all the anagrams.
*/
String stringFromMapHavingListofLists = map.values().stream().flatMap(List::stream).collect(Collectors.joining(" "));
System.out.println(stringFromMapHavingListofLists);
}
public static String sortedString(String a) {
String sortedString = a.chars().sorted()
.collect(StringBuilder::new, StringBuilder::appendCodePoint, StringBuilder::append).toString();
return sortedString;
}
/*
* The output : Gini iGin Protijayi jayiProti Soudipta Gina aGin
* All the anagrams are side by side.
*/
}
Now to Group Anagrams in Python is again easy.We have to :
Sort the lists. Then, Create a dictionary. Now dictionary will tell us where are those anagrams are( Indices of Dictionary). Then values of the dictionary is the actual indices of the anagrams.
def groupAnagrams(words):
# sort each word in the list
A = [''.join(sorted(word)) for word in words]
dict = {}
for indexofsamewords, names in enumerate(A):
dict.setdefault(names, []).append(indexofsamewords)
print(dict)
#{'AOOPR': [0, 2, 5, 11, 13], 'ABTU': [1, 3, 4], 'Sorry': [6], 'adnopr': [7], 'Sadioptu': [8, 16], ' KPaaehiklry': [9], 'Taeggllnouy': [10], 'Leov': [12], 'Paiijorty': [14, 18], 'Paaaikpr': [15], 'Saaaabhmryz': [17], ' CNaachlortttu': [19], 'Saaaaborvz': [20]}
for index in dict.values():
print([words[i] for i in index])
if __name__ == '__main__':
# list of words
words = ["ROOPA","TABU","OOPAR","BUTA","BUAT" , "PAROO","Soudipta",
"Kheyali Park", "Tollygaunge", "AROOP","Love","AOORP", "Protijayi","Paikpara","dipSouta","Shyambazaar",
"jayiProti", "North Calcutta", "Sovabazaar"]
groupAnagrams(words)
The Output :
['ROOPA', 'OOPAR', 'PAROO', 'AROOP', 'AOORP']
['TABU', 'BUTA', 'BUAT']
['Soudipta', 'dipSouta']
['Kheyali Park']
['Tollygaunge']
['Love']
['Protijayi', 'jayiProti']
['Paikpara']
['Shyambazaar']
['North Calcutta']
['Sovabazaar']
Another Important Anagram Question : Find the Anagram occuring Max. number of times.
In the Example, ROOPA is the word which has occured maximum number of times.
Hence, ['ROOPA' 'OOPAR' 'PAROO' 'AROOP' 'AOORP'] will be the final output.
from sqlite3 import collections
from statistics import mode, mean
import numpy as np
# list of words
words = ["ROOPA","TABU","OOPAR","BUTA","BUAT" , "PAROO","Soudipta",
"Kheyali Park", "Tollygaunge", "AROOP","Love","AOORP",
"Protijayi","Paikpara","dipSouta","Shyambazaar",
"jayiProti", "North Calcutta", "Sovabazaar"]
print(".....Method 1....... ")
sortedwords = [''.join(sorted(word)) for word in words]
print(sortedwords)
print("...........")
LongestAnagram = np.array(words)[np.array(sortedwords) == mode(sortedwords)]
# Longest anagram
print("Longest anagram by Method 1:")
print(LongestAnagram)
print(".....................................................")
print(".....Method 2....... ")
A = [''.join(sorted(word)) for word in words]
dict = {}
for indexofsamewords,samewords in enumerate(A):
dict.setdefault(samewords,[]).append(samewords)
#print(dict)
#{'AOOPR': ['AOOPR', 'AOOPR', 'AOOPR', 'AOOPR', 'AOOPR'], 'ABTU': ['ABTU', 'ABTU', 'ABTU'], 'Sadioptu': ['Sadioptu', 'Sadioptu'], ' KPaaehiklry': [' KPaaehiklry'], 'Taeggllnouy': ['Taeggllnouy'], 'Leov': ['Leov'], 'Paiijorty': ['Paiijorty', 'Paiijorty'], 'Paaaikpr': ['Paaaikpr'], 'Saaaabhmryz': ['Saaaabhmryz'], ' CNaachlortttu': [' CNaachlortttu'], 'Saaaaborvz': ['Saaaaborvz']}
aa = max(dict.items() , key = lambda x : len(x[1]))
print("aa => " , aa)
word, anagrams = aa
print("Longest anagram by Method 2:")
print(" ".join(anagrams))
The Output :
.....Method 1.......
['AOOPR', 'ABTU', 'AOOPR', 'ABTU', 'ABTU', 'AOOPR', 'Sadioptu', ' KPaaehiklry', 'Taeggllnouy', 'AOOPR', 'Leov', 'AOOPR', 'Paiijorty', 'Paaaikpr', 'Sadioptu', 'Saaaabhmryz', 'Paiijorty', ' CNaachlortttu', 'Saaaaborvz']
...........
Longest anagram by Method 1:
['ROOPA' 'OOPAR' 'PAROO' 'AROOP' 'AOORP']
.....................................................
.....Method 2.......
aa => ('AOOPR', ['AOOPR', 'AOOPR', 'AOOPR', 'AOOPR', 'AOOPR'])
Longest anagram by Method 2:
AOOPR AOOPR AOOPR AOOPR AOOPR

This could be the simple function call
A mix of functional Code and Imperative style of code
static boolean isAnagram(String a, String b) {
String sortedA = "";
Object[] aArr = a.toLowerCase().chars().sorted().mapToObj(i -> (char) i).toArray();
for (Object o: aArr) {
sortedA = sortedA.concat(o.toString());
}
String sortedB = "";
Object[] bArr = b.toLowerCase().chars().sorted().mapToObj(i -> (char) i).toArray();
for (Object o: bArr) {
sortedB = sortedB.concat(o.toString());
}
if(sortedA.equals(sortedB))
return true;
else
return false;
}

Generating the lexicographically greatest string

The question is to generate the lexicographically greatest string given some string s.
So the aim is to find lexicographically greatest, unique(no repetitions) substring s1 from s.
We say that some subsequence s1 is greater than another subsequence s2 if s1 has more characters than s2 or s1 is lexicographically greater than s2 if equal length.
I/O are as follows:
Input is: babab
output is: ba
Second input is: nlhthgrfdnnlprjtecpdrthigjoqdejsfkasoctjijaoebqlrgaiakfsbljmpibkidjsrtkgrdnqsknbarpabgokbsrfhmeklrle
Second output is:
tsocrpkijgdqnbafhmle
This is what I wrote for my java code but my code fails on the second test case. Also I'm having a hard time understanding why second output isn't tsrqponmlkjihgfedcba.
Can somebody provide suggestions for a fix or even java code?
I think the algorithm has to be more efficient than generating all possible unique strings, sort them and find lexicographically largest one.
To make the question much clearer, if the input is babab, then all the possible unique combinations would be b, a, ba, ab. And the output will be ba because it's the longest and lexicographically greater than ab.
Note: this is not a homework assignment.
import java.io.BufferedReader;
import java.io.IOException;
import java.io.InputStreamReader;
public class mostBeautiful {
final static int MAX = 1000000;
static String[] permute;
static void permutation(String prefix, String str, int counter) {
int n = str.length();
//System.out.println("n is: "+ n);
if (n == 0) {
permute[counter] = prefix;
} else {
for (int i = 0; i < n; i++) {
//System.out.println("str is: "+ str);
permutation(prefix + str.charAt(i), str.substring(0, i) + str.substring(i+1, n), counter++);
}
}
}
public static void main(String[] args) throws IOException {
BufferedReader bf = new BufferedReader(new InputStreamReader(System.in));
String s = bf.readLine();
char[] unique = new char[26];
int counter = 0;
String answer = "";
//System.out.println("s is: " + s);
int ascii = 0;
final int asciiAVal = 97;
final int asciiZVal = 122;
for (int i = 0; i < s.length(); i++) {
ascii = (int)s.charAt(i);
if (ascii < asciiAVal || ascii > asciiZVal) {
continue;
}
char ch = s.charAt(i);
unique[ch - 'a'] = ch;
}
String result = "";
for (int j = 25; j >= 0; j--) {
result += unique[j];
}
result = result.trim();
System.out.println(result);
int size = result.length() * (result.length() - 1);
permute = new String[size];
permutation("", result, counter);
for (int i = 1; i < size; i++) {
if (permute[i].compareTo(permute[i - 1]) > 0){
answer = permute[i];
} else {
answer = permute[i - 1];
}
}
System.out.println("answer is: " + answer);
}
}

After thinking about this problem in many ways, I have determined a divide-and-conquer algorithm that gets the results right:
Algorithm - Pseudocode
Assuming some input string, S defined as a concatenation of two substrings A + B, we compute the lexicographically greatest string recursively as:
LexMax(S) = Merge(LexMax(A),LexMax(B))
Where
LexMax(S)
{
if Length(S) = 1
return S
else
{
LMA = LexMax(S[0:Length/2])
LMB = LexMax(S[Length/2:end])
return Merge(LMA,LMB)
}
}
Merge(A,B)
{
Sa = A
Sb = B
for n = 0:Length(A)
{
if Sb contains A[n]
{
if A[n+1:end] contains character > A[n]
Remove A[n] from Sa
else
Remove A[n] from Sb
}
}
return Sa + Sb
}
Java Code
Coming soon!
Example
Given an input string
cefcfdabbcfed
Divide it into
cefcfda
bbcfed
Assuming the function works we have:
LexMax("cefcfda") = "efcda"
LexMax("bbcfed") = "bcfed"
Merging works as follows:
e: efcda bcfed
In both substrings, greater value found to right of e in left substring, remove from left
f: fcda bcfed
In both substrings, no greater value in left substring, remove from right
c: fcda bced
In both substrings, greater value found to right of c in left substring, remove from left
d: fda bced
In both substrings, no greater value in left substring, remove from right
a: fda bce
Not in both substrings, do nothing
Final result:
LexMax(cefcfdabbcfed) = fdabce

This is not a direct answer, but doesn't this code meet the requirement as you explained it in the discussion above?
final String x = "saontehusanoethusnaoteusnaoetuh";
final SortedSet<Character> chars =
new TreeSet<Character>(Collections.reverseOrder());
for (char c : x.toCharArray()) chars.add(c);
System.out.println(chars);

Lexicographic order is an order in which words are displayed in alphabetical order using the appearance of letters in the word.It is also know as dictionary order or alphabetical order.For ex:-"Africa" is smaller than "Bangladesh" ,"He" is smaller than "he".
public class LexicographicExample {
public static void main(String a[]) {
Scanner sc = new Scanner(System.in);
System.out.println("Enter the String:-");
String str = sc.nextLine();
System.out.println("Enter the length");
int count = sc.nextInt();
List<String> list = new ArrayList<String>();
for (int i = 0; i < str.length(); i = i + 1) {
if (str.length() - i >= count) {
list.add(str.substring(i, count + i));
}
}
Collections.sort(list);
System.out.println("Smallest subString:-" + list.get(0));
System.out.println("Largest subString:-" + list.get(list.size() - 1));
}
}
For reference ,refer this link http://techno-terminal.blogspot.in/2015/09/java-program-to-find-lexicographically.html

"tsrqponmlkjihgfedcba" is not the answer because it is not a subsequence of the input. The definition of subsequence requires that the characters of the subsequence occur in the original sequence in the same order. For example, "abc" is a subsequence of "apbqcr", while "cba" is not.
As to the solution, I think a simple greedy algorithm would suffice. First, one has to understand that the maximum possible length of the output is the number of unique symbols (say, N) in the input. Since any output shorter than that would not be the greatest one, it has to be exactly N symbols long. The rest of the procedure is simple and at most quadratic in time complexity: one has to go through the input string and at each step pick the lexicographically highest symbol such that the part of the string to the left of it would still contain all the "unused" symbols.
As an example, consider a string "bacb". The first symbol can be 'a' or 'b', since in both cases the remainder contains both of the other letters. 'b' is greater, so we pick it. Now for "acb" we can only pick 'a' and than 'c' according to that condition, so we end up with "bac" for output.

import java.util.ArrayList;
import java.util.HashMap;
import java.util.Scanner;
class aaa {
public static void main(String args[]) throws Exception {
Scanner scan = new Scanner(System.in);
// int n = scan.nextInt();
String s = scan.next();
HashMap<Character, Node5> map = new HashMap<>();
for (int i = 0; i < s.length(); i++) {
if (!map.containsKey(s.charAt(i))) {
Node5 node = new Node5();
node.nl.add(i);
node.li = i;
map.put(s.charAt(i), node);
} else {
Node5 rn = map.get(s.charAt(i));
rn.nl.add(i);
rn.li = i;
map.put(s.charAt(i), rn);
}
}
String s1 = "";
int index = -1;
for (int i = 25; i >= 0; i--) {
if (map.containsKey((char) (97 + i))) {
if (map.get((char) (97 + i)).li > index) {
for (int j = 0; j < map.get((char) (97 + i)).nl.size(); j++) {
if (map.get((char) (97 + i)).nl.get(j) > index) {
s1 += (char) (97 + i);
index = map.get((char) (97 + i)).nl.get(j);
}
}
}
}
}
System.out.println(s1);
scan.close();
}
}
class Node5 {
int li;
ArrayList<Integer> nl;
public Node5() {
this.nl = new ArrayList<>();
}
}