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HTTP Parameter Pollution (HPP) is a web application vulnerability exploited by injecting encoded query string delimiters in already existing parameters. The vulnerability occurs if user input is not correctly encoded for output by a web application. [1] This vulnerability allows the injection of parameters into web application-created URLs.
We assume all the substrings have a fixed length m. A naïve way to search for k patterns is to repeat a single-pattern search taking O(n+m) time, totaling in O((n+m)k) time. In contrast, the above algorithm can find all k patterns in O(n+km) expected time, assuming that a hash table check works in O(1) expected time.
The string spelled by the edges from the root to such a node is a longest repeated substring. The problem of finding the longest substring with at least k {\displaystyle k} occurrences can be solved by first preprocessing the tree to count the number of leaf descendants for each internal node, and then finding the deepest node with at least k ...
The longest common substrings of a set of strings can be found by building a generalized suffix tree for the strings, and then finding the deepest internal nodes which have leaf nodes from all the strings in the subtree below it. The figure on the right is the suffix tree for the strings "ABAB", "BABA" and "ABBA", padded with unique string ...
If n is greater than the length of the string then most implementations return the whole string (exceptions exist – see code examples). Note that for variable-length encodings such as UTF-8, UTF-16 or Shift-JIS, it can be necessary to remove string positions at the end, in order to avoid invalid strings.
Map all occurrences of a, e, i, o, u, y, h, w. to zero(0) Replace all consonants (include the first letter) with digits as in [2.] above. Replace all adjacent same digits with one digit, and then remove all the zero (0) digits; If the saved letter's digit is the same as the resulting first digit, remove the digit (keep the letter).
In computer science, the Knuth–Morris–Pratt algorithm (or KMP algorithm) is a string-searching algorithm that searches for occurrences of a "word" W within a main "text string" S by employing the observation that when a mismatch occurs, the word itself embodies sufficient information to determine where the next match could begin, thus bypassing re-examination of previously matched characters.
A basic example of string searching is when the pattern and the searched text are arrays of elements of an alphabet Σ. Σ may be a human language alphabet, for example, the letters A through Z and other applications may use a binary alphabet (Σ = {0,1}) or a DNA alphabet (Σ = {A,C,G,T}) in bioinformatics .