package strings;
import java.util.HashMap;
/**
* This class is not thread safe<br>
* <br>
* (From wikipedia) In computer science, the Boyer–Moore–Horspool algorithm or Horspool's algorithm
* is an algorithm for finding substrings in strings. It was published by Nigel Horspool in 1980.
* <br>
* <a href=https://en.wikipedia.org/wiki/Boyer%E2%80%93Moore%E2%80%93Horspool_algorithm>Wikipedia
* page</a><br>
* <br>
*
* <p>An explanation:<br>
*
* <p>The Horspool algorithm is a simplification of the Boyer-Moore algorithm in that it uses only
* one of the two heuristic methods for increasing the number of characters shifted when finding a
* bad match in the text. This method is usually called the "bad symbol" or "bad character" shift.
* The bad symbol shift method is classified as an input enhancement method in the theory of
* algorithms. Input enhancement is (from wikipedia) the principle that processing a given input to
* a problem and altering it in a specific way will increase runtime efficiency or space efficiency,
* or both. Both algorithms try to match the pattern and text comparing the pattern symbols to the
* text's from right to left.<br>
* <br>
*
* <p>In the bad symbol shift method, a table is created prior to the search, called the "bad symbol
* table". The bad symbol table contains the shift values for any symbol in the text and pattern.
* For these symbols, the value is the length of the pattern, if the symbol is not in the first
* (length - 1) of the pattern. Else it is the distance from its rightmost occurrence in the pattern
* to the last symbol of the pattern. In practice, we only calculate the values for the ones that
* exist in the first (length - 1) of the pattern.<br>
* <br>
*
* <p>For more details on the algorithm and the more advanced Boyer-Moore I recommend checking out
* the wikipedia page and professor Anany Levitin's book: Introduction To The Design And Analysis Of
* Algorithms.
*/
public class HorspoolSearch {
private static HashMap<Character, Integer> shiftValues; // bad symbol table
private static Integer patternLength;
private static int comparisons = 0; // total comparisons in the current/last search
/**
* Case sensitive version version of the algorithm
*
* @param pattern the pattern to be searched for (needle)
* @param text the text being searched in (haystack)
* @return -1 if not found or first index of the pattern in the text
*/
public static int findFirst(String pattern, String text) {
return firstOccurrence(pattern, text, true);
}
/**
* Case insensitive version version of the algorithm
*
* @param pattern the pattern to be searched for (needle)
* @param text the text being searched in (haystack)
* @return -1 if not found or first index of the pattern in the text
*/
public static int findFirstInsensitive(String pattern, String text) {
return firstOccurrence(pattern, text, false);
}
/**
* Utility method that returns comparisons made by last run (mainly for tests)
*
* @return number of character comparisons of the last search
*/
public static Integer getLastComparisons() {
return HorspoolSearch.comparisons;
}
/**
* Fairly standard implementation of the Horspool algorithm. Only the index of the last character
* of the pattern on the text is saved and shifted by the appropriate amount when a mismatch is
* found. The algorithm stops at the first match or when the entire text has been exhausted.
*
* @param pattern String to be matched in the text
* @param text text String
* @return index of first occurrence of the pattern in the text
*/
private static int firstOccurrence(String pattern, String text, boolean caseSensitive) {
shiftValues = calcShiftValues(pattern); // build the bad symbol table
comparisons = 0; // reset comparisons
int textIndex =
pattern.length() - 1; // align pattern with text start and get index of the last character
// while pattern is not out of text bounds
while (textIndex < text.length()) {
// try to match pattern with current part of the text starting from last character
int i = pattern.length() - 1;
while (i >= 0) {
comparisons++;
char patternChar = pattern.charAt(i);
char textChar = text.charAt((textIndex + i) - (pattern.length() - 1));
if (!charEquals(patternChar, textChar, caseSensitive)) { // bad character, shift pattern
textIndex += getShiftValue(text.charAt(textIndex));
break;
}
i--;
}
// check for full match
if (i == -1) {
return textIndex - pattern.length() + 1;
}
}
// text exhausted, return failure
return -1;
}
/**
* Compares the argument characters
*
* @param c1 first character
* @param c2 second character
* @param caseSensitive boolean determining case sensitivity of comparison
* @return truth value of the equality comparison
*/
private static boolean charEquals(char c1, char c2, boolean caseSensitive) {
if (caseSensitive) {
return c1 == c2;
}
return Character.toLowerCase(c1) == Character.toLowerCase(c2);
}
/**
* Builds the bad symbol table required to run the algorithm. The method starts from the second to
* last character of the pattern and moves to the left. When it meets a new character, it is by
* definition its rightmost occurrence and therefore puts the distance from the current index to
* the index of the last character into the table. If the character is already in the table, then
* it is not a rightmost occurrence, so it continues.
*
* @param pattern basis for the bad symbol table
* @return the bad symbol table
*/
private static HashMap<Character, Integer> calcShiftValues(String pattern) {
patternLength = pattern.length();
HashMap<Character, Integer> table = new HashMap<>();
for (int i = pattern.length() - 2;
i >= 0;
i--) { // length - 2 is the index of the second to last character
char c = pattern.charAt(i);
int finalI = i;
table.computeIfAbsent(c, k -> pattern.length() - 1 - finalI);
}
return table;
}
/**
* Helper function that uses the bad symbol shift table to return the appropriate shift value for
* a given character
*
* @param c character
* @return shift value that corresponds to the character argument
*/
private static Integer getShiftValue(char c) {
if (shiftValues.get(c) != null) {
return shiftValues.get(c);
} else {
return patternLength;
}
}
}