/// A contiguous NFA implementation of Aho-Corasick. /// /// When possible, prefer using [`AhoCorasick`](crate::AhoCorasick) instead of /// this type directly. Using an `NFA` directly is typically only necessary /// when one needs access to the [`Automaton`] trait implementation. /// /// This NFA can only be built by first constructing a [`noncontiguous::NFA`]. /// Both [`NFA::new`] and [`Builder::build`] do this for you automatically, but /// [`Builder::build_from_noncontiguous`] permits doing it explicitly. /// /// The main difference between a noncontiguous NFA and a contiguous NFA is /// that the latter represents all of its states and transitions in a single /// allocation, where as the former uses a separate allocation for each state. /// Doing this at construction time while keeping a low memory footprint isn't /// feasible, which is primarily why there are two different NFA types: one /// that does the least amount of work possible to build itself, and another /// that does a little extra work to compact itself and make state transitions /// faster by making some states use a dense representation. /// /// Because a contiguous NFA uses a single allocation, there is a lot more /// opportunity for compression tricks to reduce the heap memory used. Indeed, /// it is not uncommon for a contiguous NFA to use an order of magnitude less /// heap memory than a noncontiguous NFA. Since building a contiguous NFA /// usually only takes a fraction of the time it takes to build a noncontiguous /// NFA, the overall build time is not much slower. Thus, in most cases, a /// contiguous NFA is the best choice. /// /// Since a contiguous NFA uses various tricks for compression and to achieve /// faster state transitions, currently, its limit on the number of states /// is somewhat smaller than what a noncontiguous NFA can achieve. Generally /// speaking, you shouldn't expect to run into this limit if the number of /// patterns is under 1 million. It is plausible that this limit will be /// increased in the future. If the limit is reached, building a contiguous NFA /// will return an error. Often, since building a contiguous NFA is relatively /// cheap, it can make sense to always try it even if you aren't sure if it /// will fail or not. If it does, you can always fall back to a noncontiguous /// NFA. (Indeed, the main [`AhoCorasick`](crate::AhoCorasick) type employs a /// strategy similar to this at construction time.) /// /// # Example /// /// This example shows how to build an `NFA` directly and use it to execute /// [`Automaton::try_find`]: /// /// ``` /// use aho_corasick::{ /// automaton::Automaton, /// nfa::contiguous::NFA, /// Input, Match, /// }; /// /// let patterns = &["b", "abc", "abcd"]; /// let haystack = "abcd"; /// /// let nfa = NFA::new(patterns).unwrap(); /// assert_eq!( /// Some(Match::must(0, 1..2)), /// nfa.try_find(&Input::new(haystack))?, /// ); /// # Ok::<(), Box<dyn std::error::Error>>(()) /// ``` /// /// It is also possible to implement your own version of `try_find`. See the /// [`Automaton`] documentation for an example. #[derive(Clone)] pubstruct NFA { /// The raw NFA representation. Each state is packed with a header /// (containing the format of the state, the failure transition and, for /// a sparse state, the number of transitions), its transitions and any /// matching pattern IDs for match states.
repr: Vec<u32>, /// The length of each pattern. This is used to compute the start offset /// of a match.
pattern_lens: Vec<SmallIndex>, /// The total number of states in this NFA.
state_len: usize, /// A prefilter for accelerating searches, if one exists.
prefilter: Option<Prefilter>, /// The match semantics built into this NFA.
match_kind: MatchKind, /// The alphabet size, or total number of equivalence classes, for this /// NFA. Dense states always have this many transitions.
alphabet_len: usize, /// The equivalence classes for this NFA. All transitions, dense and /// sparse, are defined on equivalence classes and not on the 256 distinct /// byte values.
byte_classes: ByteClasses, /// The length of the shortest pattern in this automaton.
min_pattern_len: usize, /// The length of the longest pattern in this automaton.
max_pattern_len: usize, /// The information required to deduce which states are "special" in this /// NFA.
special: Special,
}
impl NFA { /// Create a new Aho-Corasick contiguous NFA using the default /// configuration. /// /// Use a [`Builder`] if you want to change the configuration. pubfn new<I, P>(patterns: I) -> Result<NFA, BuildError> where
I: IntoIterator<Item = P>,
P: AsRef<[u8]>,
{
NFA::builder().build(patterns)
}
/// A convenience method for returning a new Aho-Corasick contiguous NFA /// builder. /// /// This usually permits one to just import the `NFA` type. pubfn builder() -> Builder {
Builder::new()
}
}
impl NFA { /// A sentinel state ID indicating that a search should stop once it has /// entered this state. When a search stops, it returns a match if one /// has been found, otherwise no match. A contiguous NFA always has an /// actual dead state at this ID. const DEAD: StateID = StateID::new_unchecked(0); /// Another sentinel state ID indicating that a search should move through /// current state's failure transition. /// /// Note that unlike DEAD, this does not actually point to a valid state /// in a contiguous NFA. (noncontiguous::NFA::FAIL does point to a valid /// state.) Instead, this points to the position that is guaranteed to /// never be a valid state ID (by making sure it points to a place in the /// middle of the encoding of the DEAD state). Since we never need to /// actually look at the FAIL state itself, this works out. /// /// By why do it this way? So that FAIL is a constant. I don't have any /// concrete evidence that this materially helps matters, but it's easy to /// do. The alternative would be making the FAIL ID point to the second /// state, which could be made a constant but is a little trickier to do. /// The easiest path is to just make the FAIL state a runtime value, but /// since comparisons with FAIL occur in perf critical parts of the search, /// we want it to be as tight as possible and not waste any registers. /// /// Very hand wavy... But the code complexity that results from this is /// very mild. const FAIL: StateID = StateID::new_unchecked(1);
}
// SAFETY: 'start_state' always returns a valid state ID, 'next_state' always // returns a valid state ID given a valid state ID. We otherwise claim that // all other methods are correct as well. unsafeimpl Automaton for NFA { #[inline(always)] fn start_state(&self, anchored: Anchored) -> Result<StateID, MatchError> { match anchored {
Anchored::No => Ok(self.special.start_unanchored_id),
Anchored::Yes => Ok(self.special.start_anchored_id),
}
}
#[inline(always)] fn next_state(
&self,
anchored: Anchored, mut sid: StateID,
byte: u8,
) -> StateID { let repr = &self.repr; let class = self.byte_classes.get(byte); let u32tosid = StateID::from_u32_unchecked; loop { let o = sid.as_usize(); let kind = repr[o] & 0xFF; // I tried to encapsulate the "next transition" logic into its own // function, but it seemed to always result in sub-optimal codegen // that led to real and significant slowdowns. So we just inline // the logic here. // // I've also tried a lot of different ways to speed up this // routine, and most of them have failed. if kind == State::KIND_DENSE { let next = u32tosid(repr[o + 2 + usize::from(class)]); if next != NFA::FAIL { return next;
}
} elseif kind == State::KIND_ONE { if class == repr[o].low_u16().high_u8() { return u32tosid(repr[o + 2]);
}
} else { // NOTE: I tried a SWAR technique in the loop below, but found // it slower. See the 'swar' test in the tests for this module. let trans_len = kind.as_usize(); let classes_len = u32_len(trans_len); let trans_offset = o + 2 + classes_len; for (i, &chunk) in
repr[o + 2..][..classes_len].iter().enumerate()
{ let classes = chunk.to_ne_bytes(); if classes[0] == class { return u32tosid(repr[trans_offset + i * 4]);
} if classes[1] == class { return u32tosid(repr[trans_offset + i * 4 + 1]);
} if classes[2] == class { return u32tosid(repr[trans_offset + i * 4 + 2]);
} if classes[3] == class { return u32tosid(repr[trans_offset + i * 4 + 3]);
}
}
} // For an anchored search, we never follow failure transitions // because failure transitions lead us down a path to matching // a *proper* suffix of the path we were on. Thus, it can only // produce matches that appear after the beginning of the search. if anchored.is_anchored() { return NFA::DEAD;
}
sid = u32tosid(repr[o + 1]);
}
}
writeln!(f, "contiguous::NFA(")?; letmut sid = NFA::DEAD; // always the first state and always present loop { let raw = &self.repr[sid.as_usize()..]; if raw.is_empty() { break;
} let is_match = self.is_match(sid); let state = State::read(self.alphabet_len, is_match, raw);
fmt_state_indicator(f, self, sid)?;
write!(
f, "{:06}({:06}): ",
sid.as_usize(),
state.fail.as_usize()
)?;
state.fmt(f)?;
write!(f, "\n")?; ifself.is_match(sid) {
write!(f, " matches: ")?; for i in0..state.match_len { let pid = State::match_pattern(self.alphabet_len, raw, i); if i > 0 {
write!(f, ", ")?;
}
write!(f, "{}", pid.as_usize())?;
}
write!(f, "\n")?;
} // The FAIL state doesn't actually have space for a state allocated // for it, so we have to treat it as a special case. write below // the DEAD state. if sid == NFA::DEAD {
writeln!(f, "F {:06}:", NFA::FAIL.as_usize())?;
} let len = State::len(self.alphabet_len, is_match, raw);
sid = StateID::new(sid.as_usize().checked_add(len).unwrap())
.unwrap();
}
writeln!(f, "match kind: {:?}", self.match_kind)?;
writeln!(f, "prefilter: {:?}", self.prefilter.is_some())?;
writeln!(f, "state length: {:?}", self.state_len)?;
writeln!(f, "pattern length: {:?}", self.patterns_len())?;
writeln!(f, "shortest pattern length: {:?}", self.min_pattern_len)?;
writeln!(f, "longest pattern length: {:?}", self.max_pattern_len)?;
writeln!(f, "alphabet length: {:?}", self.alphabet_len)?;
writeln!(f, "byte classes: {:?}", self.byte_classes)?;
writeln!(f, "memory usage: {:?}", self.memory_usage())?;
writeln!(f, ")")?;
Ok(())
}
}
/// The "in memory" representation a single dense or sparse state. /// /// A `State`'s in memory representation is not ever actually materialized /// during a search with a contiguous NFA. Doing so would be too slow. (Indeed, /// the only time a `State` is actually constructed is in `Debug` impls.) /// Instead, a `State` exposes a number of static methods for reading certain /// things from the raw binary encoding of the state. #[derive(Clone)] struct State<'a> { /// The state to transition to when 'class_to_next' yields a transition /// to the FAIL state.
fail: StateID, /// The number of pattern IDs in this state. For a non-match state, this is /// always zero. Otherwise it is always bigger than zero.
match_len: usize, /// The sparse or dense representation of the transitions for this state.
trans: StateTrans<'a>,
}
/// The underlying representation of sparse or dense transitions for a state. /// /// Note that like `State`, we don't typically construct values of this type /// during a search since we don't always need all values and thus would /// represent a lot of wasteful work. #[derive(Clone)] enum StateTrans<'a> { /// A sparse representation of transitions for a state, where only non-FAIL /// transitions are explicitly represented.
Sparse {
classes: &'a [u32], /// The transitions for this state, where each transition is packed /// into a u32. The low 8 bits correspond to the byte class for the /// transition, and the high 24 bits correspond to the next state ID. /// /// This packing is why the max state ID allowed for a contiguous /// NFA is 2^24-1.
nexts: &'a [u32],
}, /// A "one transition" state that is never a match state. /// /// These are by far the most common state, so we use a specialized and /// very compact representation for them.
One { /// The element of this NFA's alphabet that this transition is /// defined for.
class: u8, /// The state this should transition to if the current symbol is /// equal to 'class'.
next: u32,
}, /// A dense representation of transitions for a state, where all /// transitions are explicitly represented, including transitions to the /// FAIL state.
Dense { /// A dense set of transitions to other states. The transitions may /// point to a FAIL state, in which case, the search should try the /// same transition lookup at 'fail'. /// /// Note that this is indexed by byte equivalence classes and not /// byte values. That means 'class_to_next[byte]' is wrong and /// 'class_to_next[classes.get(byte)]' is correct. The number of /// transitions is always equivalent to 'classes.alphabet_len()'.
class_to_next: &'a [u32],
},
}
impl<'a> State<'a> { /// The offset of where the "kind" of a state is stored. If it isn't one /// of the sentinel values below, then it's a sparse state and the kind /// corresponds to the number of transitions in the state. const KIND: usize = 0;
/// A sentinel value indicating that the state uses a dense representation. const KIND_DENSE: u32 = 0xFF; /// A sentinel value indicating that the state uses a special "one /// transition" encoding. In practice, non-match states with one transition /// make up the overwhelming majority of all states in any given /// Aho-Corasick automaton, so we can specialize them using a very compact /// representation. const KIND_ONE: u32 = 0xFE;
/// The maximum number of transitions to encode as a sparse state. Usually /// states with a lot of transitions are either very rare, or occur near /// the start state. In the latter case, they are probably dense already /// anyway. In the former case, making them dense is fine because they're /// rare. /// /// This needs to be small enough to permit each of the sentinel values for /// 'KIND' above. Namely, a sparse state embeds the number of transitions /// into the 'KIND'. Basically, "sparse" is a state kind too, but it's the /// "else" branch. /// /// N.B. There isn't anything particularly magical about 127 here. I /// just picked it because I figured any sparse state with this many /// transitions is going to be exceptionally rare, and if it did have this /// many transitions, then it would be quite slow to do a linear scan on /// the transitions during a search anyway. const MAX_SPARSE_TRANSITIONS: usize = 127;
/// Remap state IDs in-place. /// /// `state` should be the the raw binary encoding of a state. (The start /// of the slice must correspond to the start of the state, but the slice /// may extend past the end of the encoding of the state.) fn remap(
alphabet_len: usize,
old_to_new: &[StateID],
state: &mut [u32],
) -> Result<(), BuildError> { let kind = State::kind(state); if kind == State::KIND_DENSE {
state[1] = old_to_new[state[1].as_usize()].as_u32(); for next in state[2..][..alphabet_len].iter_mut() {
*next = old_to_new[next.as_usize()].as_u32();
}
} elseif kind == State::KIND_ONE {
state[1] = old_to_new[state[1].as_usize()].as_u32();
state[2] = old_to_new[state[2].as_usize()].as_u32();
} else { let trans_len = State::sparse_trans_len(state); let classes_len = u32_len(trans_len);
state[1] = old_to_new[state[1].as_usize()].as_u32(); for next in state[2 + classes_len..][..trans_len].iter_mut() {
*next = old_to_new[next.as_usize()].as_u32();
}
}
Ok(())
}
/// Returns the length, in number of u32s, of this state. /// /// This is useful for reading states consecutively, e.g., in the Debug /// impl without needing to store a separate map from state index to state /// identifier. /// /// `state` should be the the raw binary encoding of a state. (The start /// of the slice must correspond to the start of the state, but the slice /// may extend past the end of the encoding of the state.) fn len(alphabet_len: usize, is_match: bool, state: &[u32]) -> usize { let kind_len = 1; let fail_len = 1; let kind = State::kind(state); let (classes_len, trans_len) = if kind == State::KIND_DENSE {
(0, alphabet_len)
} elseif kind == State::KIND_ONE {
(0, 1)
} else { let trans_len = State::sparse_trans_len(state); let classes_len = u32_len(trans_len);
(classes_len, trans_len)
}; let match_len = if !is_match { 0
} elseif State::match_len(alphabet_len, state) == 1 { // This is a special case because when there is one pattern ID for // a match state, it is represented by a single u32 with its high // bit set (which is impossible for a valid pattern ID). 1
} else { // We add 1 to include the u32 that indicates the number of // pattern IDs that follow. 1 + State::match_len(alphabet_len, state)
};
kind_len + fail_len + classes_len + trans_len + match_len
}
/// Returns the kind of this state. /// /// This only includes the low byte. #[inline(always)] fn kind(state: &[u32]) -> u32 {
state[State::KIND] & 0xFF
}
/// Get the number of sparse transitions in this state. This can never /// be more than State::MAX_SPARSE_TRANSITIONS, as all states with more /// transitions are encoded as dense states. /// /// `state` should be the the raw binary encoding of a sparse state. (The /// start of the slice must correspond to the start of the state, but the /// slice may extend past the end of the encoding of the state.) If this /// isn't a sparse state, then the return value is unspecified. /// /// Do note that this is only legal to call on a sparse state. So for /// example, "one transition" state is not a sparse state, so it would not /// be legal to call this method on such a state. #[inline(always)] fn sparse_trans_len(state: &[u32]) -> usize {
(state[State::KIND] & 0xFF).as_usize()
}
/// Returns the total number of matching pattern IDs in this state. Calling /// this on a state that isn't a match results in unspecified behavior. /// Thus, the returned number is never 0 for all correct calls. /// /// `state` should be the the raw binary encoding of a state. (The start /// of the slice must correspond to the start of the state, but the slice /// may extend past the end of the encoding of the state.) #[inline(always)] fn match_len(alphabet_len: usize, state: &[u32]) -> usize { // We don't need to handle KIND_ONE here because it can never be a // match state. let packed = if State::kind(state) == State::KIND_DENSE { let start = 2 + alphabet_len;
state[start].as_usize()
} else { let trans_len = State::sparse_trans_len(state); let classes_len = u32_len(trans_len); let start = 2 + classes_len + trans_len;
state[start].as_usize()
}; if packed & (1 << 31) == 0 {
packed
} else { 1
}
}
/// Returns the pattern ID corresponding to the given index for the state /// given. The `index` provided must be less than the number of pattern IDs /// in this state. /// /// `state` should be the the raw binary encoding of a state. (The start of /// the slice must correspond to the start of the state, but the slice may /// extend past the end of the encoding of the state.) /// /// If the given state is not a match state or if the index is out of /// bounds, then this has unspecified behavior. #[inline(always)] fn match_pattern(
alphabet_len: usize,
state: &[u32],
index: usize,
) -> PatternID { // We don't need to handle KIND_ONE here because it can never be a // match state. let start = if State::kind(state) == State::KIND_DENSE { 2 + alphabet_len
} else { let trans_len = State::sparse_trans_len(state); let classes_len = u32_len(trans_len); 2 + classes_len + trans_len
}; let packed = state[start]; let pid = if packed & (1 << 31) == 0 {
state[start + 1 + index]
} else {
assert_eq!(0, index);
packed & !(1 << 31)
};
PatternID::from_u32_unchecked(pid)
}
/// Read a state's binary encoding to its in-memory representation. /// /// `alphabet_len` should be the total number of transitions defined for /// dense states. /// /// `is_match` should be true if this state is a match state and false /// otherwise. /// /// `state` should be the the raw binary encoding of a state. (The start /// of the slice must correspond to the start of the state, but the slice /// may extend past the end of the encoding of the state.) fn read(
alphabet_len: usize,
is_match: bool,
state: &'a [u32],
) -> State<'a> { let kind = State::kind(state); let match_len = if !is_match { 0 } else { State::match_len(alphabet_len, state) }; let (trans, fail) = if kind == State::KIND_DENSE { let fail = StateID::from_u32_unchecked(state[1]); let class_to_next = &state[2..][..alphabet_len];
(StateTrans::Dense { class_to_next }, fail)
} elseif kind == State::KIND_ONE { let fail = StateID::from_u32_unchecked(state[1]); let class = state[State::KIND].low_u16().high_u8(); let next = state[2];
(StateTrans::One { class, next }, fail)
} else { let fail = StateID::from_u32_unchecked(state[1]); let trans_len = State::sparse_trans_len(state); let classes_len = u32_len(trans_len); let classes = &state[2..][..classes_len]; let nexts = &state[2 + classes_len..][..trans_len];
(StateTrans::Sparse { classes, nexts }, fail)
};
State { fail, match_len, trans }
}
/// Encode the "old" state from a noncontiguous NFA to its binary /// representation to the given `dst` slice. `classes` should be the byte /// classes computed for the noncontiguous NFA that the given state came /// from. /// /// This returns an error if `dst` became so big that `StateID`s can no /// longer be created for new states. Otherwise, it returns the state ID of /// the new state created. /// /// When `force_dense` is true, then the encoded state will always use a /// dense format. Otherwise, the choice between dense and sparse will be /// automatically chosen based on the old state. fn write(
nnfa: &noncontiguous::NFA,
oldsid: StateID,
old: &noncontiguous::State,
classes: &ByteClasses,
dst: &mut Vec<u32>,
force_dense: bool,
) -> Result<StateID, BuildError> { let sid = StateID::new(dst.len()).map_err(|e| {
BuildError::state_id_overflow(StateID::MAX.as_u64(), e.attempted())
})?; let old_len = nnfa.iter_trans(oldsid).count(); // For states with a lot of transitions, we might as well just make // them dense. These kinds of hot states tend to be very rare, so we're // okay with it. This also gives us more sentinels in the state's // 'kind', which lets us create different state kinds to save on // space. let kind = if force_dense || old_len > State::MAX_SPARSE_TRANSITIONS {
State::KIND_DENSE
} elseif old_len == 1 && !old.is_match() {
State::KIND_ONE
} else { // For a sparse state, the kind is just the number of transitions.
u32::try_from(old_len).unwrap()
}; if kind == State::KIND_DENSE {
dst.push(kind);
dst.push(old.fail().as_u32());
State::write_dense_trans(nnfa, oldsid, classes, dst)?;
} elseif kind == State::KIND_ONE { let t = nnfa.iter_trans(oldsid).next().unwrap(); let class = u32::from(classes.get(t.byte()));
dst.push(kind | (class << 8));
dst.push(old.fail().as_u32());
dst.push(t.next().as_u32());
} else {
dst.push(kind);
dst.push(old.fail().as_u32());
State::write_sparse_trans(nnfa, oldsid, classes, dst)?;
} // Now finally write the number of matches and the matches themselves. if old.is_match() { let matches_len = nnfa.iter_matches(oldsid).count(); if matches_len == 1 { let pid = nnfa.iter_matches(oldsid).next().unwrap().as_u32();
assert_eq!(0, pid & (1 << 31));
dst.push((1 << 31) | pid);
} else {
assert_eq!(0, matches_len & (1 << 31));
dst.push(matches_len.as_u32());
dst.extend(nnfa.iter_matches(oldsid).map(|pid| pid.as_u32()));
}
}
Ok(sid)
}
/// Encode the "old" state transitions from a noncontiguous NFA to its /// binary sparse representation to the given `dst` slice. `classes` should /// be the byte classes computed for the noncontiguous NFA that the given /// state came from. /// /// This returns an error if `dst` became so big that `StateID`s can no /// longer be created for new states. fn write_sparse_trans(
nnfa: &noncontiguous::NFA,
oldsid: StateID,
classes: &ByteClasses,
dst: &mut Vec<u32>,
) -> Result<(), BuildError> { let (mut chunk, mut len) = ([0; 4], 0); for t in nnfa.iter_trans(oldsid) {
chunk[len] = classes.get(t.byte());
len += 1; if len == 4 {
dst.push(u32::from_ne_bytes(chunk));
chunk = [0; 4];
len = 0;
}
} if len > 0 { // In the case where the number of transitions isn't divisible // by 4, the last u32 chunk will have some left over room. In // this case, we "just" repeat the last equivalence class. By // doing this, we know the leftover faux transitions will never // be followed because if they were, it would have been followed // prior to it in the last equivalence class. This saves us some // branching in the search time state transition code. let repeat = chunk[len - 1]; while len < 4 {
chunk[len] = repeat;
len += 1;
}
dst.push(u32::from_ne_bytes(chunk));
} for t in nnfa.iter_trans(oldsid) {
dst.push(t.next().as_u32());
}
Ok(())
}
/// Encode the "old" state transitions from a noncontiguous NFA to its /// binary dense representation to the given `dst` slice. `classes` should /// be the byte classes computed for the noncontiguous NFA that the given /// state came from. /// /// This returns an error if `dst` became so big that `StateID`s can no /// longer be created for new states. fn write_dense_trans(
nnfa: &noncontiguous::NFA,
oldsid: StateID,
classes: &ByteClasses,
dst: &mut Vec<u32>,
) -> Result<(), BuildError> { // Our byte classes let us shrink the size of our dense states to the // number of equivalence classes instead of just fixing it to 256. // Any non-explicitly defined transition is just a transition to the // FAIL state, so we fill that in first and then overwrite them with // explicitly defined transitions. (Most states probably only have one // or two explicitly defined transitions.) // // N.B. Remember that while building the contiguous NFA, we use state // IDs from the noncontiguous NFA. It isn't until we've added all // states that we go back and map noncontiguous IDs to contiguous IDs. let start = dst.len();
dst.extend(
core::iter::repeat(noncontiguous::NFA::FAIL.as_u32())
.take(classes.alphabet_len()),
);
assert!(start < dst.len(), "equivalence classes are never empty"); for t in nnfa.iter_trans(oldsid) {
dst[start + usize::from(classes.get(t.byte()))] =
t.next().as_u32();
}
Ok(())
}
/// Return an iterator over every explicitly defined transition in this /// state. fn transitions<'b>(&'b self) -> impl Iterator<Item = (u8, StateID)> + 'b { letmut i = 0;
core::iter::from_fn(move || matchself.trans {
StateTrans::Sparse { classes, nexts } => { if i >= nexts.len() { return None;
} let chunk = classes[i / 4]; let class = chunk.to_ne_bytes()[i % 4]; let next = StateID::from_u32_unchecked(nexts[i]);
i += 1;
Some((class, next))
}
StateTrans::One { class, next } => { if i == 0 {
i += 1;
Some((class, StateID::from_u32_unchecked(next)))
} else {
None
}
}
StateTrans::Dense { class_to_next } => { if i >= class_to_next.len() { return None;
} let class = i.as_u8(); let next = StateID::from_u32_unchecked(class_to_next[i]);
i += 1;
Some((class, next))
}
})
}
}
let it = sparse_transitions(self.transitions()) // Writing out all FAIL transitions is quite noisy. Instead, we // just require readers of the output to assume anything absent // maps to the FAIL transition.
.filter(|&(_, _, sid)| sid != NFA::FAIL)
.enumerate(); for (i, (start, end, sid)) in it { if i > 0 {
write!(f, ", ")?;
} if start == end {
write!(f, "{:?} => {:?}", DebugByte(start), sid.as_usize())?;
} else {
write!(
f, "{:?}-{:?} => {:?}",
DebugByte(start),
DebugByte(end),
sid.as_usize()
)?;
}
}
Ok(())
}
}
/// A builder for configuring an Aho-Corasick contiguous NFA. /// /// This builder has a subset of the options available to a /// [`AhoCorasickBuilder`](crate::AhoCorasickBuilder). Of the shared options, /// their behavior is identical. #[derive(Clone, Debug)] pubstruct Builder {
noncontiguous: noncontiguous::Builder,
dense_depth: usize,
byte_classes: bool,
}
impl Builder { /// Create a new builder for configuring an Aho-Corasick contiguous NFA. pubfn new() -> Builder {
Builder::default()
}
/// Build an Aho-Corasick contiguous NFA from the given iterator of /// patterns. /// /// A builder may be reused to create more NFAs. pubfn build<I, P>(&self, patterns: I) -> Result<NFA, BuildError> where
I: IntoIterator<Item = P>,
P: AsRef<[u8]>,
{ let nnfa = self.noncontiguous.build(patterns)?; self.build_from_noncontiguous(&nnfa)
}
/// Build an Aho-Corasick contiguous NFA from the given noncontiguous NFA. /// /// Note that when this method is used, only the `dense_depth` and /// `byte_classes` settings on this builder are respected. The other /// settings only apply to the initial construction of the Aho-Corasick /// automaton. Since using this method requires that initial construction /// has already completed, all settings impacting only initial construction /// are no longer relevant. pubfn build_from_noncontiguous(
&self,
nnfa: &noncontiguous::NFA,
) -> Result<NFA, BuildError> {
debug!("building contiguous NFA"); let byte_classes = ifself.byte_classes {
nnfa.byte_classes().clone()
} else {
ByteClasses::singletons()
}; letmut index_to_state_id = vec![NFA::DEAD; nnfa.states().len()]; letmut nfa = NFA {
repr: vec![],
pattern_lens: nnfa.pattern_lens_raw().to_vec(),
state_len: nnfa.states().len(),
prefilter: nnfa.prefilter().map(|p| p.clone()),
match_kind: nnfa.match_kind(),
alphabet_len: byte_classes.alphabet_len(),
byte_classes,
min_pattern_len: nnfa.min_pattern_len(),
max_pattern_len: nnfa.max_pattern_len(), // The special state IDs are set later.
special: Special::zero(),
}; for (oldsid, state) in nnfa.states().iter().with_state_ids() { // We don't actually encode a fail state since it isn't necessary. // But we still want to make sure any FAIL ids are mapped // correctly. if oldsid == noncontiguous::NFA::FAIL {
index_to_state_id[oldsid] = NFA::FAIL; continue;
} let force_dense = state.depth().as_usize() < self.dense_depth; let newsid = State::write(
nnfa,
oldsid,
state,
&nfa.byte_classes,
&mut nfa.repr,
force_dense,
)?;
index_to_state_id[oldsid] = newsid;
} for &newsid in index_to_state_id.iter() { if newsid == NFA::FAIL { continue;
} let state = &mut nfa.repr[newsid.as_usize()..];
State::remap(nfa.alphabet_len, &index_to_state_id, state)?;
} // Now that we've remapped all the IDs in our states, all that's left // is remapping the special state IDs. let remap = &index_to_state_id; let old = nnfa.special(); let new = &mut nfa.special;
new.max_special_id = remap[old.max_special_id];
new.max_match_id = remap[old.max_match_id];
new.start_unanchored_id = remap[old.start_unanchored_id];
new.start_anchored_id = remap[old.start_anchored_id];
debug!( "contiguous NFA built, <states: {:?}, size: {:?}, \
alphabet len: {:?}>",
nfa.state_len,
nfa.memory_usage(),
nfa.byte_classes.alphabet_len(),
); // The vectors can grow ~twice as big during construction because a // Vec amortizes growth. But here, let's shrink things back down to // what we actually need since we're never going to add more to it.
nfa.repr.shrink_to_fit();
nfa.pattern_lens.shrink_to_fit();
Ok(nfa)
}
/// Set the desired match semantics. /// /// This only applies when using [`Builder::build`] and not /// [`Builder::build_from_noncontiguous`]. /// /// See /// [`AhoCorasickBuilder::match_kind`](crate::AhoCorasickBuilder::match_kind) /// for more documentation and examples. pubfn match_kind(&mutself, kind: MatchKind) -> &mut Builder { self.noncontiguous.match_kind(kind); self
}
/// Enable ASCII-aware case insensitive matching. /// /// This only applies when using [`Builder::build`] and not /// [`Builder::build_from_noncontiguous`]. /// /// See /// [`AhoCorasickBuilder::ascii_case_insensitive`](crate::AhoCorasickBuilder::ascii_case_insensitive) /// for more documentation and examples. pubfn ascii_case_insensitive(&mutself, yes: bool) -> &'color:red'>mut Builder { self.noncontiguous.ascii_case_insensitive(yes); self
}
/// Enable heuristic prefilter optimizations. /// /// This only applies when using [`Builder::build`] and not /// [`Builder::build_from_noncontiguous`]. /// /// See /// [`AhoCorasickBuilder::prefilter`](crate::AhoCorasickBuilder::prefilter) /// for more documentation and examples. pubfn prefilter(&mutself, yes: bool) -> &mut Builder { self.noncontiguous.prefilter(yes); self
}
/// Set the limit on how many states use a dense representation for their /// transitions. Other states will generally use a sparse representation. /// /// See /// [`AhoCorasickBuilder::dense_depth`](crate::AhoCorasickBuilder::dense_depth) /// for more documentation and examples. pubfn dense_depth(&mutself, depth: usize) -> &mut Builder { self.dense_depth = depth; self
}
/// A debug setting for whether to attempt to shrink the size of the /// automaton's alphabet or not. /// /// This should never be enabled unless you're debugging an automaton. /// Namely, disabling byte classes makes transitions easier to reason /// about, since they use the actual bytes instead of equivalence classes. /// Disabling this confers no performance benefit at search time. /// /// See /// [`AhoCorasickBuilder::byte_classes`](crate::AhoCorasickBuilder::byte_classes) /// for more documentation and examples. pubfn byte_classes(&mutself, yes: bool) -> &mut Builder { self.byte_classes = yes; self
}
}
/// Computes the number of u32 values needed to represent one byte per the /// number of transitions given. fn u32_len(ntrans: usize) -> usize { if ntrans % 4 == 0 {
ntrans >> 2
} else {
(ntrans >> 2) + 1
}
}
#[cfg(test)] mod tests { // This test demonstrates a SWAR technique I tried in the sparse transition // code inside of 'next_state'. Namely, sparse transitions work by // iterating over u32 chunks, with each chunk containing up to 4 classes // corresponding to 4 transitions. This SWAR technique lets us find a // matching transition without converting the u32 to a [u8; 4]. // // It turned out to be a little slower unfortunately, which isn't too // surprising, since this is likely a throughput oriented optimization. // Loop unrolling doesn't really help us because the vast majority of // states have very few transitions. // // Anyway, this code was a little tricky to write, so I converted it to a // test in case someone figures out how to use it more effectively than // I could. // // (This also only works on little endian. So big endian would need to be // accounted for if we ever decided to use this I think.) #[cfg(target_endian = "little")] #[test] fn swar() { usesuper::*;
Die Informationen auf dieser Webseite wurden
nach bestem Wissen sorgfältig zusammengestellt. Es wird jedoch weder Vollständigkeit, noch Richtigkeit,
noch Qualität der bereit gestellten Informationen zugesichert.
Bemerkung:
Die farbliche Syntaxdarstellung und die Messung sind noch experimentell.