I'm trying to do some programming homework but I cant figure out how to display the last N characters of a C string. This is my attempt at it so far. I am also supposed to ask for the number of characters and validate it. Any help would be greatly appreciated.
void choice_4(char str[]) {
int characters;
cout << "How many characters from the end of the string do you want to display? ";
cin >> characters;
if (str[characters] != '\0')
cout<<str.Substring(str.length - characters,characters)
}
As usual with homework questions, I won't give a solution but a few hints.
I assume by “validate” you mean check whether the string is long enough. For example, you cannot show the last 12 characters of a string that is only 7 characters long. Your current attempt looking at the n-th byte of the string cannot work, however. If the string is shorter than n bytes, you'll index it out of range and invoke undefined behavior. If it is longer – which is perfectly valid and, in fact, will be the case except for trivial cases – your test wrongly returns that the requested length is invalid.
What you should do instead is computing the length N of the string and then test whether n ≤ N. You can use the standard library function std::strlen to obtain the length of a NUL terminated character array. Or you can loop it yourself and count how many bytes you see until the first NUL byte.
A C-style string is just a pointer to a byte in memory with the implicit contract that any bytes up to the first NUL byte that follow it belong to the string. Therefore, if you add m ≤ N to the pointer, you get the sub-string starting at the m-th (zero-based) byte.
Therefore, in order to get the sub-string with the last n characters of a string with N characters, how do you determine m?
By the way: A NUL byte is a char with the integer value 0. You can encode it as '\0' (as you did) but 0 works perfectly fine, too.
Related
I am doing this problem https://www.spoj.com/problems/DIVSTR/
We are given two strings S and T.
S is divisible by string T if there is some non-negative integer k, which satisfies the equation S=k*T
What is the minimum number of characters which should be removed from S, so that S is divisible by T?
The main idea was to match T with S using a pointer and count the number of instances of T occurring in S when the count is done, bring the pointer to the start of T and if there's a mismatch, compare T's first letter with S's present letter.
This code is working totally fine with test cases they provided and custom test cases I gave, but it could not get through hidden test cases.
this is the code
def no_of_letters(string1,string2):
# print(len(string1),len(string2))
count = 0
pointer = 0
if len(string1)<len(string2):
return len(string1)
if (len(string1)==len(string2)) and (string1!=string2):
return len(string1)
for j in range(len(string1)):
if (string1[j]==string2[pointer]) and pointer<(len(string2)-1):
pointer+=1
elif (string1[j]==string2[pointer]) and pointer == (len(string2)-1):
count+=1
pointer=0
elif (string1[j]!=string2[pointer]):
if string1[j]==string2[0]:
pointer=1
else:
pointer = 0
return len(string1)-len(string2)*count
One place where I think there should be confusion is when same letters can be parts of two counts, but it should not be a problem, because our answer doesn't need to take overlapping into account.
for example, S = 'akaka' T= 'aka' will give the output 2, irrespective of considering first 'aka',ka as count or second ak,'aka'.
I believe that the solution is much more straightforward that you make it. You're simply trying to find how many times the characters of T appear, in order, in S. Everything else is the characters you remove. For instance, given RobertBaron's example of S="akbaabka" and T="aka", you would write your routine to locate the characters a, k, a, in that order, from the start of S:
akbaabka
ak a^
# with some pointer, ptr, now at position 4, marked with a caret above
With that done, you can now recur on the remainder of the string:
find_chars(S[ptr:], T)
With each call, you look for T in S; if you find it, count 1 repetition and recur on the remainder of S; if not, return 0 (base case). As you crawl back up your recursion stack, accumulate all the 1 counts, and there is your value of k.
The quantity of chars to remove is len(s) - k*len(T).
Can you take it from there?
I'm making a simple Cocoa program that can encode text to binary and decode it back to text. I tried to make this script and I was not even close to accomplishing this. Can anyone help me? This has to include two textboxes and two buttons or whatever is best, Thanks!
There are two parts to this.
The first is to encode the characters of the string into bytes. You do this by sending the string a dataUsingEncoding: message. Which encoding you choose will determine which bytes it gives you for each character. Start with NSUTF8StringEncoding, and then experiment with other encodings, such as NSUnicodeStringEncoding, once you get it working.
The second part is to convert every bit of every byte into either a '0' character or a '1' character, so that, for example, the letter A, encoded in UTF-8 to a single byte, will be represented as 01000001.
So, converting characters to bytes, and converting bytes to characters representing bits. These two are completely separate tasks; the second part should work correctly for any stream of bytes, including any valid stream of encoded characters, any invalid stream of encoded characters, and indeed anything that isn't text at all.
The first part is easy enough:
- (NSString *) stringOfBitsFromEncoding:(NSStringEncoding)encoding
ofString:(NSString *)inputString
{
//Encode the characters to bytes using the UTF-8 encoding. The bytes are contained in an NSData object, which we receive.
NSData *data = [string dataUsingEncoding:NSUTF8StringEncoding];
//I did say these were two separate jobs.
return [self stringOfBitsFromData:data];
}
For the second part, you'll need to loop through the bytes of the data. A C for loop will do the job there, and that will look like this:
//This is the method we're using above. I'll leave out the method signature and let you fill that in.
- …
{
//Find out how many bytes the data object contains.
NSUInteger length = [data length];
//Get the pointer to those bytes. “const” here means that we promise not to change the values of any of the bytes. (The compiler may give a warning if we don't include this, since we're not allowed to change these bytes anyway.)
const char *bytes = [data bytes];
//We'll store the output here. There are 8 bits per byte, and we'll be putting in one character per bit, so we'll tell NSMutableString that it should make room for (the number of bytes times 8) characters.
NSMutableString *outputString = [NSMutableString stringWithCapacity:length * 8];
//The loop. We start by initializing i to 0, then increment it (add 1 to it) after each pass. We keep looping as long as i < length; when i >= length, the loop ends.
for (NSUInteger i = 0; i < length; ++i) {
char thisByte = bytes[i];
for (NSUInteger bitNum = 0; bitNum < 8; ++bitNum) {
//Call a function, which I'll show the definition of in a moment, that will get the value of a bit at a given index within a given character.
bool bit = getBitAtIndex(thisByte, bitNum);
//If this bit is a 1, append a '1' character; if it is a 0, append a '0' character.
[outputString appendFormat: #"%c", bit ? '1' : '0'];
}
}
return outputString;
}
Bits 101 (or, 1100101)
Bits are literally just digits in base 2. Humans in the Western world usually write out numbers in base 10, but a number is a number no matter what base it's written in, and every character, and every byte, and indeed every bit, is just a number.
Digits—including bits—are counted up from the lowest place, according to the exponent to which the base is raised to find the magnitude of that place. We want bits, so that base is 2, so our place values are:
2^0 = 1: The ones place (the lowest bit)
2^1 = 2: The twos place (the next higher bit)
2^2 = 4: The fours place
2^3 = 8: The eights place
And so on, up to 2^7. (Note that the highest exponent is exactly one lower than the number of digits we're after; in this case, 7 vs. 8.)
If that all reminds you of reading about “the ones place”, “the tens place”, “the hundreds place”, etc. when you were a kid, it should: it's the exact same principle.
So a byte such as 65, which (in UTF-8) completely represents the character 'A', is the sum of:
2^7 × 0 = 0
+ 2^6 × 0 = 64
+ 2^5 × 1 = 0
+ 2^4 × 0 = 0
+ 2^3 × 0 = 0
+ 2^2 × 0 = 0
+ 2^1 × 0 = 0
+ 2^0 × 1 = 1
= 0 + 64 +0+0+0+0+0 + 1
= 64 + 1
= 65
Back when you learned base 10 numbers as a kid, you probably noticed that ten is “10”, one hundred is “100”, etc. This is true in base 2 as well: as 10^x is “1” followed by x “0”s in base 10, so is 2^x “1” followed by “x” 0s in base 2. So, for example, sixty-four in base 2 is “1000000” (count the zeroes and compare to the table above).
We are going to use these exact-power-of-two numbers to test each bit in each input byte.
Finding the bit
C has a pair of “shift” operators that will insert zeroes or remove digits at the low end of a number. The former is called “shift left”, and is written as <<, and you can guess the opposite.
We want shift left. We want to shift 1 left by the number of the bit we're after. That is exactly equivalent to raising 2 (our base) to the power of that number; for example, 1 << 6 = 2^6 = “1000000”.
Testing the bit
C has an operator for bit testing, too; it's &, the bitwise AND operator. (Do not confuse this with &&, which is the logical AND operator. && is for using whole true/false values in making decisions; & is one of your tools for working with bits within values.)
Strictly speaking, & does not test single bits; it goes through the bits of both input values, and returns a new value whose bits are the bitwise AND of each input pair. So, for example,
01100101
& 00101011
----------
00100001
Each bit in the output is 1 if and only if both of the corresponding input bits were also 1.
Putting these two things together
We're going to use the shift left operator to give us a number where one bit, the nth bit, is set—i.e., 2^n—and then use the bitwise AND operator to test whether the same bit is also set in our input byte.
//This is a C function that takes a char and an int, promising not to change either one, and returns a bool.
bool getBitAtIndex(const char byte, const int bitNum)
//It could also be a method, which would look like this:
//- (bool) bitAtIndex:(const int)bitNum inByte:(const char)byte
//but you would have to change the code above. (Feel free to try it both ways.)
{
//Find 2^bitNum, which will be a number with exactly 1 bit set. For example, when bitNum is 6, this number is “1000000”—a single 1 followed by six 0s—in binary.
const int powerOfTwo = 1 << bitNum;
//Test whether the same bit is also set in the input byte.
bool bitIsSet = byte & powerOfTwo;
return bitIsSet;
}
A bit of magic I should acknowledge
The bitwise AND operator does not evaluate to a single bit—it does not evaluate to only 1 or 0. Remember the above example, in which the & operator returned 33.
The bool type is a bit magic: Any time you convert any value to bool, it automatically becomes either 1 or 0. Anything that is not 0 becomes 1; anything that is 0 becomes 0.
The Objective-C BOOL type does not do this, which is why I used bool in the code above. You are free to use whichever you prefer, except that you generally should use BOOL whenever you deal with anything that expects a BOOL, particularly when overriding methods in subclasses or implementing protocols. You can convert back and forth freely, though not losslessly (since bool will change non-zero values as described above).
Oh yeah, you said something about text boxes too
When the user clicks on your button, get the stringValue of your input field, call stringOfBitsFromEncoding:ofString: using a reasonable encoding (such as UTF-8) and that string, and set the resulting string as the new stringValue of your output field.
Extra credit: Add a pop-up button with which the user can choose an encoding.
Extra extra credit: Populate the pop-up button with all of the available encodings, without hard-coding or hard-nibbing a list.
the logic behind this was (n-2)3^(n-3) has lots of repetitons like (abc)***(abc) when abc is at start and at end and the strings repated total to 3^4 . similarly as abc moves ahead and number of sets of (abc) increase
You can use dynamic programming to compute the number of forbidden strings.
The algorithms follow from the observation below:
"Legal string of size n is the legal string of size n - 1 extended with one letter, so that the last three letters of the resulting string are not all distinct."
So if we had all the legal strings of size n-1 we could try extending them to obtain the legal strings of size n.
To check whether the extended string is legal we just need to know the last two letters of the previous string (of size n-1).
In the algorithm we will compute two arrays, where
different[i] # number of legal strings of length i in which last two letters are different
same[i] # number of legal strings of length i in which last two letters are the same
It can be easily proved that:
different[i+1] = different[i] + 2*same[i]
same[i+1] = different[i] + same[i]
It is the consequence of the following facts:
Any 'same' string of size i+1 can be obtained either from 'same' string of size i (think BB -> BBB) or from 'different' string (think AB -> ABB) and these are the only options.
Any 'different' string of size i+1 can be obtained either from 'different' string of size i (think AB-> ABA ) or from the 'same' string in two ways (AA -> AAB or AA -> AAC)
Having observed all this it is easy to write an algorithm that computes the result in O(n) time.
I suggest you use recursion, and look at two numbers:
F(n), the number of legal strings of length n whose last two symbols are the same.
G(n), the number of legal strings of length n whose last two symbols are different.
Is that enough to go on?
get the ASCII values of the last three letters and add the square values of these letters. If it gives a certain result, then it is forbidden. For A, B and C, it would be fine.
To do this:
1) find out how to get characters from your string.
2) find out how to get ASCII value of a character.
3) Multiply these ASCII values with themselves.
4) Do that for the three letters each time and add their values.
If string A and string B contain the same characters, they are called "brother string".
for example: "abc" and "cab", "aabb" and "baab".
The question is how to check if two strings are brother string(fast)?
Sort them then compare, or keep a count of each character in a map of some sort then compare counts at the end.
Just count how many times each character is present in the string. And them compare the counts for the two strings you have.
If the strings are always ASCII or some 8-bit encoding, simple array is good enough for the counts.
If they can contain Unicode characters, use a hash map.
The fastest algorithm in this case has a complexity of O(n) where n is the length of the longest string.
Infact in O(n) you can create an array (one for each string) where the characters are stored. Besides, you need another O(n) time to do the test.
What about have an array of all characters and to count the number of a's b's etc'
than compare the two array's
Let me show my variant. Each char has its int ASCII value. So I think, you may multiply all chars for both strings and compare two products. For example:
private static boolean compareForBrother(String s1, String s2) {
long lProduct= 1L;
for (byte b : s1.getBytes()) {
lProduct *= b;
}
long lProduct2= 1L;
for (byte b : s2.getBytes()) {
lProduct2 *= b;
}
return (lProduct2 == lProduct);
}
Compare the set of characters in each string.
In python, something like:
if set(stringA) == set(stringB):
print("%s and %s are brother strings" % (stringA, stringB))
Prepare a histogram of character frequencies; this is fwiw exactly the same process as a radix sort. Then compare the histograms.
Given a dictionary find out if given word can be made by two words in dictionary. For eg. given "newspaper" you have to find if it can be made by two words. (news and paper in this case). Only thing i can think of is starting from beginning and checking if current string is a word. In this case checking n, ne, new, news..... check for the remaining part if current string is a valid word.
Also how do you generalize it for k(means if a word is made up of k words) ? Any thoughts?
Starting your split at the center may yield results faster. For example, for newspaper, you would first try splitting at 'news paper' or 'newsp aper'. As you can see, for this example, you would find your result on the first or second try. If you do not find a result, just search outwards. See the example for 'crossbow' below:
cros sbow
cro ssbow
cross bow
For the case with two words, the problem can be solved by just considering all possible ways of splitting the word into two, then checking each half to see if it's a valid word. If the input string has length n, then there are only O(n) different ways of splitting the string. If you store the strings in a structure supporting fast lookup (say, a trie, or hash table).
The more interesting case is when you have k > 2 words to split the word into. For this, we can use a really elegant recursive formulation:
A word can be split into k words if it can be split into a word followed by a word splittable into k - 1 words.
The recursive base case would be that a word can be split into zero words only if it's the empty string, which is trivially true.
To use this recursive insight, we'll modify the original algorithm by considering all possible splits of the word into two parts. Once we have that split, we can check if the first part of the split is a word and if the second part of the split can be broken apart into k - 1 words. As an optimization, we don't recurse on all possible splits, but rather just on those where we know the first word is valid. Here's some sample code written in Java:
public static boolean isSplittable(String word, int k, Set<String> dictionary) {
/* Base case: If the string is empty, we can only split into k words and vice-
* versa.
*/
if (word.isEmpty() || k == 0)
return word.isEmpty() && k == 0;
/* Generate all possible non-empty splits of the word into two parts, recursing on
* problems where the first word is known to be valid.
*
* This loop is structured so that we always try pulling off at least one letter
* from the input string so that we don't try splitting the word into k pieces
* of which some are empty.
*/
for (int i = 1; i <= word.length(); ++i) {
String first = word.substring(0, i), last = word.substring(i);
if (dictionary.contains(first) &&
isSplittable(last, k - 1, dictionary)
return true;
}
/* If we're here, then no possible split works in this case and we should signal
* that no solution exists.
*/
return false;
}
}
This code, in the worst case, runs in time O(nk) because it tries to generate all possible partitions of the string into k different pieces. Of course, it's unlikely to hit this worst-case behavior because most possible splits won't end up forming any words.
I'd first loop through the dictionary using a strpos(-like) function to check if it occurs at all. Then try if you can find a match with the results.
So it would do something like this:
Loop through the dictionary strpos-ing every word in the dictionary and saving results into an array, let's say it gives me the results 'new', 'paper', and 'news'.
Check if new+paper==newspaper, check if new+news==newspaper, etc, untill you get to paper+news==newspaper which returns.
Not sure if it is a good method though, but it seems more efficient than checking a word letter for letter (more iterations) and you didn't explain how you'd check when the second word started.
Don't know what you mean by 'how do you generalize it for k'.