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PCRE2MATCHING(3)					      PCRE2MATCHING(3)

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 documenta‐
       tion 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 alter‐
       native  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 rep‐
       resented	 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  Expres‐
       sions",	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  alterna‐
       tives  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 possi‐
       ble 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 rela‐
       tively straightforward for this algorithm to keep  track	 of  the  sub‐
       strings	that  are  matched  by portions of the pattern in parentheses.
       This provides support for capturing parentheses and back references.

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 long‐
       est.  The  matches are returned in decreasing order of length. There is
       an option to stop the algorithm after the first match (which is	neces‐
       sarily 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  automati‐
       cally move on to find matches that start at later positions.

       PCRE2's "auto-possessification" optimization usually applies to charac‐
       ter repeats at the end of a pattern (as well as internally). For	 exam‐
       ple, 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_POS‐
       SESS option when compiling.

       There are a number of features of PCRE2 regular	expressions  that  are
       not  supported  by the alternative matching algorithm. They are as fol‐
       lows:

       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 sub‐
       strings are available.

       3. Because no substrings are captured, back references within the  pat‐
       tern are not supported, and cause errors if encountered.

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

       5.  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. It causes an
       error if encountered.

       6. 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.

       7.  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 sub‐
       ject string one character (not code unit) at a  time,  for  all	active
       paths through the tree.

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

ADVANTAGES OF THE ALTERNATIVE ALGORITHM

       Using  the alternative matching algorithm provides the following advan‐
       tages:

       1. All possible matches (at a single point in the subject) are automat‐
       ically  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 pos‐
       sible  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 algo‐
       rithm, by retaining partially matched substrings, it  is	 more  compli‐
       cated. 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 and back references 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: 29 September 2014
       Copyright (c) 1997-2014 University of Cambridge.

PCRE2 10.00		       29 September 2014	      PCRE2MATCHING(3)
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