Time complexity of prefix to postfix conversion? - data-structures

I think it should be quadratic i.e O(n^2). I am reading from this source prefix to postfix . I assume that appending two string takes linear time (O(sum of size of the two strings which we are appending)) and maximum number of times we need to append can go upto O(n) and thus overall complexity is O(n^2).
Can some one tell if i am wrong and can some one provide better proof of this ?

Yes, you're right that it's O(n2), and I think your proof is OK, but that depends who you have to prove it to. Maybe show explicitly how to construct a string that would result in O(n) appends of O(n) size.
Here's a simple recursive version that does the job in O(n):
static String preToPost(String src)
{
StringBuilder dest = new StringBuilder(src.length());
for(int pos=0; pos < src.length(); pos = preToPost(dest, src, pos));
return dest.toString();
}
// Convert one prefix expression to postfix. Returns
// end position
static int preToPost(StringBuilder dest, String src, int pos)
{
if (pos >= src.length())
{
//no expression
return pos;
}
char c = src.charAt(pos++);
if ("+-/*".indexOf(c)>=0)
{
//operator. Convert both operands first
pos = preToPost(dest, src, pos);
pos = preToPost(dest, src, pos);
}
dest.append(c);
return pos;
}
The iterative version is not much more complicated:
static String preToPost2(String src)
{
StringBuilder dest = new StringBuilder(src.length());
int pos=0;
Stack<Character> stk = new Stack<>();
while(pos < src.length())
{
char c = src.charAt(pos++);
if ("+-/*".indexOf(c)>=0)
{
//operator. After the next 2 expressions, put c
stk.push(c);
//after the next expression, just do another one
stk.push('\0');
continue;
}
dest.append(c);
// done expression. check the todo stack
while(!stk.empty())
{
c = stk.pop();
if (c=='\0')
{
break;
}
dest.append(c);
// the append completed another expression, so loop
// to check the todo stack again
}
}
return dest.toString();
}
This is a direct conversion of the recursive one.

Related

Fast String Searching Algorithm for large strings

I'm trying to implement a plagiarism detection software using pattern matching algorithms. I came across the KMP Algorithm Here and tried out the c# implementation. I can see that it's not as fast for actual documents (not strings, I uploaded two pdf documents using iText and got the implementation to check for plagiarism in these two papers. About 50 pages).
It's really slow and I have no idea how to go about this. I've looked at Boyer Moore and Rabin Karp as well.
What I am currently doing is taking each sentence in the document (split on '.') and scanning through the whole reference document (2nd document) for a match. Then taking the next sentence and so on...
I am fully aware that this could be very expensive. But I have no idea how else to implement string (pattern) matching without using this approach. It's for my final year project and I was given a topic so I HAVE to use string matching. (Not allowed to do Citation based plagiarism, Semantics or Vector Space.)
The larger the text and pattern gets, the slower the algorithm gets (extremely slow, not even reasonably slow). Is there another way to go about this that I don't know? Or are there faster algorithms for me to use with this my approach?
EDIT
My code below:`
public class MatchChecker
{
public void KMPSearch(string pattern, string text, int page)
{
if (pattern.Trim() != "")
{
int M = pattern.Length;
int N = text.Length;
// create lps[] that will hold the longest
// prefix suffix values for pattern
int[] lps = new int[M];
int j = 0; // index for pat[]
// Preprocess the pattern (calculate lps[]
// array)
computeLPSArray(pattern, M, lps);
int i = 0; //index for text[]
while (i < N)
{
if (pattern[j] == text[i])
{
j++;
i++;
}
if (j == M)
{
Console.WriteLine("Found pattern " + pattern + " at page " + page);
j = lps[j - 1];
}
//mismatch after j matches
else if (i < N && pattern[j] != text[i])
{
//Do not match lps[0..lps[j-1]] characters,
//they will match anyway
if (j != 0)
j = lps[j - 1];
else
i = i + 1;
}
}
}
}
private void computeLPSArray(string pattern, int M, int[] lps)
{
//length of the previous longest prefix suffix
int length = 0;
int i = 1;
lps[0] = 0; //lps[0]is always 0
//the loop calculates lps[i] for i = 1 to M - 1
while (i < M)
{
if (pattern[i] == pattern[length])
{
length++;
lps[i] = length;
i++;
}
else // (pat[i] != pat[len])
{
// This is tricky. Consider the example.
// AAACAAAA and i = 7. The idea is similar
// to search step.
if (length != 0)
{
length = lps[length - 1];
// Also, note that we do not increment
// i here
}
else // if (len == 0)
{
lps[i] = length;
i++;
}
}
}
}
public string ReadDocPDF()
{
List<string> pages = new List<string>();
PdfReader reader2 = new PdfReader(#"C:\Users\obn\Desktop\project\chapter1.pdf");
string strText = string.Empty;
for (int page = 1; page <= reader2.NumberOfPages; page++)
{
ITextExtractionStrategy its = new SimpleTextExtractionStrategy();
PdfReader reader = new PdfReader(#"C:\Users\obn\Desktop\project\chapter1.pdf");
String s = PdfTextExtractor.GetTextFromPage(reader, page, its);
s = Regex.Replace(Encoding.UTF8.GetString(ASCIIEncoding.Convert(Encoding.Default, Encoding.UTF8, Encoding.Default.GetBytes(s))).Replace(",", ""), "[0-9]", "").ToLower();
pages.Add(s);
strText = strText + s;
reader.Close();
}
return strText;
}
public void CheckForPlag()
{
string document = ReadDocPDF().Trim();
string[] sentences = document.Split(new string[] { "\n", "\t\n\r", ". ", "." }, StringSplitOptions.RemoveEmptyEntries);
foreach(string sentence in sentences) {
PdfReader reader2 = new PdfReader(#"C:\Users\obn\Documents\visual studio 2015\Projects\PlagDetector\PlagDetector\bin\Debug\test3.pdf");
for (int page = 1; page <= reader2.NumberOfPages; page++)
{
ITextExtractionStrategy its = new SimpleTextExtractionStrategy();
PdfReader reader = new PdfReader(#"C:\Users\obn\Documents\visual studio 2015\Projects\PlagDetector\PlagDetector\bin\Debug\test3.pdf");
String s = PdfTextExtractor.GetTextFromPage(reader, page, its);
s = Regex.Replace(Encoding.UTF8.GetString(ASCIIEncoding.Convert(Encoding.Default, Encoding.UTF8, Encoding.Default.GetBytes(s))).Trim().Replace(".","").Replace(",","").Replace("\n", ""), "[0-9]", "").ToLower();
KMPSearch(sentence, s, page);
reader.Close();
}
}
}
}`
Your algorithm is doing lot of repeated searches purely a brute force. Some of the problems features can be considered to optimize it.
How do you define 'plagiarism'? content-1 and content-2 are nearly similar. Let us say >80% are same. i.e content-1 is taken 20% is changed to produce content-2.
Now, Let us try to solve: what will be cost (no.of changes) to convert content-1 to content-2?
This is a well know problem in DP(dynamic programming world) as EDIT Distance problem. The standard problem talks about strings distance, but you can easily modify it for words instead of chars.
Now, the above problem will give you least no.of changes for conversion of content-1 to content-2.
With the total length of content-1, we can easily calculate the % of changes to go to content-2 from content-1. If it below a fixed threshold (say 20%) then declare the plagiarism.

Find word in string buffer/paragraph/text

This was asked in Amazon telephonic interview - "Can you write a program (in your preferred language C/C++/etc.) to find a given word in a string buffer of big size ? i.e. number of occurrences "
I am still looking for perfect answer which I should have given to the interviewer.. I tried to write a linear search (char by char comparison) and obviously I was rejected.
Given a 40-45 min time for a telephonic interview, what was the perfect algorithm he/she was looking for ???
The KMP Algorithm is a popular string matching algorithm.
KMP Algorithm
Checking char by char is inefficient. If the string has 1000 characters and the keyword has 100 characters, you don't want to perform unnecessary comparisons. The KMP Algorithm handles many cases which can occur, but I imagine the interviewer was looking for the case where: When you begin (pass 1), the first 99 characters match, but the 100th character doesn't match. Now, for pass 2, instead of performing the entire comparison from character 2, you have enough information to deduce where the next possible match can begin.
// C program for implementation of KMP pattern searching
// algorithm
#include<stdio.h>
#include<string.h>
#include<stdlib.h>
void computeLPSArray(char *pat, int M, int *lps);
void KMPSearch(char *pat, char *txt)
{
int M = strlen(pat);
int N = strlen(txt);
// create lps[] that will hold the longest prefix suffix
// values for pattern
int *lps = (int *)malloc(sizeof(int)*M);
int j = 0; // index for pat[]
// Preprocess the pattern (calculate lps[] array)
computeLPSArray(pat, M, lps);
int i = 0; // index for txt[]
while (i < N)
{
if (pat[j] == txt[i])
{
j++;
i++;
}
if (j == M)
{
printf("Found pattern at index %d \n", i-j);
j = lps[j-1];
}
// mismatch after j matches
else if (i < N && pat[j] != txt[i])
{
// Do not match lps[0..lps[j-1]] characters,
// they will match anyway
if (j != 0)
j = lps[j-1];
else
i = i+1;
}
}
free(lps); // to avoid memory leak
}
void computeLPSArray(char *pat, int M, int *lps)
{
int len = 0; // length of the previous longest prefix suffix
int i;
lps[0] = 0; // lps[0] is always 0
i = 1;
// the loop calculates lps[i] for i = 1 to M-1
while (i < M)
{
if (pat[i] == pat[len])
{
len++;
lps[i] = len;
i++;
}
else // (pat[i] != pat[len])
{
if (len != 0)
{
// This is tricky. Consider the example
// AAACAAAA and i = 7.
len = lps[len-1];
// Also, note that we do not increment i here
}
else // if (len == 0)
{
lps[i] = 0;
i++;
}
}
}
}
// Driver program to test above function
int main()
{
char *txt = "ABABDABACDABABCABAB";
char *pat = "ABABCABAB";
KMPSearch(pat, txt);
return 0;
}
This code is taken from a really good site that teaches algorithms:
Geeks for Geeks KMP
Amazon and companies alike expect knowledge of Boyer–Moore string search or / and Knuth–Morris–Pratt algorithms.
Those are good if you want to show perfect knowledge. Otherwise, try to be creative and write something relatively elegant and efficient.
Did you ask about delimiters before you wrote anything? It could be that they may simplify your task to provide some extra information about a string buffer.
Even code below could be ok (it's really not) if you provide enough information in advance, properly explain runtime, space requirements, choice of data containers.
int find( std::string & the_word, std::string & text )
{
std::stringstream ss( text ); // !!! could be really bad idea if 'text' is really big
std::string word;
std::unordered_map< std::string, int > umap;
while( ss >> text ) ++umap[text]; // you have to assume that each word separated by white-spaces.
return umap[the_word];
}

Trying to understand the space complexity of this algorithm

I see a lot of articles online explaining Time complexity but haven't found anything good that explains space complexity well. I was trying to solve the following interview question
You have two numbers represented by a linked list, where each node
contains a single digit. The digits are stored in reverse order, such
that the Ts digit is at the head of the list. Write a function that
adds the two numbers and returns the sum as a linked list.
EXAMPLE
Input: (7-> 1 -> 6) + (5 -> 9 -> 2).That is, 617 + 295.
Output: 2 -> 1 -> 9.That is, 912.
My solution for it is the following:
private Node addLists(Node head1, Node head2) {
Node summationHead = null;
Node summationIterator = null;
int num1 = extractNumber(head1);
int num2 = extractNumber(head2);
int sum = num1 + num2;
StringBuilder strValue = new StringBuilder();
strValue.append(sum);
String value = strValue.reverse().toString();
char[] valueArray = value.toCharArray();
for (char charValue : valueArray) {
Node node = createNode(Character.getNumericValue(charValue));
if (summationHead == null) {
summationHead = node;
summationIterator = summationHead;
} else {
summationIterator.next = node;
summationIterator = node;
}
}
return summationHead;
}
private Node createNode(int value) {
Node node = new Node(value);
node.element = value;
node.next = null;
return node;
}
private int extractNumber(Node head) {
Node iterator = head;
StringBuilder strNum = new StringBuilder();
while (iterator != null) {
int value = iterator.element;
strNum.append(value);
iterator = iterator.next;
}
String reversedString = strNum.reverse().toString();
return Integer.parseInt(reversedString);
}
Can someone please deduce the space complexity for this? Thanks.
The space complexity means "how does the amount of space required to run this algorithm change asymptotically as the inputs get larger"?
So you have two lists of length N and M. The resultant list will have length max(N,M), possibly +1 if there's a carry. But that +1 is a constant, and we don't consider it part of the Big-O as the larger of N or M will dominate.
Also note this algo is pretty straightforward. There's no intermediate calculation requiring larger-than-linear space.
The space complexity is max(N,M).

Find the first un-repeated character in a string

What is the quickest way to find the first character which only appears once in a string?
It has to be at least O(n) because you don't know if a character will be repeated until you've read all characters.
So you can iterate over the characters and append each character to a list the first time you see it, and separately keep a count of how many times you've seen it (in fact the only values that matter for the count is "0", "1" or "more than 1").
When you reach the end of the string you just have to find the first character in the list that has a count of exactly one.
Example code in Python:
def first_non_repeated_character(s):
counts = defaultdict(int)
l = []
for c in s:
counts[c] += 1
if counts[c] == 1:
l.append(c)
for c in l:
if counts[c] == 1:
return c
return None
This runs in O(n).
I see that people have posted some delightful answers below, so I'd like to offer something more in-depth.
An idiomatic solution in Ruby
We can find the first un-repeated character in a string like so:
def first_unrepeated_char string
string.each_char.tally.find { |_, n| n == 1 }.first
end
How does Ruby accomplish this?
Reading Ruby's source
Let's break down the solution and consider what algorithms Ruby uses for each step.
First we call each_char on the string. This creates an enumerator which allows us to visit the string one character at a time. This is complicated by the fact that Ruby handles Unicode characters, so each value we get from the enumerator can be a variable number of bytes. If we know our input is ASCII or similar, we could use each_byte instead.
The each_char method is implemented like so:
rb_str_each_char(VALUE str)
{
RETURN_SIZED_ENUMERATOR(str, 0, 0, rb_str_each_char_size);
return rb_str_enumerate_chars(str, 0);
}
In turn, rb_string_enumerate_chars is implemented as:
rb_str_enumerate_chars(VALUE str, VALUE ary)
{
VALUE orig = str;
long i, len, n;
const char *ptr;
rb_encoding *enc;
str = rb_str_new_frozen(str);
ptr = RSTRING_PTR(str);
len = RSTRING_LEN(str);
enc = rb_enc_get(str);
if (ENC_CODERANGE_CLEAN_P(ENC_CODERANGE(str))) {
for (i = 0; i < len; i += n) {
n = rb_enc_fast_mbclen(ptr + i, ptr + len, enc);
ENUM_ELEM(ary, rb_str_subseq(str, i, n));
}
}
else {
for (i = 0; i < len; i += n) {
n = rb_enc_mbclen(ptr + i, ptr + len, enc);
ENUM_ELEM(ary, rb_str_subseq(str, i, n));
}
}
RB_GC_GUARD(str);
if (ary)
return ary;
else
return orig;
}
From this we can see that it calls rb_enc_mbclen (or its fast version) to get the length (in bytes) of the next character in the string so that it can iterate the next step. By lazily iterating over a string, reading just one character at a time, we end up doing just one full pass over the input string as tally consumes the iterator.
Tally is then implemented like so:
static void
tally_up(VALUE hash, VALUE group)
{
VALUE tally = rb_hash_aref(hash, group);
if (NIL_P(tally)) {
tally = INT2FIX(1);
}
else if (FIXNUM_P(tally) && tally < INT2FIX(FIXNUM_MAX)) {
tally += INT2FIX(1) & ~FIXNUM_FLAG;
}
else {
tally = rb_big_plus(tally, INT2FIX(1));
}
rb_hash_aset(hash, group, tally);
}
static VALUE
tally_i(RB_BLOCK_CALL_FUNC_ARGLIST(i, hash))
{
ENUM_WANT_SVALUE();
tally_up(hash, i);
return Qnil;
}
Here, tally_i uses RB_BLOCK_CALL_FUNC_ARGLIST to call repeatedly to tally_up, which updates the tally hash on every iteration.
Rough time & memory analysis
The each_char method doesn't allocate an array to eagerly hold the characters of the string, so it has a small constant memory overhead. When we tally the characters, we allocate a hash and put our tally data into it which in the worst case scenario can take up as much memory as the input string times some constant factor.
Time-wise, tally does a full scan of the string, and calling find to locate the first non-repeated character will scan the hash again, each of which carry O(n) worst-case complexity.
However, tally also updates a hash on every iteration. Updating the hash on every character can be as slow as O(n) again, so the worst case complexity of this Ruby solution is perhaps O(n^2).
However, under reasonable assumptions, updating a hash has an O(1) complexity, so we can expect the average case amortized to look like O(n).
My old accepted answer in Python
You can't know that the character is un-repeated until you've processed the whole string, so my suggestion would be this:
def first_non_repeated_character(string):
chars = []
repeated = []
for character in string:
if character in chars:
chars.remove(character)
repeated.append(character)
else:
if not character in repeated:
chars.append(character)
if len(chars):
return chars[0]
else:
return False
Edit: originally posted code was bad, but this latest snippet is Certified To Work On Ryan's Computer™.
Why not use a heap based data structure such as a minimum priority queue. As you read each character from the string, add it to the queue with a priority based on the location in the string and the number of occurrences so far. You could modify the queue to add priorities on collision so that the priority of a character is the sum of the number appearances of that character. At the end of the loop, the first element in the queue will be the least frequent character in the string and if there are multiple characters with a count == 1, the first element was the first unique character added to the queue.
Here is another fun way to do it. Counter requires Python2.7 or Python3.1
>>> from collections import Counter
>>> def first_non_repeated_character(s):
... return min((k for k,v in Counter(s).items() if v<2), key=s.index)
...
>>> first_non_repeated_character("aaabbbcddd")
'c'
>>> first_non_repeated_character("aaaebbbcddd")
'e'
Lots of answers are attempting O(n) but are forgetting the actual costs of inserting and removing from the lists/associative arrays/sets they're using to track.
If you can assume that a char is a single byte, then you use a simple array indexed by the char and keep a count in it. This is truly O(n) because the array accesses are guaranteed O(1), and the final pass over the array to find the first element with 1 is constant time (because the array has a small, fixed size).
If you can't assume that a char is a single byte, then I would propose sorting the string and then doing a single pass checking adjacent values. This would be O(n log n) for the sort plus O(n) for the final pass. So it's effectively O(n log n), which is better than O(n^2). Also, it has virtually no space overhead, which is another problem with many of the answers that are attempting O(n).
Counter requires Python2.7 or Python3.1
>>> from collections import Counter
>>> def first_non_repeated_character(s):
... counts = Counter(s)
... for c in s:
... if counts[c]==1:
... return c
... return None
...
>>> first_non_repeated_character("aaabbbcddd")
'c'
>>> first_non_repeated_character("aaaebbbcddd")
'e'
Refactoring a solution proposed earlier (not having to use extra list/memory). This goes over the string twice. So this takes O(n) too like the original solution.
def first_non_repeated_character(s):
counts = defaultdict(int)
for c in s:
counts[c] += 1
for c in s:
if counts[c] == 1:
return c
return None
The following is a Ruby implementation of finding the first nonrepeated character of a string:
def first_non_repeated_character(string)
string1 = string.split('')
string2 = string.split('')
string1.each do |let1|
counter = 0
string2.each do |let2|
if let1 == let2
counter+=1
end
end
if counter == 1
return let1
break
end
end
end
p first_non_repeated_character('dont doddle in the forest')
And here is a JavaScript implementation of the same style function:
var first_non_repeated_character = function (string) {
var string1 = string.split('');
var string2 = string.split('');
var single_letters = [];
for (var i = 0; i < string1.length; i++) {
var count = 0;
for (var x = 0; x < string2.length; x++) {
if (string1[i] == string2[x]) {
count++
}
}
if (count == 1) {
return string1[i];
}
}
}
console.log(first_non_repeated_character('dont doddle in the forest'));
console.log(first_non_repeated_character('how are you today really?'));
In both cases I used a counter knowing that if the letter is not matched anywhere in the string, it will only occur in the string once so I just count it's occurrence.
I think this should do it in C. This operates in O(n) time with no ambiguity about order of insertion and deletion operators. This is a counting sort (simplest form of a bucket sort, which itself is the simple form of a radix sort).
unsigned char find_first_unique(unsigned char *string)
{
int chars[256];
int i=0;
memset(chars, 0, sizeof(chars));
while (string[i++])
{
chars[string[i]]++;
}
i = 0;
while (string[i++])
{
if (chars[string[i]] == 1) return string[i];
}
return 0;
}
In Ruby:
(Original Credit: Andrew A. Smith)
x = "a huge string in which some characters repeat"
def first_unique_character(s)
s.each_char.detect { |c| s.count(c) == 1 }
end
first_unique_character(x)
=> "u"
def first_non_repeated_character(string):
chars = []
repeated = []
for character in string:
if character in repeated:
... discard it.
else if character in chars:
chars.remove(character)
repeated.append(character)
else:
if not character in repeated:
chars.append(character)
if len(chars):
return chars[0]
else:
return False
Other JavaScript solutions are quite c-style solutions here is a more JavaScript-style solution.
var arr = string.split("");
var occurences = {};
var tmp;
var lowestindex = string.length+1;
arr.forEach( function(c){
tmp = c;
if( typeof occurences[tmp] == "undefined")
occurences[tmp] = tmp;
else
occurences[tmp] += tmp;
});
for(var p in occurences) {
if(occurences[p].length == 1)
lowestindex = Math.min(lowestindex, string.indexOf(p));
}
if(lowestindex > string.length)
return null;
return string[lowestindex];
}
in C, this is almost Shlemiel the Painter's Algorithm (not quite O(n!) but more than 0(n2)).
But will outperform "better" algorithms for reasonably sized strings because O is so small. This can also easily tell you the location of the first non-repeating string.
char FirstNonRepeatedChar(char * psz)
{
for (int ii = 0; psz[ii] != 0; ++ii)
{
for (int jj = ii+1; ; ++jj)
{
// if we hit the end of string, then we found a non-repeat character.
//
if (psz[jj] == 0)
return psz[ii]; // this character doesn't repeat
// if we found a repeat character, we can stop looking.
//
if (psz[ii] == psz[jj])
break;
}
}
return 0; // there were no non-repeating characters.
}
edit: this code is assuming you don't mean consecutive repeating characters.
Here's an implementation in Perl (version >=5.10) that doesn't care whether the repeated characters are consecutive or not:
use strict;
use warnings;
foreach my $word(#ARGV)
{
my #distinct_chars;
my %char_counts;
my #chars=split(//,$word);
foreach (#chars)
{
push #distinct_chars,$_ unless $_~~#distinct_chars;
$char_counts{$_}++;
}
my $first_non_repeated="";
foreach(#distinct_chars)
{
if($char_counts{$_}==1)
{
$first_non_repeated=$_;
last;
}
}
if(length($first_non_repeated))
{
print "For \"$word\", the first non-repeated character is '$first_non_repeated'.\n";
}
else
{
print "All characters in \"$word\" are repeated.\n";
}
}
Storing this code in a script (which I named non_repeated.pl) and running it on a few inputs produces:
jmaney> perl non_repeated.pl aabccd "a huge string in which some characters repeat" abcabc
For "aabccd", the first non-repeated character is 'b'.
For "a huge string in which some characters repeat", the first non-repeated character is 'u'.
All characters in "abcabc" are repeated.
Here's a possible solution in ruby without using Array#detect (as in this answer). Using Array#detect makes it too easy, I think.
ALPHABET = %w(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)
def fnr(s)
unseen_chars = ALPHABET.dup
seen_once_chars = []
s.each_char do |c|
if unseen_chars.include?(c)
unseen_chars.delete(c)
seen_once_chars << c
elsif seen_once_chars.include?(c)
seen_once_chars.delete(c)
end
end
seen_once_chars.first
end
Seems to work for some simple examples:
fnr "abcdabcegghh"
# => "d"
fnr "abababababababaqababa"
=> "q"
Suggestions and corrections are very much appreciated!
Try this code:
public static String findFirstUnique(String str)
{
String unique = "";
foreach (char ch in str)
{
if (unique.Contains(ch)) unique=unique.Replace(ch.ToString(), "");
else unique += ch.ToString();
}
return unique[0].ToString();
}
In Mathematica one might write this:
string = "conservationist deliberately treasures analytical";
Cases[Gather # Characters # string, {_}, 1, 1][[1]]
{"v"}
This snippet code in JavaScript
var string = "tooth";
var hash = [];
for(var i=0; j=string.length, i<j; i++){
if(hash[string[i]] !== undefined){
hash[string[i]] = hash[string[i]] + 1;
}else{
hash[string[i]] = 1;
}
}
for(i=0; j=string.length, i<j; i++){
if(hash[string[i]] === 1){
console.info( string[i] );
return false;
}
}
// prints "h"
Different approach here.
scan each element in the string and create a count array which stores the repetition count of each element.
Next time again start from first element in the array and print the first occurrence of element with count = 1
C code
-----
#include <stdio.h>
#include <stdlib.h>
int main(int argc, char *argv[])
{
char t_c;
char *t_p = argv[1] ;
char count[128]={'\0'};
char ch;
for(t_c = *(argv[1]); t_c != '\0'; t_c = *(++t_p))
count[t_c]++;
t_p = argv[1];
for(t_c = *t_p; t_c != '\0'; t_c = *(++t_p))
{
if(count[t_c] == 1)
{
printf("Element is %c\n",t_c);
break;
}
}
return 0;
}
input is = aabbcddeef output is = c
char FindUniqueChar(char *a)
{
int i=0;
bool repeat=false;
while(a[i] != '\0')
{
if (a[i] == a[i+1])
{
repeat = true;
}
else
{
if(!repeat)
{
cout<<a[i];
return a[i];
}
repeat=false;
}
i++;
}
return a[i];
}
Here is another approach...we could have a array which will store the count and the index of the first occurrence of the character. After filling up the array we could jst traverse the array and find the MINIMUM index whose count is 1 then return str[index]
#include <iostream>
#include <cstdio>
#include <cstdlib>
#include <climits>
using namespace std;
#define No_of_chars 256
//store the count and the index where the char first appear
typedef struct countarray
{
int count;
int index;
}countarray;
//returns the count array
countarray *getcountarray(char *str)
{
countarray *count;
count=new countarray[No_of_chars];
for(int i=0;i<No_of_chars;i++)
{
count[i].count=0;
count[i].index=-1;
}
for(int i=0;*(str+i);i++)
{
(count[*(str+i)].count)++;
if(count[*(str+i)].count==1) //if count==1 then update the index
count[*(str+i)].index=i;
}
return count;
}
char firstnonrepeatingchar(char *str)
{
countarray *array;
array = getcountarray(str);
int result = INT_MAX;
for(int i=0;i<No_of_chars;i++)
{
if(array[i].count==1 && result > array[i].index)
result = array[i].index;
}
delete[] (array);
return (str[result]);
}
int main()
{
char str[] = "geeksforgeeks";
cout<<"First non repeating character is "<<firstnonrepeatingchar(str)<<endl;
return 0;
}
Function:
This c# function uses a HashTable (Dictionary) and have a performance O(2n) worstcase.
private static string FirstNoRepeatingCharacter(string aword)
{
Dictionary<string, int> dic = new Dictionary<string, int>();
for (int i = 0; i < aword.Length; i++)
{
if (!dic.ContainsKey(aword.Substring(i, 1)))
dic.Add(aword.Substring(i, 1), 1);
else
dic[aword.Substring(i, 1)]++;
}
foreach (var item in dic)
{
if (item.Value == 1) return item.Key;
}
return string.Empty;
}
Example:
string aword = "TEETER";
Console.WriteLine(FirstNoRepeatingCharacter(aword)); //print: R
I have two strings i.e. 'unique' and 'repeated'. Every character appearing for the first time, gets added to 'unique'. If it is repeated for the second time, it gets removed from 'unique' and added to 'repeated'. This way, we will always have a string of unique characters in 'unique'.
Complexity big O(n)
public void firstUniqueChar(String str){
String unique= "";
String repeated = "";
str = str.toLowerCase();
for(int i=0; i<str.length();i++){
char ch = str.charAt(i);
if(!(repeated.contains(str.subSequence(i, i+1))))
if(unique.contains(str.subSequence(i, i+1))){
unique = unique.replaceAll(Character.toString(ch), "");
repeated = repeated+ch;
}
else
unique = unique+ch;
}
System.out.println(unique.charAt(0));
}
The following code is in C# with complexity of n.
using System;
using System.Linq;
using System.Text;
namespace SomethingDigital
{
class FirstNonRepeatingChar
{
public static void Main()
{
String input = "geeksforgeeksandgeeksquizfor";
char[] str = input.ToCharArray();
bool[] b = new bool[256];
String unique1 = "";
String unique2 = "";
foreach (char ch in str)
{
if (!unique1.Contains(ch))
{
unique1 = unique1 + ch;
unique2 = unique2 + ch;
}
else
{
unique2 = unique2.Replace(ch.ToString(), "");
}
}
if (unique2 != "")
{
Console.WriteLine(unique2[0].ToString());
Console.ReadLine();
}
else
{
Console.WriteLine("No non repeated string");
Console.ReadLine();
}
}
}
}
The following solution is an elegant way to find the first unique character within a string using the new features which have been introduced as part as Java 8. This solution uses the approach of first creating a map to count the number of occurrences of each character. It then uses this map to find the first character which occurs only once. This runs in O(N) time.
import static java.util.stream.Collectors.counting;
import static java.util.stream.Collectors.groupingBy;
import java.util.Arrays;
import java.util.List;
import java.util.Map;
// Runs in O(N) time and uses lambdas and the stream API from Java 8
// Also, it is only three lines of code!
private static String findFirstUniqueCharacterPerformantWithLambda(String inputString) {
// convert the input string into a list of characters
final List<String> inputCharacters = Arrays.asList(inputString.split(""));
// first, construct a map to count the number of occurrences of each character
final Map<Object, Long> characterCounts = inputCharacters
.stream()
.collect(groupingBy(s -> s, counting()));
// then, find the first unique character by consulting the count map
return inputCharacters
.stream()
.filter(s -> characterCounts.get(s) == 1)
.findFirst()
.orElse(null);
}
Here is one more solution with o(n) time complexity.
public void findUnique(String string) {
ArrayList<Character> uniqueList = new ArrayList<>();
int[] chatArr = new int[128];
for (int i = 0; i < string.length(); i++) {
Character ch = string.charAt(i);
if (chatArr[ch] != -1) {
chatArr[ch] = -1;
uniqueList.add(ch);
} else {
uniqueList.remove(ch);
}
}
if (uniqueList.size() == 0) {
System.out.println("No unique character found!");
} else {
System.out.println("First unique character is :" + uniqueList.get(0));
}
}
I read through the answers, but did not see any like mine, I think this answer is very simple and fast, am I wrong?
def first_unique(s):
repeated = []
while s:
if s[0] not in s[1:] and s[0] not in repeated:
return s[0]
else:
repeated.append(s[0])
s = s[1:]
return None
test
(first_unique('abdcab') == 'd', first_unique('aabbccdad') == None, first_unique('') == None, first_unique('a') == 'a')
Question : First Unique Character of a String
This is the simplest solution.
public class Test4 {
public static void main(String[] args) {
String a = "GiniGinaProtijayi";
firstUniqCharindex(a);
}
public static void firstUniqCharindex(String a) {
int[] count = new int[256];
for (int i = 0; i < a.length(); i++) {
count[a.charAt(i)]++;
}
int index = -1;
for (int i = 0; i < a.length(); i++) {
if (count[a.charAt(i)] == 1) {
index = i;
break;
} // if
}
System.out.println(index);// output => 8
System.out.println(a.charAt(index)); //output => P
}// end1
}
IN Python :
def firstUniqChar(a):
count = [0] * 256
for i in a: count[ord(i)] += 1
element = ""
for items in a:
if(count[ord(items) ] == 1):
element = items ;
break
return element
a = "GiniGinaProtijayi";
print(firstUniqChar(a)) # output is P
Using Java 8 :
public class Test2 {
public static void main(String[] args) {
String a = "GiniGinaProtijayi";
Map<Character, Long> map = a.chars()
.mapToObj(
ch -> Character.valueOf((char) ch)
).collect(
Collectors.groupingBy(
Function.identity(),
LinkedHashMap::new,
Collectors.counting()));
System.out.println("MAP => " + map);
// {G=2, i=5, n=2, a=2, P=1, r=1, o=1, t=1, j=1, y=1}
Character chh = map
.entrySet()
.stream()
.filter(entry -> entry.getValue() == 1L)
.map(entry -> entry.getKey())
.findFirst()
.get();
System.out.println("First Non Repeating Character => " + chh);// P
}// main
}
how about using a suffix tree for this case... the first unrepeated character will be first character of longest suffix string with least depth in tree..
Create Two list -
unique list - having only unique character .. UL
non-unique list - having only repeated character -NUL
for(char c in str) {
if(nul.contains(c)){
//do nothing
}else if(ul.contains(c)){
ul.remove(c);
nul.add(c);
}else{
nul.add(c);
}

How can I compute the number of characters required to turn a string into a palindrome?

I recently found a contest problem that asks you to compute the minimum number of characters that must be inserted (anywhere) in a string to turn it into a palindrome.
For example, given the string: "abcbd" we can turn it into a palindrome by inserting just two characters: one after "a" and another after "d": "adbcbda".
This seems to be a generalization of a similar problem that asks for the same thing, except characters can only be added at the end - this has a pretty simple solution in O(N) using hash tables.
I have been trying to modify the Levenshtein distance algorithm to solve this problem, but haven't been successful. Any help on how to solve this (it doesn't necessarily have to be efficient, I'm just interested in any DP solution) would be appreciated.
Note: This is just a curiosity. Dav proposed an algorithm which can be modified to DP algorithm to run in O(n^2) time and O(n^2) space easily (and perhaps O(n) with better bookkeeping).
Of course, this 'naive' algorithm might actually come in handy if you decide to change the allowed operations.
Here is a 'naive'ish algorithm, which can probably be made faster with clever bookkeeping.
Given a string, we guess the middle of the resulting palindrome and then try to compute the number of inserts required to make the string a palindrome around that middle.
If the string is of length n, there are 2n+1 possible middles (Each character, between two characters, just before and just after the string).
Suppose we consider a middle which gives us two strings L and R (one to left and one to right).
If we are using inserts, I believe the Longest Common Subsequence algorithm (which is a DP algorithm) can now be used the create a 'super' string which contains both L and reverse of R, see Shortest common supersequence.
Pick the middle which gives you the smallest number inserts.
This is O(n^3) I believe. (Note: I haven't tried proving that it is true).
My C# solution looks for repeated characters in a string and uses them to reduce the number of insertions. In a word like program, I use the 'r' characters as a boundary. Inside of the 'r's, I make that a palindrome (recursively). Outside of the 'r's, I mirror the characters on the left and the right.
Some inputs have more than one shortest output: output can be toutptuot or outuputuo. My solution only selects one of the possibilities.
Some example runs:
radar -> radar, 0 insertions
esystem -> metsystem, 2 insertions
message -> megassagem, 3 insertions
stackexchange -> stegnahckexekchangets, 8 insertions
First I need to check if an input is already a palindrome:
public static bool IsPalindrome(string str)
{
for (int left = 0, right = str.Length - 1; left < right; left++, right--)
{
if (str[left] != str[right])
return false;
}
return true;
}
Then I need to find any repeated characters in the input. There may be more than one. The word message has two most-repeated characters ('e' and 's'):
private static bool TryFindMostRepeatedChar(string str, out List<char> chs)
{
chs = new List<char>();
int maxCount = 1;
var dict = new Dictionary<char, int>();
foreach (var item in str)
{
int temp;
if (dict.TryGetValue(item, out temp))
{
dict[item] = temp + 1;
maxCount = temp + 1;
}
else
dict.Add(item, 1);
}
foreach (var item in dict)
{
if (item.Value == maxCount)
chs.Add(item.Key);
}
return maxCount > 1;
}
My algorithm is here:
public static string MakePalindrome(string str)
{
List<char> repeatedList;
if (string.IsNullOrWhiteSpace(str) || IsPalindrome(str))
{
return str;
}
//If an input has repeated characters,
// use them to reduce the number of insertions
else if (TryFindMostRepeatedChar(str, out repeatedList))
{
string shortestResult = null;
foreach (var ch in repeatedList) //"program" -> { 'r' }
{
//find boundaries
int iLeft = str.IndexOf(ch); // "program" -> 1
int iRight = str.LastIndexOf(ch); // "program" -> 4
//make a palindrome of the inside chars
string inside = str.Substring(iLeft + 1, iRight - iLeft - 1); // "program" -> "og"
string insidePal = MakePalindrome(inside); // "og" -> "ogo"
string right = str.Substring(iRight + 1); // "program" -> "am"
string rightRev = Reverse(right); // "program" -> "ma"
string left = str.Substring(0, iLeft); // "program" -> "p"
string leftRev = Reverse(left); // "p" -> "p"
//Shave off extra chars in rightRev and leftRev
// When input = "message", this loop converts "meegassageem" to "megassagem",
// ("ee" to "e"), as long as the extra 'e' is an inserted char
while (left.Length > 0 && rightRev.Length > 0 &&
left[left.Length - 1] == rightRev[0])
{
rightRev = rightRev.Substring(1);
leftRev = leftRev.Substring(1);
}
//piece together the result
string result = left + rightRev + ch + insidePal + ch + right + leftRev;
//find the shortest result for inputs that have multiple repeated characters
if (shortestResult == null || result.Length < shortestResult.Length)
shortestResult = result;
}
return shortestResult;
}
else
{
//For inputs that have no repeated characters,
// just mirror the characters using the last character as the pivot.
for (int i = str.Length - 2; i >= 0; i--)
{
str += str[i];
}
return str;
}
}
Note that you need a Reverse function:
public static string Reverse(string str)
{
string result = "";
for (int i = str.Length - 1; i >= 0; i--)
{
result += str[i];
}
return result;
}
C# Recursive solution adding to the end of the string:
There are 2 base cases. When length is 1 or 2. Recursive case: If the extremes are equal, then
make palindrome the inner string without the extremes and return that with the extremes.
If the extremes are not equal, then add the first character to the end and make palindrome the
inner string including the previous last character. return that.
public static string ConvertToPalindrome(string str) // By only adding characters at the end
{
if (str.Length == 1) return str; // base case 1
if (str.Length == 2 && str[0] == str[1]) return str; // base case 2
else
{
if (str[0] == str[str.Length - 1]) // keep the extremes and call
return str[0] + ConvertToPalindrome(str.Substring(1, str.Length - 2)) + str[str.Length - 1];
else //Add the first character at the end and call
return str[0] + ConvertToPalindrome(str.Substring(1, str.Length - 1)) + str[0];
}
}

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