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NAME

       PCRE2 - Perl-compatible regular expressions (revised API)

PCRE2 MATCHING ALGORITHMS


       This  document  describes  the  two  different  algorithms that are available in PCRE2 for
       matching a compiled regular expression against a  given  subject  string.  The  "standard"
       algorithm  is the one provided by the pcre2_match() function. This works in the same as as
       Perl's matching function, and provide a Perl-compatible matching operation.  The  just-in-
       time (JIT) optimization that is described in the pcre2jit documentation is compatible with
       this function.

       An alternative algorithm is provided by the pcre2_dfa_match() function; it operates  in  a
       different   way,   and  is  not  Perl-compatible.  This  alternative  has  advantages  and
       disadvantages compared with the standard algorithm, and these are described below.

       When there is only one possible way in which a given subject string can match  a  pattern,
       the  two  algorithms  give  the  same answer. A difference arises, however, when there are
       multiple possibilities. For example, if the pattern

         ^<.*>

       is matched against the string

         <something> <something else> <something further>

       there are three possible answers. The standard algorithm finds only one of  them,  whereas
       the alternative algorithm finds all three.

REGULAR EXPRESSIONS AS TREES


       The  set  of strings that are matched by a regular expression can be represented as a tree
       structure. An unlimited repetition in the pattern makes the tree of infinite size, but  it
       is  still  a  tree.  Matching the pattern to a given subject string (from a given starting
       point) can be thought of as a search of the tree.  There are two ways to  search  a  tree:
       depth-first  and  breadth-first,  and  these  correspond  to  the  two matching algorithms
       provided by PCRE2.

THE STANDARD MATCHING ALGORITHM


       In the terminology of Jeffrey Friedl's book "Mastering Regular Expressions", the  standard
       algorithm  is  an  "NFA  algorithm". It conducts a depth-first search of the pattern tree.
       That is, it proceeds along a single path through  the  tree,  checking  that  the  subject
       matches  what  is required. When there is a mismatch, the algorithm tries any alternatives
       at the current point, and if they all fail, it backs up to the previous  branch  point  in
       the tree, and tries the next alternative branch at that level. This often involves backing
       up (moving to the left) in the subject string as  well.  The  order  in  which  repetition
       branches are tried is controlled by the greedy or ungreedy nature of the quantifier.

       If  a  leaf  node  is  reached,  a  matching  string has been found, and at that point the
       algorithm stops. Thus, if there is more than one possible match,  this  algorithm  returns
       the  first  one  that  it  finds.  Whether  this  is  the  shortest,  the longest, or some
       intermediate length depends on the way the greedy and ungreedy repetition quantifiers  are
       specified in the pattern.

       Because  it  ends up with a single path through the tree, it is relatively straightforward
       for this algorithm to keep track of the substrings that are matched  by  portions  of  the
       pattern   in   parentheses.   This   provides   support   for  capturing  parentheses  and
       backreferences.

THE ALTERNATIVE MATCHING ALGORITHM


       This algorithm conducts a breadth-first search  of  the  tree.  Starting  from  the  first
       matching  point  in  the  subject,  it  scans the subject string from left to right, once,
       character by character, and as it does this, it remembers all the paths through  the  tree
       that  represent valid matches. In Friedl's terminology, this is a kind of "DFA algorithm",
       though it is not implemented as a traditional finite  state  machine  (it  keeps  multiple
       states active simultaneously).

       Although  the  general  principle  of this matching algorithm is that it scans the subject
       string only once,  without  backtracking,  there  is  one  exception:  when  a  lookaround
       assertion  is encountered, the characters following or preceding the current point have to
       be independently inspected.

       The scan continues until either the end of the subject is reached, or there  are  no  more
       unterminated  paths.  At  this  point,  terminated  paths represent the different matching
       possibilities (if there are none, the match has failed).  Thus, if there is more than  one
       possible match, this algorithm finds all of them, and in particular, it finds the longest.
       The matches are returned in decreasing order of length. There is an  option  to  stop  the
       algorithm after the first match (which is necessarily the shortest) is found.

       Note  that  all  the matches that are found start at the same point in the subject. If the
       pattern

         cat(er(pillar)?)?

       is matched against the string "the caterpillar catchment", the result is the three strings
       "caterpillar",  "cater",  and  "cat" that start at the fifth character of the subject. The
       algorithm does not automatically move on to find matches that start at later positions.

       PCRE2's "auto-possessification" optimization usually applies to character repeats  at  the
       end  of  a pattern (as well as internally). For example, the pattern "a\d+" is compiled as
       if it were "a\d++"  because  there  is  no  point  even  considering  the  possibility  of
       backtracking into the repeated digits. For DFA matching, this means that only one possible
       match is found. If you really do want multiple  matches  in  such  cases,  either  use  an
       ungreedy repeat ("a\d+?") or set the PCRE2_NO_AUTO_POSSESS option when compiling.

       There  are  a  number  of  features of PCRE2 regular expressions that are not supported or
       behave differently in the alternative matching function.  Those  that  are  not  supported
       cause an error if encountered.

       1.  Because  the  algorithm  finds  all possible matches, the greedy or ungreedy nature of
       repetition quantifiers is not relevant (though it  may  affect  auto-possessification,  as
       just  described).  During matching, greedy and ungreedy quantifiers are treated in exactly
       the same way. However, possessive quantifiers can make  a  difference  when  what  follows
       could also match what is quantified, for example in a pattern like this:

         ^a++\w!

       This  pattern  matches  "aaab!" but not "aaa!", which would be matched by a non-possessive
       quantifier. Similarly, if an atomic group is present, it  is  matched  as  if  it  were  a
       standalone pattern at the current point, and the longest match is then "locked in" for the
       rest of the overall pattern.

       2.  When  dealing  with  multiple  paths  through  the  tree  simultaneously,  it  is  not
       straightforward   to  keep  track  of  captured  substrings  for  the  different  matching
       possibilities, and PCRE2's implementation of this algorithm does not attempt to  do  this.
       This means that no captured substrings are available.

       3.  Because  no  substrings  are  captured,  backreferences  within  the  pattern  are not
       supported.

       4. For the same reason, conditional expressions that use a backreference as the  condition
       or test for a specific group recursion are not supported.

       5. Again for the same reason, script runs are not supported.

       6. Because many paths through the tree may be active, the \K escape sequence, which resets
       the start of the match when encountered (but may be on some paths and not on  others),  is
       not supported.

       7.  Callouts  are  supported,  but the value of the capture_top field is always 1, and the
       value of the capture_last field is always 0.

       8. The \C escape sequence, which (in the standard algorithm) always matches a single  code
       unit,  even  in  a  UTF  mode,  is  not  supported in these modes, because the alternative
       algorithm moves through the subject string one character (not code unit) at  a  time,  for
       all active paths through the tree.

       9.  Except for (*FAIL), the backtracking control verbs such as (*PRUNE) are not supported.
       (*FAIL) is supported, and behaves like a failing negative assertion.

       10.  The  PCRE2_MATCH_INVALID_UTF  option  for  pcre2_compile()  is   not   supported   by
       pcre2_dfa_match().

ADVANTAGES OF THE ALTERNATIVE ALGORITHM


       Using the alternative matching algorithm provides the following advantages:

       1. All possible matches (at a single point in the subject) are automatically found, and in
       particular, the longest match is found. To find more than one  match  using  the  standard
       algorithm, you have to do kludgy things with callouts.

       2.  Because  the alternative algorithm scans the subject string just once, and never needs
       to backtrack (except for lookbehinds), it is possible to pass very long subject strings to
       the matching function in several pieces, checking for partial matching each time. Although
       it is also possible  to  do  multi-segment  matching  using  the  standard  algorithm,  by
       retaining   partially  matched  substrings,  it  is  more  complicated.  The  pcre2partial
       documentation gives details of partial matching and discusses multi-segment matching.

DISADVANTAGES OF THE ALTERNATIVE ALGORITHM


       The alternative algorithm suffers from a number of disadvantages:

       1. It is substantially slower than the standard algorithm. This is partly because  it  has
       to  search  for  all  possible  matches,  but  is  also  because it is less susceptible to
       optimization.

       2. Capturing parentheses, backreferences, script runs, and  matching  within  invalid  UTF
       string are not supported.

       3.  Although  atomic  groups  are  supported,  their  use does not provide the performance
       advantage that it does for the standard algorithm.

AUTHOR


       Philip Hazel
       University Computing Service
       Cambridge, England.

REVISION


       Last updated: 23 May 2019
       Copyright (c) 1997-2019 University of Cambridge.