// Setup our haystack and initial start state. letinput=Input::new("Samwise"); letmutstate=OverlappingState::start();
// First, 'Sam' will match. sparse_re.try_search_overlapping_fwd(&input,&mutstate)?; assert_eq!(Some(HalfMatch::must(0,3)),state.get_match());
// And now 'Samwise' will match. sparse_re.try_search_overlapping_fwd(&input,&mutstate)?; assert_eq!(Some(HalfMatch::must(0,7)),state.get_match()); #Ok::<(),Box<dynstd::error::Error>>(()) ```
*/
#[cfg(feature = "dfa-build")] use core::iter; use core::{
convert::{TryFrom, TryInto},
fmt,
mem::size_of,
};
#[cfg(feature = "dfa-build")] use alloc::{vec, vec::Vec};
/// A sparse deterministic finite automaton (DFA) with variable sized states. /// /// In contrast to a [dense::DFA](crate::dfa::dense::DFA), a sparse DFA uses /// a more space efficient representation for its transitions. Consequently, /// sparse DFAs may use much less memory than dense DFAs, but this comes at a /// price. In particular, reading the more space efficient transitions takes /// more work, and consequently, searching using a sparse DFA is typically /// slower than a dense DFA. /// /// A sparse DFA can be built using the default configuration via the /// [`DFA::new`] constructor. Otherwise, one can configure various aspects /// of a dense DFA via [`dense::Builder`](crate::dfa::dense::Builder), /// and then convert a dense DFA to a sparse DFA using /// [`dense::DFA::to_sparse`](crate::dfa::dense::DFA::to_sparse). /// /// In general, a sparse DFA supports all the same search operations as a dense /// DFA. /// /// Making the choice between a dense and sparse DFA depends on your specific /// work load. If you can sacrifice a bit of search time performance, then a /// sparse DFA might be the best choice. In particular, while sparse DFAs are /// probably always slower than dense DFAs, you may find that they are easily /// fast enough for your purposes! /// /// # Type parameters /// /// A `DFA` has one type parameter, `T`, which is used to represent the parts /// of a sparse DFA. `T` is typically a `Vec<u8>` or a `&[u8]`. /// /// # The `Automaton` trait /// /// This type implements the [`Automaton`] trait, which means it can be used /// for searching. For example: /// /// ``` /// use regex_automata::{dfa::{Automaton, sparse::DFA}, HalfMatch, Input}; /// /// let dfa = DFA::new("foo[0-9]+")?; /// let expected = Some(HalfMatch::must(0, 8)); /// assert_eq!(expected, dfa.try_search_fwd(&Input::new("foo12345"))?); /// # Ok::<(), Box<dyn std::error::Error>>(()) /// ``` #[derive(Clone)] pubstruct DFA<T> { // When compared to a dense DFA, a sparse DFA *looks* a lot simpler // representation-wise. In reality, it is perhaps more complicated. Namely, // in a dense DFA, all information needs to be very cheaply accessible // using only state IDs. In a sparse DFA however, each state uses a // variable amount of space because each state encodes more information // than just its transitions. Each state also includes an accelerator if // one exists, along with the matching pattern IDs if the state is a match // state. // // That is, a lot of the complexity is pushed down into how each state // itself is represented.
tt: Transitions<T>,
st: StartTable<T>,
special: Special,
pre: Option<Prefilter>,
quitset: ByteSet,
flags: Flags,
}
#[cfg(feature = "dfa-build")] impl DFA<Vec<u8>> { /// Parse the given regular expression using a default configuration and /// return the corresponding sparse DFA. /// /// If you want a non-default configuration, then use /// the [`dense::Builder`](crate::dfa::dense::Builder) /// to set your own configuration, and then call /// [`dense::DFA::to_sparse`](crate::dfa::dense::DFA::to_sparse) to create /// a sparse DFA. /// /// # Example /// /// ``` /// use regex_automata::{dfa::{Automaton, sparse}, HalfMatch, Input}; /// /// let dfa = sparse::DFA::new("foo[0-9]+bar")?; /// /// let expected = Some(HalfMatch::must(0, 11)); /// assert_eq!(expected, dfa.try_search_fwd(&Input::new("foo12345bar"))?); /// # Ok::<(), Box<dyn std::error::Error>>(()) /// ``` #[cfg(feature = "syntax")] pubfn new(pattern: &str) -> Result<DFA<Vec<u8>>, BuildError> {
dense::Builder::new()
.build(pattern)
.and_then(|dense| dense.to_sparse())
}
/// Parse the given regular expressions using a default configuration and /// return the corresponding multi-DFA. /// /// If you want a non-default configuration, then use /// the [`dense::Builder`](crate::dfa::dense::Builder) /// to set your own configuration, and then call /// [`dense::DFA::to_sparse`](crate::dfa::dense::DFA::to_sparse) to create /// a sparse DFA. /// /// # Example /// /// ``` /// use regex_automata::{dfa::{Automaton, sparse}, HalfMatch, Input}; /// /// let dfa = sparse::DFA::new_many(&["[0-9]+", "[a-z]+"])?; /// let expected = Some(HalfMatch::must(1, 3)); /// assert_eq!(expected, dfa.try_search_fwd(&Input::new("foo12345bar"))?); /// # Ok::<(), Box<dyn std::error::Error>>(()) /// ``` #[cfg(feature = "syntax")] pubfn new_many<P: AsRef<str>>(
patterns: &[P],
) -> Result<DFA<Vec<u8>>, BuildError> {
dense::Builder::new()
.build_many(patterns)
.and_then(|dense| dense.to_sparse())
}
}
#[cfg(feature = "dfa-build")] impl DFA<Vec<u8>> { /// Create a new DFA that matches every input. /// /// # Example /// /// ``` /// use regex_automata::{ /// dfa::{Automaton, sparse}, /// HalfMatch, Input, /// }; /// /// let dfa = sparse::DFA::always_match()?; /// /// let expected = Some(HalfMatch::must(0, 0)); /// assert_eq!(expected, dfa.try_search_fwd(&Input::new(""))?); /// assert_eq!(expected, dfa.try_search_fwd(&Input::new("foo"))?); /// # Ok::<(), Box<dyn std::error::Error>>(()) /// ``` pubfn always_match() -> Result<DFA<Vec<u8>>, BuildError> {
dense::DFA::always_match()?.to_sparse()
}
/// Create a new sparse DFA that never matches any input. /// /// # Example /// /// ``` /// use regex_automata::{dfa::{Automaton, sparse}, Input}; /// /// let dfa = sparse::DFA::never_match()?; /// assert_eq!(None, dfa.try_search_fwd(&Input::new(""))?); /// assert_eq!(None, dfa.try_search_fwd(&Input::new("foo"))?); /// # Ok::<(), Box<dyn std::error::Error>>(()) /// ``` pubfn never_match() -> Result<DFA<Vec<u8>>, BuildError> {
dense::DFA::never_match()?.to_sparse()
}
/// The implementation for constructing a sparse DFA from a dense DFA. pub(crate) fn from_dense<T: AsRef<[u32]>>(
dfa: &dense::DFA<T>,
) -> Result<DFA<Vec<u8>>, BuildError> { // In order to build the transition table, we need to be able to write // state identifiers for each of the "next" transitions in each state. // Our state identifiers correspond to the byte offset in the // transition table at which the state is encoded. Therefore, we do not // actually know what the state identifiers are until we've allocated // exactly as much space as we need for each state. Thus, construction // of the transition table happens in two passes. // // In the first pass, we fill out the shell of each state, which // includes the transition length, the input byte ranges and // zero-filled space for the transitions and accelerators, if present. // In this first pass, we also build up a map from the state identifier // index of the dense DFA to the state identifier in this sparse DFA. // // In the second pass, we fill in the transitions based on the map // built in the first pass.
// The capacity given here reflects a minimum. (Well, the true minimum // is likely even bigger, but hopefully this saves a few reallocs.) letmut sparse = Vec::with_capacity(StateID::SIZE * dfa.state_len()); // This maps state indices from the dense DFA to StateIDs in the sparse // DFA. We build out this map on the first pass, and then use it in the // second pass to back-fill our transitions. letmut remap: Vec<StateID> = vec![DEAD; dfa.state_len()]; for state in dfa.states() { let pos = sparse.len();
remap[dfa.to_index(state.id())] = StateID::new(pos)
.map_err(|_| BuildError::too_many_states())?; // zero-filled space for the transition length
sparse.push(0);
sparse.push(0);
letmut transition_len = 0; for (unit1, unit2, _) in state.sparse_transitions() { match (unit1.as_u8(), unit2.as_u8()) {
(Some(b1), Some(b2)) => {
transition_len += 1;
sparse.push(b1);
sparse.push(b2);
}
(None, None) => {}
(Some(_), None) | (None, Some(_)) => { // can never occur because sparse_transitions never // groups EOI with any other transition.
unreachable!()
}
}
} // Add dummy EOI transition. This is never actually read while // searching, but having space equivalent to the total number // of transitions is convenient. Otherwise, we'd need to track // a different number of transitions for the byte ranges as for // the 'next' states. // // N.B. The loop above is not guaranteed to yield the EOI // transition, since it may point to a DEAD state. By putting // it here, we always write the EOI transition, and thus // guarantee that our transition length is >0. Why do we always // need the EOI transition? Because in order to implement // Automaton::next_eoi_state, this lets us just ask for the last // transition. There are probably other/better ways to do this.
transition_len += 1;
sparse.push(0);
sparse.push(0);
// Check some assumptions about transition length.
assert_ne!(
transition_len, 0, "transition length should be non-zero",
);
assert!(
transition_len <= 257, "expected transition length {} to be <= 257",
transition_len,
);
// Fill in the transition length. // Since transition length is always <= 257, we use the most // significant bit to indicate whether this is a match state or // not. let ntrans = if dfa.is_match_state(state.id()) {
transition_len | (1 << 15)
} else {
transition_len
};
wire::NE::write_u16(ntrans, &mut sparse[pos..]);
// zero-fill the actual transitions. // Unwraps are OK since transition_length <= 257 and our minimum // support usize size is 16-bits. let zeros = usize::try_from(transition_len)
.unwrap()
.checked_mul(StateID::SIZE)
.unwrap();
sparse.extend(iter::repeat(0).take(zeros));
// If this is a match state, write the pattern IDs matched by this // state. if dfa.is_match_state(state.id()) { let plen = dfa.match_pattern_len(state.id()); // Write the actual pattern IDs with a u32 length prefix. // First, zero-fill space. letmut pos = sparse.len(); // Unwraps are OK since it's guaranteed that plen <= // PatternID::LIMIT, which is in turn guaranteed to fit into a // u32. let zeros = size_of::<u32>()
.checked_mul(plen)
.unwrap()
.checked_add(size_of::<u32>())
.unwrap();
sparse.extend(iter::repeat(0).take(zeros));
// Now write the length prefix.
wire::NE::write_u32( // Will never fail since u32::MAX is invalid pattern ID. // Thus, the number of pattern IDs is representable by a // u32.
plen.try_into().expect("pattern ID length fits in u32"),
&mut sparse[pos..],
);
pos += size_of::<u32>();
// Now write the pattern IDs. for &pid in dfa.pattern_id_slice(state.id()) {
pos += wire::write_pattern_id::<wire::NE>(
pid,
&mut sparse[pos..],
);
}
}
// And now add the accelerator, if one exists. An accelerator is // at most 4 bytes and at least 1 byte. The first byte is the // length, N. N bytes follow the length. The set of bytes that // follow correspond (exhaustively) to the bytes that must be seen // to leave this state. let accel = dfa.accelerator(state.id());
sparse.push(accel.len().try_into().unwrap());
sparse.extend_from_slice(accel);
}
letmut new = DFA {
tt: Transitions {
sparse,
classes: dfa.byte_classes().clone(),
state_len: dfa.state_len(),
pattern_len: dfa.pattern_len(),
},
st: StartTable::from_dense_dfa(dfa, &remap)?,
special: dfa.special().remap(|id| remap[dfa.to_index(id)]),
pre: dfa.get_prefilter().map(|p| p.clone()),
quitset: dfa.quitset().clone(),
flags: dfa.flags().clone(),
}; // And here's our second pass. Iterate over all of the dense states // again, and update the transitions in each of the states in the // sparse DFA. for old_state in dfa.states() { let new_id = remap[dfa.to_index(old_state.id())]; letmut new_state = new.tt.state_mut(new_id); let sparse = old_state.sparse_transitions(); for (i, (_, _, next)) in sparse.enumerate() { let next = remap[dfa.to_index(next)];
new_state.set_next_at(i, next);
}
}
debug!( "created sparse DFA, memory usage: {} (dense memory usage: {})",
new.memory_usage(),
dfa.memory_usage(),
);
Ok(new)
}
}
impl<T: AsRef<[u8]>> DFA<T> { /// Cheaply return a borrowed version of this sparse DFA. Specifically, the /// DFA returned always uses `&[u8]` for its transitions. pubfn as_ref<'a>(&'a self) -> DFA<&'a [u8]> {
DFA {
tt: self.tt.as_ref(),
st: self.st.as_ref(),
special: self.special,
pre: self.pre.clone(),
quitset: self.quitset,
flags: self.flags,
}
}
/// Return an owned version of this sparse DFA. Specifically, the DFA /// returned always uses `Vec<u8>` for its transitions. /// /// Effectively, this returns a sparse DFA whose transitions live on the /// heap. #[cfg(feature = "alloc")] pubfn to_owned(&self) -> DFA<alloc::vec::Vec<u8>> {
DFA {
tt: self.tt.to_owned(),
st: self.st.to_owned(),
special: self.special,
pre: self.pre.clone(),
quitset: self.quitset,
flags: self.flags,
}
}
/// Returns the starting state configuration for this DFA. /// /// The default is [`StartKind::Both`], which means the DFA supports both /// unanchored and anchored searches. However, this can generally lead to /// bigger DFAs. Therefore, a DFA might be compiled with support for just /// unanchored or anchored searches. In that case, running a search with /// an unsupported configuration will panic. pubfn start_kind(&self) -> StartKind { self.st.kind
}
/// Returns true only if this DFA has starting states for each pattern. /// /// When a DFA has starting states for each pattern, then a search with the /// DFA can be configured to only look for anchored matches of a specific /// pattern. Specifically, APIs like [`Automaton::try_search_fwd`] can /// accept a [`Anchored::Pattern`] if and only if this method returns true. /// Otherwise, an error will be returned. /// /// Note that if the DFA is empty, this always returns false. pubfn starts_for_each_pattern(&self) -> bool { self.st.pattern_len.is_some()
}
/// Returns the equivalence classes that make up the alphabet for this DFA. /// /// Unless [`dense::Config::byte_classes`] was disabled, it is possible /// that multiple distinct bytes are grouped into the same equivalence /// class if it is impossible for them to discriminate between a match and /// a non-match. This has the effect of reducing the overall alphabet size /// and in turn potentially substantially reducing the size of the DFA's /// transition table. /// /// The downside of using equivalence classes like this is that every state /// transition will automatically use this map to convert an arbitrary /// byte to its corresponding equivalence class. In practice this has a /// negligible impact on performance. pubfn byte_classes(&self) -> &ByteClasses {
&self.tt.classes
}
/// Returns the memory usage, in bytes, of this DFA. /// /// The memory usage is computed based on the number of bytes used to /// represent this DFA. /// /// This does **not** include the stack size used up by this DFA. To /// compute that, use `std::mem::size_of::<sparse::DFA>()`. pubfn memory_usage(&self) -> usize { self.tt.memory_usage() + self.st.memory_usage()
}
}
/// Routines for converting a sparse DFA to other representations, such as raw /// bytes suitable for persistent storage. impl<T: AsRef<[u8]>> DFA<T> { /// Serialize this DFA as raw bytes to a `Vec<u8>` in little endian /// format. /// /// The written bytes are guaranteed to be deserialized correctly and /// without errors in a semver compatible release of this crate by a /// `DFA`'s deserialization APIs (assuming all other criteria for the /// deserialization APIs has been satisfied): /// /// * [`DFA::from_bytes`] /// * [`DFA::from_bytes_unchecked`] /// /// Note that unlike a [`dense::DFA`](crate::dfa::dense::DFA)'s /// serialization methods, this does not add any initial padding to the /// returned bytes. Padding isn't required for sparse DFAs since they have /// no alignment requirements. /// /// # Example /// /// This example shows how to serialize and deserialize a DFA: /// /// ``` /// use regex_automata::{dfa::{Automaton, sparse::DFA}, HalfMatch, Input}; /// /// // Compile our original DFA. /// let original_dfa = DFA::new("foo[0-9]+")?; /// /// // N.B. We use native endianness here to make the example work, but /// // using to_bytes_little_endian would work on a little endian target. /// let buf = original_dfa.to_bytes_native_endian(); /// // Even if buf has initial padding, DFA::from_bytes will automatically /// // ignore it. /// let dfa: DFA<&[u8]> = DFA::from_bytes(&buf)?.0; /// /// let expected = Some(HalfMatch::must(0, 8)); /// assert_eq!(expected, dfa.try_search_fwd(&Input::new("foo12345"))?); /// # Ok::<(), Box<dyn std::error::Error>>(()) /// ``` #[cfg(feature = "dfa-build")] pubfn to_bytes_little_endian(&self) -> Vec<u8> { self.to_bytes::<wire::LE>()
}
/// Serialize this DFA as raw bytes to a `Vec<u8>` in big endian /// format. /// /// The written bytes are guaranteed to be deserialized correctly and /// without errors in a semver compatible release of this crate by a /// `DFA`'s deserialization APIs (assuming all other criteria for the /// deserialization APIs has been satisfied): /// /// * [`DFA::from_bytes`] /// * [`DFA::from_bytes_unchecked`] /// /// Note that unlike a [`dense::DFA`](crate::dfa::dense::DFA)'s /// serialization methods, this does not add any initial padding to the /// returned bytes. Padding isn't required for sparse DFAs since they have /// no alignment requirements. /// /// # Example /// /// This example shows how to serialize and deserialize a DFA: /// /// ``` /// use regex_automata::{dfa::{Automaton, sparse::DFA}, HalfMatch, Input}; /// /// // Compile our original DFA. /// let original_dfa = DFA::new("foo[0-9]+")?; /// /// // N.B. We use native endianness here to make the example work, but /// // using to_bytes_big_endian would work on a big endian target. /// let buf = original_dfa.to_bytes_native_endian(); /// // Even if buf has initial padding, DFA::from_bytes will automatically /// // ignore it. /// let dfa: DFA<&[u8]> = DFA::from_bytes(&buf)?.0; /// /// let expected = Some(HalfMatch::must(0, 8)); /// assert_eq!(expected, dfa.try_search_fwd(&Input::new("foo12345"))?); /// # Ok::<(), Box<dyn std::error::Error>>(()) /// ``` #[cfg(feature = "dfa-build")] pubfn to_bytes_big_endian(&self) -> Vec<u8> { self.to_bytes::<wire::BE>()
}
/// Serialize this DFA as raw bytes to a `Vec<u8>` in native endian /// format. /// /// The written bytes are guaranteed to be deserialized correctly and /// without errors in a semver compatible release of this crate by a /// `DFA`'s deserialization APIs (assuming all other criteria for the /// deserialization APIs has been satisfied): /// /// * [`DFA::from_bytes`] /// * [`DFA::from_bytes_unchecked`] /// /// Note that unlike a [`dense::DFA`](crate::dfa::dense::DFA)'s /// serialization methods, this does not add any initial padding to the /// returned bytes. Padding isn't required for sparse DFAs since they have /// no alignment requirements. /// /// Generally speaking, native endian format should only be used when /// you know that the target you're compiling the DFA for matches the /// endianness of the target on which you're compiling DFA. For example, /// if serialization and deserialization happen in the same process or on /// the same machine. Otherwise, when serializing a DFA for use in a /// portable environment, you'll almost certainly want to serialize _both_ /// a little endian and a big endian version and then load the correct one /// based on the target's configuration. /// /// # Example /// /// This example shows how to serialize and deserialize a DFA: /// /// ``` /// use regex_automata::{dfa::{Automaton, sparse::DFA}, HalfMatch, Input}; /// /// // Compile our original DFA. /// let original_dfa = DFA::new("foo[0-9]+")?; /// /// let buf = original_dfa.to_bytes_native_endian(); /// // Even if buf has initial padding, DFA::from_bytes will automatically /// // ignore it. /// let dfa: DFA<&[u8]> = DFA::from_bytes(&buf)?.0; /// /// let expected = Some(HalfMatch::must(0, 8)); /// assert_eq!(expected, dfa.try_search_fwd(&Input::new("foo12345"))?); /// # Ok::<(), Box<dyn std::error::Error>>(()) /// ``` #[cfg(feature = "dfa-build")] pubfn to_bytes_native_endian(&self) -> Vec<u8> { self.to_bytes::<wire::NE>()
}
/// The implementation of the public `to_bytes` serialization methods, /// which is generic over endianness. #[cfg(feature = "dfa-build")] fn to_bytes<E: Endian>(&self) -> Vec<u8> { letmut buf = vec![0; self.write_to_len()]; // This should always succeed since the only possible serialization // error is providing a buffer that's too small, but we've ensured that // `buf` is big enough here. self.write_to::<E>(&mut buf).unwrap();
buf
}
/// Serialize this DFA as raw bytes to the given slice, in little endian /// format. Upon success, the total number of bytes written to `dst` is /// returned. /// /// The written bytes are guaranteed to be deserialized correctly and /// without errors in a semver compatible release of this crate by a /// `DFA`'s deserialization APIs (assuming all other criteria for the /// deserialization APIs has been satisfied): /// /// * [`DFA::from_bytes`] /// * [`DFA::from_bytes_unchecked`] /// /// # Errors /// /// This returns an error if the given destination slice is not big enough /// to contain the full serialized DFA. If an error occurs, then nothing /// is written to `dst`. /// /// # Example /// /// This example shows how to serialize and deserialize a DFA without /// dynamic memory allocation. /// /// ``` /// use regex_automata::{dfa::{Automaton, sparse::DFA}, HalfMatch, Input}; /// /// // Compile our original DFA. /// let original_dfa = DFA::new("foo[0-9]+")?; /// /// // Create a 4KB buffer on the stack to store our serialized DFA. /// let mut buf = [0u8; 4 * (1<<10)]; /// // N.B. We use native endianness here to make the example work, but /// // using write_to_little_endian would work on a little endian target. /// let written = original_dfa.write_to_native_endian(&mut buf)?; /// let dfa: DFA<&[u8]> = DFA::from_bytes(&buf[..written])?.0; /// /// let expected = Some(HalfMatch::must(0, 8)); /// assert_eq!(expected, dfa.try_search_fwd(&Input::new("foo12345"))?); /// # Ok::<(), Box<dyn std::error::Error>>(()) /// ``` pubfn write_to_little_endian(
&self,
dst: &mut [u8],
) -> Result<usize, SerializeError> { self.write_to::<wire::LE>(dst)
}
/// Serialize this DFA as raw bytes to the given slice, in big endian /// format. Upon success, the total number of bytes written to `dst` is /// returned. /// /// The written bytes are guaranteed to be deserialized correctly and /// without errors in a semver compatible release of this crate by a /// `DFA`'s deserialization APIs (assuming all other criteria for the /// deserialization APIs has been satisfied): /// /// * [`DFA::from_bytes`] /// * [`DFA::from_bytes_unchecked`] /// /// # Errors /// /// This returns an error if the given destination slice is not big enough /// to contain the full serialized DFA. If an error occurs, then nothing /// is written to `dst`. /// /// # Example /// /// This example shows how to serialize and deserialize a DFA without /// dynamic memory allocation. /// /// ``` /// use regex_automata::{dfa::{Automaton, sparse::DFA}, HalfMatch, Input}; /// /// // Compile our original DFA. /// let original_dfa = DFA::new("foo[0-9]+")?; /// /// // Create a 4KB buffer on the stack to store our serialized DFA. /// let mut buf = [0u8; 4 * (1<<10)]; /// // N.B. We use native endianness here to make the example work, but /// // using write_to_big_endian would work on a big endian target. /// let written = original_dfa.write_to_native_endian(&mut buf)?; /// let dfa: DFA<&[u8]> = DFA::from_bytes(&buf[..written])?.0; /// /// let expected = Some(HalfMatch::must(0, 8)); /// assert_eq!(expected, dfa.try_search_fwd(&Input::new("foo12345"))?); /// # Ok::<(), Box<dyn std::error::Error>>(()) /// ``` pubfn write_to_big_endian(
&self,
dst: &mut [u8],
) -> Result<usize, SerializeError> { self.write_to::<wire::BE>(dst)
}
/// Serialize this DFA as raw bytes to the given slice, in native endian /// format. Upon success, the total number of bytes written to `dst` is /// returned. /// /// The written bytes are guaranteed to be deserialized correctly and /// without errors in a semver compatible release of this crate by a /// `DFA`'s deserialization APIs (assuming all other criteria for the /// deserialization APIs has been satisfied): /// /// * [`DFA::from_bytes`] /// * [`DFA::from_bytes_unchecked`] /// /// Generally speaking, native endian format should only be used when /// you know that the target you're compiling the DFA for matches the /// endianness of the target on which you're compiling DFA. For example, /// if serialization and deserialization happen in the same process or on /// the same machine. Otherwise, when serializing a DFA for use in a /// portable environment, you'll almost certainly want to serialize _both_ /// a little endian and a big endian version and then load the correct one /// based on the target's configuration. /// /// # Errors /// /// This returns an error if the given destination slice is not big enough /// to contain the full serialized DFA. If an error occurs, then nothing /// is written to `dst`. /// /// # Example /// /// This example shows how to serialize and deserialize a DFA without /// dynamic memory allocation. /// /// ``` /// use regex_automata::{dfa::{Automaton, sparse::DFA}, HalfMatch, Input}; /// /// // Compile our original DFA. /// let original_dfa = DFA::new("foo[0-9]+")?; /// /// // Create a 4KB buffer on the stack to store our serialized DFA. /// let mut buf = [0u8; 4 * (1<<10)]; /// let written = original_dfa.write_to_native_endian(&mut buf)?; /// let dfa: DFA<&[u8]> = DFA::from_bytes(&buf[..written])?.0; /// /// let expected = Some(HalfMatch::must(0, 8)); /// assert_eq!(expected, dfa.try_search_fwd(&Input::new("foo12345"))?); /// # Ok::<(), Box<dyn std::error::Error>>(()) /// ``` pubfn write_to_native_endian(
&self,
dst: &mut [u8],
) -> Result<usize, SerializeError> { self.write_to::<wire::NE>(dst)
}
/// The implementation of the public `write_to` serialization methods, /// which is generic over endianness. fn write_to<E: Endian>(
&self,
dst: &mut [u8],
) -> Result<usize, SerializeError> { letmut nw = 0;
nw += wire::write_label(LABEL, &mut dst[nw..])?;
nw += wire::write_endianness_check::<E>(&mut dst[nw..])?;
nw += wire::write_version::<E>(VERSION, &mut dst[nw..])?;
nw += { // Currently unused, intended for future flexibility
E::write_u32(0, &mut dst[nw..]);
size_of::<u32>()
};
nw += self.flags.write_to::<E>(&mut dst[nw..])?;
nw += self.tt.write_to::<E>(&mut dst[nw..])?;
nw += self.st.write_to::<E>(&mut dst[nw..])?;
nw += self.special.write_to::<E>(&mut dst[nw..])?;
nw += self.quitset.write_to::<E>(&mut dst[nw..])?;
Ok(nw)
}
/// Return the total number of bytes required to serialize this DFA. /// /// This is useful for determining the size of the buffer required to pass /// to one of the serialization routines: /// /// * [`DFA::write_to_little_endian`] /// * [`DFA::write_to_big_endian`] /// * [`DFA::write_to_native_endian`] /// /// Passing a buffer smaller than the size returned by this method will /// result in a serialization error. /// /// # Example /// /// This example shows how to dynamically allocate enough room to serialize /// a sparse DFA. /// /// ``` /// use regex_automata::{dfa::{Automaton, sparse::DFA}, HalfMatch, Input}; /// /// // Compile our original DFA. /// let original_dfa = DFA::new("foo[0-9]+")?; /// /// let mut buf = vec![0; original_dfa.write_to_len()]; /// let written = original_dfa.write_to_native_endian(&mut buf)?; /// let dfa: DFA<&[u8]> = DFA::from_bytes(&buf[..written])?.0; /// /// let expected = Some(HalfMatch::must(0, 8)); /// assert_eq!(expected, dfa.try_search_fwd(&Input::new("foo12345"))?); /// # Ok::<(), Box<dyn std::error::Error>>(()) /// ``` pubfn write_to_len(&self) -> usize {
wire::write_label_len(LABEL)
+ wire::write_endianness_check_len()
+ wire::write_version_len()
+ size_of::<u32>() // unused, intended for future flexibility
+ self.flags.write_to_len()
+ self.tt.write_to_len()
+ self.st.write_to_len()
+ self.special.write_to_len()
+ self.quitset.write_to_len()
}
}
impl<'a> DFA<&'a [u8]> { /// Safely deserialize a sparse DFA with a specific state identifier /// representation. Upon success, this returns both the deserialized DFA /// and the number of bytes read from the given slice. Namely, the contents /// of the slice beyond the DFA are not read. /// /// Deserializing a DFA using this routine will never allocate heap memory. /// For safety purposes, the DFA's transitions will be verified such that /// every transition points to a valid state. If this verification is too /// costly, then a [`DFA::from_bytes_unchecked`] API is provided, which /// will always execute in constant time. /// /// The bytes given must be generated by one of the serialization APIs /// of a `DFA` using a semver compatible release of this crate. Those /// include: /// /// * [`DFA::to_bytes_little_endian`] /// * [`DFA::to_bytes_big_endian`] /// * [`DFA::to_bytes_native_endian`] /// * [`DFA::write_to_little_endian`] /// * [`DFA::write_to_big_endian`] /// * [`DFA::write_to_native_endian`] /// /// The `to_bytes` methods allocate and return a `Vec<u8>` for you. The /// `write_to` methods do not allocate and write to an existing slice /// (which may be on the stack). Since deserialization always uses the /// native endianness of the target platform, the serialization API you use /// should match the endianness of the target platform. (It's often a good /// idea to generate serialized DFAs for both forms of endianness and then /// load the correct one based on endianness.) /// /// # Errors /// /// Generally speaking, it's easier to state the conditions in which an /// error is _not_ returned. All of the following must be true: /// /// * The bytes given must be produced by one of the serialization APIs /// on this DFA, as mentioned above. /// * The endianness of the target platform matches the endianness used to /// serialized the provided DFA. /// /// If any of the above are not true, then an error will be returned. /// /// Note that unlike deserializing a /// [`dense::DFA`](crate::dfa::dense::DFA), deserializing a sparse DFA has /// no alignment requirements. That is, an alignment of `1` is valid. /// /// # Panics /// /// This routine will never panic for any input. /// /// # Example /// /// This example shows how to serialize a DFA to raw bytes, deserialize it /// and then use it for searching. /// /// ``` /// use regex_automata::{dfa::{Automaton, sparse::DFA}, HalfMatch, Input}; /// /// let initial = DFA::new("foo[0-9]+")?; /// let bytes = initial.to_bytes_native_endian(); /// let dfa: DFA<&[u8]> = DFA::from_bytes(&bytes)?.0; /// /// let expected = Some(HalfMatch::must(0, 8)); /// assert_eq!(expected, dfa.try_search_fwd(&Input::new("foo12345"))?); /// # Ok::<(), Box<dyn std::error::Error>>(()) /// ``` /// /// # Example: loading a DFA from static memory /// /// One use case this library supports is the ability to serialize a /// DFA to disk and then use `include_bytes!` to store it in a compiled /// Rust program. Those bytes can then be cheaply deserialized into a /// `DFA` structure at runtime and used for searching without having to /// re-compile the DFA (which can be quite costly). /// /// We can show this in two parts. The first part is serializing the DFA to /// a file: /// /// ```no_run /// use regex_automata::dfa::sparse::DFA; /// /// let dfa = DFA::new("foo[0-9]+")?; /// /// // Write a big endian serialized version of this DFA to a file. /// let bytes = dfa.to_bytes_big_endian(); /// std::fs::write("foo.bigendian.dfa", &bytes)?; /// /// // Do it again, but this time for little endian. /// let bytes = dfa.to_bytes_little_endian(); /// std::fs::write("foo.littleendian.dfa", &bytes)?; /// # Ok::<(), Box<dyn std::error::Error>>(()) /// ``` /// /// And now the second part is embedding the DFA into the compiled program /// and deserializing it at runtime on first use. We use conditional /// compilation to choose the correct endianness. We do not need to employ /// any special tricks to ensure a proper alignment, since a sparse DFA has /// no alignment requirements. /// /// ```no_run /// use regex_automata::{ /// dfa::{Automaton, sparse::DFA}, /// util::lazy::Lazy, /// HalfMatch, Input, /// }; /// /// // This crate provides its own "lazy" type, kind of like /// // lazy_static! or once_cell::sync::Lazy. But it works in no-alloc /// // no-std environments and let's us write this using completely /// // safe code. /// static RE: Lazy<DFA<&'static [u8]>> = Lazy::new(|| { /// # const _: &str = stringify! { /// #[cfg(target_endian = "big")] /// static BYTES: &[u8] = include_bytes!("foo.bigendian.dfa"); /// #[cfg(target_endian = "little")] /// static BYTES: &[u8] = include_bytes!("foo.littleendian.dfa"); /// # }; /// # static BYTES: &[u8] = b""; /// /// let (dfa, _) = DFA::from_bytes(BYTES) /// .expect("serialized DFA should be valid"); /// dfa /// }); /// /// let expected = Ok(Some(HalfMatch::must(0, 8))); /// assert_eq!(expected, RE.try_search_fwd(&Input::new("foo12345"))); /// ``` /// /// Alternatively, consider using /// [`lazy_static`](https://crates.io/crates/lazy_static) /// or /// [`once_cell`](https://crates.io/crates/once_cell), /// which will guarantee safety for you. pubfn from_bytes(
slice: &'a [u8],
) -> Result<(DFA<&'a [u8]>, usize), DeserializeError> { // SAFETY: This is safe because we validate both the sparse transitions // (by trying to decode every state) and start state ID list below. If // either validation fails, then we return an error. let (dfa, nread) = unsafe { DFA::from_bytes_unchecked(slice)? };
dfa.tt.validate(&dfa.special)?;
dfa.st.validate(&dfa.special, &dfa.tt)?; // N.B. dfa.special doesn't have a way to do unchecked deserialization, // so it has already been validated.
Ok((dfa, nread))
}
/// Deserialize a DFA with a specific state identifier representation in /// constant time by omitting the verification of the validity of the /// sparse transitions. /// /// This is just like [`DFA::from_bytes`], except it can potentially return /// a DFA that exhibits undefined behavior if its transitions contains /// invalid state identifiers. /// /// This routine is useful if you need to deserialize a DFA cheaply and /// cannot afford the transition validation performed by `from_bytes`. /// /// # Safety /// /// This routine is not safe because it permits callers to provide /// arbitrary transitions with possibly incorrect state identifiers. While /// the various serialization routines will never return an incorrect /// DFA, there is no guarantee that the bytes provided here are correct. /// While `from_bytes_unchecked` will still do several forms of basic /// validation, this routine does not check that the transitions themselves /// are correct. Given an incorrect transition table, it is possible for /// the search routines to access out-of-bounds memory because of explicit /// bounds check elision. /// /// # Example /// /// ``` /// use regex_automata::{dfa::{Automaton, sparse::DFA}, HalfMatch, Input}; /// /// let initial = DFA::new("foo[0-9]+")?; /// let bytes = initial.to_bytes_native_endian(); /// // SAFETY: This is guaranteed to be safe since the bytes given come /// // directly from a compatible serialization routine. /// let dfa: DFA<&[u8]> = unsafe { DFA::from_bytes_unchecked(&bytes)?.0 }; /// /// let expected = Some(HalfMatch::must(0, 8)); /// assert_eq!(expected, dfa.try_search_fwd(&Input::new("foo12345"))?); /// # Ok::<(), Box<dyn std::error::Error>>(()) /// ``` pubunsafefn from_bytes_unchecked(
slice: &'a [u8],
) -> Result<(DFA<&'a [u8]>, usize), DeserializeError> { letmut nr = 0;
nr += wire::read_label(&slice[nr..], LABEL)?;
nr += wire::read_endianness_check(&slice[nr..])?;
nr += wire::read_version(&slice[nr..], VERSION)?;
let _unused = wire::try_read_u32(&slice[nr..], "unused space")?;
nr += size_of::<u32>();
let (flags, nread) = Flags::from_bytes(&slice[nr..])?;
nr += nread;
let (tt, nread) = Transitions::from_bytes_unchecked(&slice[nr..])?;
nr += nread;
let (st, nread) = StartTable::from_bytes_unchecked(&slice[nr..])?;
nr += nread;
let (special, nread) = Special::from_bytes(&slice[nr..])?;
nr += nread; if special.max.as_usize() >= tt.sparse().len() { return Err(DeserializeError::generic( "max should not be greater than or equal to sparse bytes",
));
}
let (quitset, nread) = ByteSet::from_bytes(&slice[nr..])?;
nr += nread;
// Prefilters don't support serialization, so they're always absent. let pre = None;
Ok((DFA { tt, st, special, pre, quitset, flags }, nr))
}
}
// SAFETY: We assert that our implementation of each method is correct. unsafeimpl<T: AsRef<[u8]>> Automaton for DFA<T> { #[inline] fn is_special_state(&self, id: StateID) -> bool { self.special.is_special_state(id)
}
// This is marked as inline to help dramatically boost sparse searching, // which decodes each state it enters to follow the next transition. #[cfg_attr(feature = "perf-inline", inline(always))] fn next_state(&self, current: StateID, input: u8) -> StateID { let input = self.tt.classes.get(input); self.tt.state(current).next(input)
}
#[inline] fn match_pattern(&self, id: StateID, match_index: usize) -> PatternID { // This is an optimization for the very common case of a DFA with a // single pattern. This conditional avoids a somewhat more costly path // that finds the pattern ID from the state machine, which requires // a bit of slicing/pointer-chasing. This optimization tends to only // matter when matches are frequent. ifself.tt.pattern_len == 1 { return PatternID::ZERO;
} self.tt.state(id).pattern_id(match_index)
}
/// The transition table portion of a sparse DFA. /// /// The transition table is the core part of the DFA in that it describes how /// to move from one state to another based on the input sequence observed. /// /// Unlike a typical dense table based DFA, states in a sparse transition /// table have variable size. That is, states with more transitions use more /// space than states with fewer transitions. This means that finding the next /// transition takes more work than with a dense DFA, but also typically uses /// much less space. #[derive(Clone)] struct Transitions<T> { /// The raw encoding of each state in this DFA. /// /// Each state has the following information: /// /// * A set of transitions to subsequent states. Transitions to the dead /// state are omitted. /// * If the state can be accelerated, then any additional accelerator /// information. /// * If the state is a match state, then the state contains all pattern /// IDs that match when in that state. /// /// To decode a state, use Transitions::state. /// /// In practice, T is either Vec<u8> or &[u8].
sparse: T, /// A set of equivalence classes, where a single equivalence class /// represents a set of bytes that never discriminate between a match /// and a non-match in the DFA. Each equivalence class corresponds to a /// single character in this DFA's alphabet, where the maximum number of /// characters is 257 (each possible value of a byte plus the special /// EOI transition). Consequently, the number of equivalence classes /// corresponds to the number of transitions for each DFA state. Note /// though that the *space* used by each DFA state in the transition table /// may be larger. The total space used by each DFA state is known as the /// stride and is documented above. /// /// The only time the number of equivalence classes is fewer than 257 is /// if the DFA's kind uses byte classes which is the default. Equivalence /// classes should generally only be disabled when debugging, so that /// the transitions themselves aren't obscured. Disabling them has no /// other benefit, since the equivalence class map is always used while /// searching. In the vast majority of cases, the number of equivalence /// classes is substantially smaller than 257, particularly when large /// Unicode classes aren't used. /// /// N.B. Equivalence classes aren't particularly useful in a sparse DFA /// in the current implementation, since equivalence classes generally tend /// to correspond to continuous ranges of bytes that map to the same /// transition. So in a sparse DFA, equivalence classes don't really lead /// to a space savings. In the future, it would be good to try and remove /// them from sparse DFAs entirely, but requires a bit of work since sparse /// DFAs are built from dense DFAs, which are in turn built on top of /// equivalence classes.
classes: ByteClasses, /// The total number of states in this DFA. Note that a DFA always has at /// least one state---the dead state---even the empty DFA. In particular, /// the dead state always has ID 0 and is correspondingly always the first /// state. The dead state is never a match state.
state_len: usize, /// The total number of unique patterns represented by these match states.
pattern_len: usize,
}
wire::check_slice_len(slice, len, "sparse states byte length")?; let sparse = &slice[..len];
slice = &slice[len..];
let trans = Transitions { sparse, classes, state_len, pattern_len };
Ok((trans, slice.as_ptr().as_usize() - slice_start))
}
}
impl<T: AsRef<[u8]>> Transitions<T> { /// Writes a serialized form of this transition table to the buffer given. /// If the buffer is too small, then an error is returned. To determine /// how big the buffer must be, use `write_to_len`. fn write_to<E: Endian>(
&self, mut dst: &mut [u8],
) -> Result<usize, SerializeError> { let nwrite = self.write_to_len(); if dst.len() < nwrite { return Err(SerializeError::buffer_too_small( "sparse transition table",
));
}
dst = &mut dst[..nwrite];
// write state length
E::write_u32(u32::try_from(self.state_len).unwrap(), dst);
dst = &mut dst[size_of::<u32>()..];
// write byte class map let n = self.classes.write_to(dst)?;
dst = &mut dst[n..];
// write number of bytes in sparse transitions
E::write_u32(u32::try_from(self.sparse().len()).unwrap(), dst);
dst = &mut dst[size_of::<u32>()..];
// write actual transitions letmut id = DEAD; while id.as_usize() < self.sparse().len() { let state = self.state(id); let n = state.write_to::<E>(&mut dst)?;
dst = &mut dst[n..]; // The next ID is the offset immediately following `state`.
id = StateID::new(id.as_usize() + state.write_to_len()).unwrap();
}
Ok(nwrite)
}
/// Returns the number of bytes the serialized form of this transition /// table will use. fn write_to_len(&self) -> usize {
size_of::<u32>() // state length
+ size_of::<u32>() // pattern length
+ self.classes.write_to_len()
+ size_of::<u32>() // sparse transitions length
+ self.sparse().len()
}
/// Validates that every state ID in this transition table is valid. /// /// That is, every state ID can be used to correctly index a state in this /// table. fn validate(&self, sp: &Special) -> Result<(), DeserializeError> { // In order to validate everything, we not only need to make sure we // can decode every state, but that every transition in every state // points to a valid state. There are many duplicative transitions, so // we record state IDs that we've verified so that we don't redo the // decoding work. // // Except, when in no_std mode, we don't have dynamic memory allocation // available to us, so we skip this optimization. It's not clear // whether doing something more clever is worth it just yet. If you're // profiling this code and need it to run faster, please file an issue. // // OK, so we also use this to record the set of valid state IDs. Since // it is possible for a transition to point to an invalid state ID that // still (somehow) deserializes to a valid state. So we need to make // sure our transitions are limited to actually correct state IDs. // The problem is, I'm not sure how to do this verification step in // no-std no-alloc mode. I think we'd *have* to store the set of valid // state IDs in the DFA itself. For now, we don't do this verification // in no-std no-alloc mode. The worst thing that can happen is an // incorrect result. But no panics or memory safety problems should // result. Because we still do validate that the state itself is // "valid" in the sense that everything it points to actually exists. // // ---AG struct Seen { #[cfg(feature = "alloc")]
set: alloc::collections::BTreeSet<StateID>, #[cfg(not(feature = "alloc"))]
set: core::marker::PhantomData<StateID>,
}
letmut verified: Seen = Seen::new(); // We need to make sure that we decode the correct number of states. // Otherwise, an empty set of transitions would validate even if the // recorded state length is non-empty. letmut len = 0; // We can't use the self.states() iterator because it assumes the state // encodings are valid. It could panic if they aren't. letmut id = DEAD; while id.as_usize() < self.sparse().len() { // Before we even decode the state, we check that the ID itself // is well formed. That is, if it's a special state then it must // actually be a quit, dead, accel, match or start state. if sp.is_special_state(id) { let is_actually_special = sp.is_dead_state(id)
|| sp.is_quit_state(id)
|| sp.is_match_state(id)
|| sp.is_start_state(id)
|| sp.is_accel_state(id); if !is_actually_special { // This is kind of a cryptic error message... return Err(DeserializeError::generic( "found sparse state tagged as special but \
wasn't actually special",
));
}
} let state = self.try_state(sp, id)?;
verified.insert(id); // The next ID should be the offset immediately following `state`.
id = StateID::new(wire::add(
id.as_usize(),
state.write_to_len(), "next state ID offset",
)?)
.map_err(|err| {
DeserializeError::state_id_error(err, "next state ID offset")
})?;
len += 1;
} // Now that we've checked that all top-level states are correct and // importantly, collected a set of valid state IDs, we have all the // information we need to check that all transitions are correct too. // // Note that we can't use `valid_ids` to iterate because it will // be empty in no-std no-alloc contexts. (And yes, that means our // verification isn't quite as good.) We can use `self.states()` // though at least, since we know that all states can at least be // decoded and traversed correctly. for state inself.states() { // Check that all transitions in this state are correct. for i in0..state.ntrans { let to = state.next_at(i); // For no-alloc, we just check that the state can decode. It is // technically possible that the state ID could still point to // a non-existent state even if it decodes (fuzzing proved this // to be true), but it shouldn't result in any memory unsafety // or panics in non-debug mode. #[cfg(not(feature = "alloc"))]
{ let _ = self.try_state(sp, to)?;
} #[cfg(feature = "alloc")]
{ if !verified.contains(&to) { return Err(DeserializeError::generic( "found transition that points to a \
non-existent state",
));
}
}
}
} if len != self.state_len { return Err(DeserializeError::generic( "mismatching sparse state length",
));
}
Ok(())
}
/// Converts these transitions to a borrowed value. fn as_ref(&self) -> Transitions<&'_ [u8]> {
Transitions {
sparse: self.sparse(),
classes: self.classes.clone(),
state_len: self.state_len,
pattern_len: self.pattern_len,
}
}
/// Converts these transitions to an owned value. #[cfg(feature = "alloc")] fn to_owned(&self) -> Transitions<alloc::vec::Vec<u8>> {
Transitions {
sparse: self.sparse().to_vec(),
classes: self.classes.clone(),
state_len: self.state_len,
pattern_len: self.pattern_len,
}
}
/// Return a convenient representation of the given state. /// /// This panics if the state is invalid. /// /// This is marked as inline to help dramatically boost sparse searching, /// which decodes each state it enters to follow the next transition. Other /// functions involved are also inlined, which should hopefully eliminate /// a lot of the extraneous decoding that is never needed just to follow /// the next transition. #[cfg_attr(feature = "perf-inline", inline(always))] fn state(&self, id: StateID) -> State<'_> { letmut state = &self.sparse()[id.as_usize()..]; letmut ntrans = wire::read_u16(&state).as_usize(); let is_match = (1 << 15) & ntrans != 0;
ntrans &= !(1 << 15);
state = &state[2..];
let (input_ranges, state) = state.split_at(ntrans * 2); let (next, state) = state.split_at(ntrans * StateID::SIZE); let (pattern_ids, state) = if is_match { let npats = wire::read_u32(&state).as_usize();
state[4..].split_at(npats * 4)
} else {
(&[][..], state)
};
let accel_len = usize::from(state[0]); let accel = &state[1..accel_len + 1];
State { id, is_match, ntrans, input_ranges, next, pattern_ids, accel }
}
/// Like `state`, but will return an error if the state encoding is /// invalid. This is useful for verifying states after deserialization, /// which is required for a safe deserialization API. /// /// Note that this only verifies that this state is decodable and that /// all of its data is consistent. It does not verify that its state ID /// transitions point to valid states themselves, nor does it verify that /// every pattern ID is valid. fn try_state(
&self,
sp: &Special,
id: StateID,
) -> Result<State<'_>, DeserializeError> { if id.as_usize() > self.sparse().len() { return Err(DeserializeError::generic( "invalid caller provided sparse state ID",
));
} letmut state = &self.sparse()[id.as_usize()..]; // Encoding format starts with a u16 that stores the total number of // transitions in this state. let (mut ntrans, _) =
wire::try_read_u16_as_usize(state, "state transition length")?; let is_match = ((1 << 15) & ntrans) != 0;
ntrans &= !(1 << 15);
state = &state[2..]; if ntrans > 257 || ntrans == 0 { return Err(DeserializeError::generic( "invalid transition length",
));
} if is_match && !sp.is_match_state(id) { return Err(DeserializeError::generic( "state marked as match but not in match ID range",
));
} elseif !is_match && sp.is_match_state(id) { return Err(DeserializeError::generic( "state in match ID range but not marked as match state",
));
}
// Each transition has two pieces: an inclusive range of bytes on which // it is defined, and the state ID that those bytes transition to. The // pairs come first, followed by a corresponding sequence of state IDs. let input_ranges_len = ntrans.checked_mul(2).unwrap();
wire::check_slice_len(state, input_ranges_len, "sparse byte pairs")?; let (input_ranges, state) = state.split_at(input_ranges_len); // Every range should be of the form A-B, where A<=B. for pair in input_ranges.chunks(2) { let (start, end) = (pair[0], pair[1]); if start > end { return Err(DeserializeError::generic("invalid input range"));
}
}
// And now extract the corresponding sequence of state IDs. We leave // this sequence as a &[u8] instead of a &[S] because sparse DFAs do // not have any alignment requirements. let next_len = ntrans
.checked_mul(self.id_len())
.expect("state size * #trans should always fit in a usize");
wire::check_slice_len(state, next_len, "sparse trans state IDs")?; let (next, state) = state.split_at(next_len); // We can at least verify that every state ID is in bounds. for idbytes in next.chunks(self.id_len()) { let (id, _) =
wire::read_state_id(idbytes, "sparse state ID in try_state")?;
wire::check_slice_len( self.sparse(),
id.as_usize(), "invalid sparse state ID",
)?;
}
// If this is a match state, then read the pattern IDs for this state. // Pattern IDs is a u32-length prefixed sequence of native endian // encoded 32-bit integers. let (pattern_ids, state) = if is_match { let (npats, nr) =
wire::try_read_u32_as_usize(state, "pattern ID length")?; let state = &state[nr..]; if npats == 0 { return Err(DeserializeError::generic( "state marked as a match, but has no pattern IDs",
));
}
let pattern_ids_len =
wire::mul(npats, 4, "sparse pattern ID byte length")?;
wire::check_slice_len(
state,
pattern_ids_len, "sparse pattern IDs",
)?; let (pattern_ids, state) = state.split_at(pattern_ids_len); for patbytes in pattern_ids.chunks(PatternID::SIZE) {
wire::read_pattern_id(
patbytes, "sparse pattern ID in try_state",
)?;
}
(pattern_ids, state)
} else {
(&[][..], state)
};
// Now read this state's accelerator info. The first byte is the length // of the accelerator, which is typically 0 (for no acceleration) but // is no bigger than 3. The length indicates the number of bytes that // follow, where each byte corresponds to a transition out of this // state. if state.is_empty() { return Err(DeserializeError::generic("no accelerator length"));
} let (accel_len, state) = (usize::from(state[0]), &state[1..]);
if accel_len > 3 { return Err(DeserializeError::generic( "sparse invalid accelerator length",
));
} elseif accel_len == 0 && sp.is_accel_state(id) { return Err(DeserializeError::generic( "got no accelerators in state, but in accelerator ID range",
));
} elseif accel_len > 0 && !sp.is_accel_state(id) { return Err(DeserializeError::generic( "state in accelerator ID range, but has no accelerators",
));
}
let state = State {
id,
is_match,
ntrans,
input_ranges,
next,
pattern_ids,
accel,
}; if sp.is_quit_state(state.next_at(state.ntrans - 1)) { return Err(DeserializeError::generic( "state with EOI transition to quit state is illegal",
));
}
Ok(state)
}
/// Return an iterator over all of the states in this DFA. /// /// The iterator returned yields tuples, where the first element is the /// state ID and the second element is the state itself. fn states(&self) -> StateIter<'_, T> {
StateIter { trans: self, id: DEAD.as_usize() }
}
/// Returns the sparse transitions as raw bytes. fn sparse(&self) -> &[u8] { self.sparse.as_ref()
}
/// Returns the number of bytes represented by a single state ID. fn id_len(&self) -> usize {
StateID::SIZE
}
/// Return the memory usage, in bytes, of these transitions. /// /// This does not include the size of a `Transitions` value itself. fn memory_usage(&self) -> usize { self.sparse().len()
}
}
#[cfg(feature = "dfa-build")] impl<T: AsMut<[u8]>> Transitions<T> { /// Return a convenient mutable representation of the given state. /// This panics if the state is invalid. fn state_mut(&mutself, id: StateID) -> StateMut<'_> { letmut state = &mutself.sparse_mut()[id.as_usize()..]; letmut ntrans = wire::read_u16(&state).as_usize(); let is_match = (1 << 15) & ntrans != 0;
ntrans &= !(1 << 15);
state = &mut state[2..];
let (input_ranges, state) = state.split_at_mut(ntrans * 2); let (next, state) = state.split_at_mut(ntrans * StateID::SIZE); let (pattern_ids, state) = if is_match { let npats = wire::read_u32(&state).as_usize();
state[4..].split_at_mut(npats * 4)
} else {
(&mut [][..], state)
};
/// Returns the sparse transitions as raw mutable bytes. fn sparse_mut(&mutself) -> &mut [u8] { self.sparse.as_mut()
}
}
/// The set of all possible starting states in a DFA. /// /// See the eponymous type in the `dense` module for more details. This type /// is very similar to `dense::StartTable`, except that its underlying /// representation is `&[u8]` instead of `&[S]`. (The latter would require /// sparse DFAs to be aligned, which is explicitly something we do not require /// because we don't really need it.) #[derive(Clone)] struct StartTable<T> { /// The initial start state IDs as a contiguous table of native endian /// encoded integers, represented by `S`. /// /// In practice, T is either Vec<u8> or &[u8] and has no alignment /// requirements. /// /// The first `2 * stride` (currently always 8) entries always correspond /// to the starts states for the entire DFA, with the first 4 entries being /// for unanchored searches and the second 4 entries being for anchored /// searches. To keep things simple, we always use 8 entries even if the /// `StartKind` is not both. /// /// After that, there are `stride * patterns` state IDs, where `patterns` /// may be zero in the case of a DFA with no patterns or in the case where /// the DFA was built without enabling starting states for each pattern.
table: T, /// The starting state configuration supported. When 'both', both /// unanchored and anchored searches work. When 'unanchored', anchored /// searches panic. When 'anchored', unanchored searches panic.
kind: StartKind, /// The start state configuration for every possible byte.
start_map: StartByteMap, /// The number of starting state IDs per pattern.
stride: usize, /// The total number of patterns for which starting states are encoded. /// This is `None` for DFAs that were built without start states for each /// pattern. Thus, one cannot use this field to say how many patterns /// are in the DFA in all cases. It is specific to how many patterns are /// represented in this start table.
pattern_len: Option<usize>, /// The universal starting state for unanchored searches. This is only /// present when the DFA supports unanchored searches and when all starting /// state IDs for an unanchored search are equivalent.
universal_start_unanchored: Option<StateID>, /// The universal starting state for anchored searches. This is only /// present when the DFA supports anchored searches and when all starting /// state IDs for an anchored search are equivalent.
universal_start_anchored: Option<StateID>,
}
#[cfg(feature = "dfa-build")] impl StartTable<Vec<u8>> { fn new<T: AsRef<[u32]>>(
dfa: &dense::DFA<T>,
pattern_len: Option<usize>,
) -> StartTable<Vec<u8>> { let stride = Start::len(); // This is OK since the only way we're here is if a dense DFA could be // constructed successfully, which uses the same space. let len = stride
.checked_mul(pattern_len.unwrap_or(0))
.unwrap()
.checked_add(stride.checked_mul(2).unwrap())
.unwrap()
.checked_mul(StateID::SIZE)
.unwrap();
StartTable {
table: vec![0; len],
kind: dfa.start_kind(),
start_map: dfa.start_map().clone(),
stride,
pattern_len,
universal_start_unanchored: dfa
.universal_start_state(Anchored::No),
universal_start_anchored: dfa.universal_start_state(Anchored::Yes),
}
}
fn from_dense_dfa<T: AsRef<[u32]>>(
dfa: &dense::DFA<T>,
remap: &[StateID],
) -> Result<StartTable<Vec<u8>>, BuildError> { // Unless the DFA has start states compiled for each pattern, then // as far as the starting state table is concerned, there are zero // patterns to account for. It will instead only store starting states // for the entire DFA. let start_pattern_len = if dfa.starts_for_each_pattern() {
Some(dfa.pattern_len())
} else {
None
}; letmut sl = StartTable::new(dfa, start_pattern_len); for (old_start_id, anchored, sty) in dfa.starts() { let new_start_id = remap[dfa.to_index(old_start_id)];
sl.set_start(anchored, sty, new_start_id);
}
Ok(sl)
}
}
let pattern_table_size = wire::mul(
stride,
pattern_len.unwrap_or(0), "sparse invalid pattern length",
)?; // Our start states always start with a single stride of start states // for the entire automaton which permit it to match any pattern. What // follows it are an optional set of start states for each pattern. let start_state_len = wire::add(
wire::mul(2, stride, "start state stride too big")?,
pattern_table_size, "sparse invalid 'any' pattern starts size",
)?; let table_bytes_len = wire::mul(
start_state_len,
StateID::SIZE, "sparse pattern table bytes length",
)?;
wire::check_slice_len(
slice,
table_bytes_len, "sparse start ID table",
)?; let table = &slice[..table_bytes_len];
slice = &slice[table_bytes_len..];
/// Returns the number of bytes the serialized form of this transition /// table will use. fn write_to_len(&self) -> usize { self.kind.write_to_len()
+ self.start_map.write_to_len()
+ size_of::<u32>() // stride
+ size_of::<u32>() // # patterns
+ size_of::<u32>() // universal unanchored start
+ size_of::<u32>() // universal anchored start
+ self.table().len()
}
/// Validates that every starting state ID in this table is valid. /// /// That is, every starting state ID can be used to correctly decode a /// state in the DFA's sparse transitions. fn validate(
&self,
sp: &Special,
trans: &Transitions<T>,
) -> Result<(), DeserializeError> { for (id, _, _) inself.iter() { if sp.is_match_state(id) { return Err(DeserializeError::generic( "start states cannot be match states",
));
} // Confirm that the start state points to a valid state. let state = trans.try_state(sp, id)?; // And like for the transition table, confirm that the transitions // on all start states themselves point to a valid state. // // It'd probably be better to integrate this validation with the // transition table, or otherwise store a sorted sequence of all // valid state IDs in the sparse DFA itself. That way, we could // check that every pointer to a state corresponds precisely to a // correct and valid state. for i in0..state.ntrans { let to = state.next_at(i); let _ = trans.try_state(sp, to)?;
}
}
Ok(())
}
/// Converts this start list to a borrowed value. fn as_ref(&self) -> StartTable<&'_ [u8]> {
StartTable {
table: self.table(),
kind: self.kind,
start_map: self.start_map.clone(),
stride: self.stride,
pattern_len: self.pattern_len,
universal_start_unanchored: self.universal_start_unanchored,
universal_start_anchored: self.universal_start_anchored,
}
}
/// Converts this start list to an owned value. #[cfg(feature = "alloc")] fn to_owned(&self) -> StartTable<alloc::vec::Vec<u8>> {
StartTable {
table: self.table().to_vec(),
kind: self.kind,
start_map: self.start_map.clone(),
stride: self.stride,
pattern_len: self.pattern_len,
universal_start_unanchored: self.universal_start_unanchored,
universal_start_anchored: self.universal_start_anchored,
}
}
/// Return the start state for the given index and pattern ID. If the /// pattern ID is None, then the corresponding start state for the entire /// DFA is returned. If the pattern ID is not None, then the corresponding /// starting state for the given pattern is returned. If this start table /// does not have individual starting states for each pattern, then this /// panics. fn start(
&self,
input: &Input<'_>,
start: Start,
) -> Result<StateID, MatchError> { let start_index = start.as_usize(); let mode = input.get_anchored(); let index = match mode {
Anchored::No => { if !self.kind.has_unanchored() { return Err(MatchError::unsupported_anchored(mode));
}
start_index
}
Anchored::Yes => { if !self.kind.has_anchored() { return Err(MatchError::unsupported_anchored(mode));
} self.stride + start_index
}
Anchored::Pattern(pid) => { let len = matchself.pattern_len {
None => { return Err(MatchError::unsupported_anchored(mode))
}
Some(len) => len,
}; if pid.as_usize() >= len { return Ok(DEAD);
}
(2 * self.stride)
+ (self.stride * pid.as_usize())
+ start_index
}
}; let start = index * StateID::SIZE; // This OK since we're allowed to assume that the start table contains // valid StateIDs.
Ok(wire::read_state_id_unchecked(&self.table()[start..]).0)
}
/// Return an iterator over all start IDs in this table. fn iter(&self) -> StartStateIter<'_, T> {
StartStateIter { st: self, i: 0 }
}
/// Returns the total number of start state IDs in this table. fn len(&self) -> usize { self.table().len() / StateID::SIZE
}
/// Returns the table as a raw slice of bytes. fn table(&self) -> &[u8] { self.table.as_ref()
}
/// Return the memory usage, in bytes, of this start list. /// /// This does not include the size of a `StartTable` value itself. fn memory_usage(&self) -> usize { self.table().len()
}
}
#[cfg(feature = "dfa-build")] impl<T: AsMut<[u8]>> StartTable<T> { /// Set the start state for the given index and pattern. /// /// If the pattern ID or state ID are not valid, then this will panic. fn set_start(&mutself, anchored: Anchored, start: Start, id: StateID) { let start_index = start.as_usize(); let index = match anchored {
Anchored::No => start_index,
Anchored::Yes => self.stride + start_index,
Anchored::Pattern(pid) => { let pid = pid.as_usize(); let len = self
.pattern_len
.expect("start states for each pattern enabled");
assert!(pid < len, "invalid pattern ID {:?}", pid); self.stride
.checked_mul(pid)
.unwrap()
.checked_add(self.stride.checked_mul(2).unwrap())
.unwrap()
.checked_add(start_index)
.unwrap()
}
}; let start = index * StateID::SIZE; let end = start + StateID::SIZE;
wire::write_state_id::<wire::NE>(
id,
&mutself.table.as_mut()[start..end],
);
}
}
/// An iterator over all state state IDs in a sparse DFA. struct StartStateIter<'a, T> {
st: &'a StartTable<T>,
i: usize,
}
impl<'a, T: AsRef<[u8]>> Iterator for StartStateIter<'a, T> { type Item = (StateID, Anchored, Start);
fn next(&mutself) -> Option<(StateID, Anchored, Start)> { let i = self.i; if i >= self.st.len() { return None;
} self.i += 1;
// This unwrap is okay since the stride of any DFA must always match // the number of start state types. let start_type = Start::from_usize(i % self.st.stride).unwrap(); let anchored = if i < self.st.stride {
Anchored::No
} elseif i < (2 * self.st.stride) {
Anchored::Yes
} else { let pid = (i - (2 * self.st.stride)) / self.st.stride;
Anchored::Pattern(PatternID::new(pid).unwrap())
}; let start = i * StateID::SIZE; let end = start + StateID::SIZE; let bytes = self.st.table()[start..end].try_into().unwrap(); // This is OK since we're allowed to assume that any IDs in this start // table are correct and valid for this DFA. let id = StateID::from_ne_bytes_unchecked(bytes);
Some((id, anchored, start_type))
}
}
/// An iterator over all states in a sparse DFA. /// /// This iterator yields tuples, where the first element is the state ID and /// the second element is the state itself. struct StateIter<'a, T> {
trans: &'a Transitions<T>,
id: usize,
}
impl<'a, T: AsRef<[u8]>> Iterator for StateIter<'a, T> { type Item = State<'a>;
/// A representation of a sparse DFA state that can be cheaply materialized /// from a state identifier. #[derive(Clone)] struct State<'a> { /// The identifier of this state.
id: StateID, /// Whether this is a match state or not.
is_match: bool, /// The number of transitions in this state.
ntrans: usize, /// Pairs of input ranges, where there is one pair for each transition. /// Each pair specifies an inclusive start and end byte range for the /// corresponding transition.
input_ranges: &'a [u8], /// Transitions to the next state. This slice contains native endian /// encoded state identifiers, with `S` as the representation. Thus, there /// are `ntrans * size_of::<S>()` bytes in this slice.
next: &'a [u8], /// If this is a match state, then this contains the pattern IDs that match /// when the DFA is in this state. /// /// This is a contiguous sequence of 32-bit native endian encoded integers.
pattern_ids: &'a [u8], /// An accelerator for this state, if present. If this state has no /// accelerator, then this is an empty slice. When non-empty, this slice /// has length at most 3 and corresponds to the exhaustive set of bytes /// that must be seen in order to transition out of this state.
accel: &'a [u8],
}
impl<'a> State<'a> { /// Searches for the next transition given an input byte. If no such /// transition could be found, then a dead state is returned. /// /// This is marked as inline to help dramatically boost sparse searching, /// which decodes each state it enters to follow the next transition. #[cfg_attr(feature = "perf-inline", inline(always))] fn next(&self, input: u8) -> StateID { // This straight linear search was observed to be much better than // binary search on ASCII haystacks, likely because a binary search // visits the ASCII case last but a linear search sees it first. A // binary search does do a little better on non-ASCII haystacks, but // not by much. There might be a better trade off lurking here. for i in0..(self.ntrans - 1) { let (start, end) = self.range(i); if start <= input && input <= end { returnself.next_at(i);
} // We could bail early with an extra branch: if input < b1, then // we know we'll never find a matching transition. Interestingly, // this extra branch seems to not help performance, or will even // hurt it. It's likely very dependent on the DFA itself and what // is being searched.
}
DEAD
}
/// Returns the next state ID for the special EOI transition. fn next_eoi(&self) -> StateID { self.next_at(self.ntrans - 1)
}
/// Returns the identifier for this state. fn id(&self) -> StateID { self.id
}
/// Returns the inclusive input byte range for the ith transition in this /// state. fn range(&self, i: usize) -> (u8, u8) {
(self.input_ranges[i * 2], self.input_ranges[i * 2 + 1])
}
/// Returns the next state for the ith transition in this state. fn next_at(&self, i: usize) -> StateID { let start = i * StateID::SIZE; let end = start + StateID::SIZE; let bytes = self.next[start..end].try_into().unwrap();
StateID::from_ne_bytes_unchecked(bytes)
}
/// Returns the pattern ID for the given match index. If the match index /// is invalid, then this panics. fn pattern_id(&self, match_index: usize) -> PatternID { let start = match_index * PatternID::SIZE;
wire::read_pattern_id_unchecked(&self.pattern_ids[start..]).0
}
/// Returns the total number of pattern IDs for this state. This is always /// zero when `is_match` is false. fn pattern_len(&self) -> usize {
assert_eq!(0, self.pattern_ids.len() % 4); self.pattern_ids.len() / 4
}
/// Return an accelerator for this state. fn accelerator(&self) -> &'a [u8] { self.accel
}
/// Write the raw representation of this state to the given buffer using /// the given endianness. fn write_to<E: Endian>(
&self, mut dst: &mut [u8],
) -> Result<usize, SerializeError> { let nwrite = self.write_to_len(); if dst.len() < nwrite { return Err(SerializeError::buffer_too_small( "sparse state transitions",
));
}
/// Return the total number of bytes that this state consumes in its /// encoded form. fn write_to_len(&self) -> usize { letmut len = 2
+ (self.ntrans * 2)
+ (self.ntrans * StateID::SIZE)
+ (1 + self.accel.len()); ifself.is_match {
len += size_of::<u32>() + self.pattern_ids.len();
}
len
}
}
impl<'a> fmt::Debug for State<'a> { fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result { letmut printed = false; for i in0..(self.ntrans - 1) { let next = self.next_at(i); if next == DEAD { continue;
}
if printed {
write!(f, ", ")?;
} let (start, end) = self.range(i); if start == end {
write!(f, "{:?} => {:?}", DebugByte(start), next.as_usize())?;
} else {
write!(
f, "{:?}-{:?} => {:?}",
DebugByte(start),
DebugByte(end),
next.as_usize(),
)?;
}
printed = true;
} let eoi = self.next_at(self.ntrans - 1); if eoi != DEAD { if printed {
write!(f, ", ")?;
}
write!(f, "EOI => {:?}", eoi.as_usize())?;
}
Ok(())
}
}
/// A representation of a mutable sparse DFA state that can be cheaply /// materialized from a state identifier. #[cfg(feature = "dfa-build")] struct StateMut<'a> { /// The identifier of this state.
id: StateID, /// Whether this is a match state or not.
is_match: bool, /// The number of transitions in this state.
ntrans: usize, /// Pairs of input ranges, where there is one pair for each transition. /// Each pair specifies an inclusive start and end byte range for the /// corresponding transition.
input_ranges: &'a mut [u8], /// Transitions to the next state. This slice contains native endian /// encoded state identifiers, with `S` as the representation. Thus, there /// are `ntrans * size_of::<S>()` bytes in this slice.
next: &'a mut [u8], /// If this is a match state, then this contains the pattern IDs that match /// when the DFA is in this state. /// /// This is a contiguous sequence of 32-bit native endian encoded integers.
pattern_ids: &'a [u8], /// An accelerator for this state, if present. If this state has no /// accelerator, then this is an empty slice. When non-empty, this slice /// has length at most 3 and corresponds to the exhaustive set of bytes /// that must be seen in order to transition out of this state.
accel: &'a mut [u8],
}
#[cfg(feature = "dfa-build")] impl<'a> StateMut<'a> { /// Sets the ith transition to the given state. fn set_next_at(&mutself, i: usize, next: StateID) { let start = i * StateID::SIZE; let end = start + StateID::SIZE;
wire::write_state_id::<wire::NE>(next, &mutself.next[start..end]);
}
}
#[cfg(feature = "dfa-build")] impl<'a> fmt::Debug for StateMut<'a> { fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result { let state = State {
id: self.id,
is_match: self.is_match,
ntrans: self.ntrans,
input_ranges: self.input_ranges,
next: self.next,
pattern_ids: self.pattern_ids,
accel: self.accel,
};
fmt::Debug::fmt(&state, f)
}
}
/* /// A binary search routine specialized specifically to a sparse DFA state's /// transitions. Specifically, the transitions are defined as a set of pairs /// of input bytes that delineate an inclusive range of bytes. If the input /// byte is in the range, then the corresponding transition is a match. /// /// This binary search accepts a slice of these pairs and returns the position /// of the matching pair (the ith transition), or None if no matching pair /// could be found. /// /// Note that this routine is not currently used since it was observed to /// either decrease performance when searching ASCII, or did not provide enough /// of a boost on non-ASCII haystacks to be worth it. However, we leave it here /// for posterity in case we can find a way to use it. /// /// In theory, we could use the standard library's search routine if we could /// cast a `&[u8]` to a `&[(u8, u8)]`, but I don't believe this is currently /// guaranteed to be safe and is thus UB (since I don't think the in-memory /// representation of `(u8, u8)` has been nailed down). One could define a /// repr(C) type, but the casting doesn't seem justified. #[cfg_attr(feature="perf-inline",inline(always))] fnbinary_search_ranges(ranges:&[u8],needle:u8)->Option<usize>{ debug_assert!(ranges.len()%2==0,"rangesmusthaveevenlength"); debug_assert!(ranges.len()<=512,"rangesshouldbeshort");
// See the analogous test in src/hybrid/dfa.rs and src/dfa/dense.rs. #[test] fn heuristic_unicode_forward() { let dfa = DFA::builder()
.configure(DFA::config().unicode_word_boundary(true))
.thompson(thompson::Config::new().reverse(true))
.build(r"\b[0-9]+\b")
.unwrap()
.to_sparse()
.unwrap();
let input = Input::new("β123").range(2..); let expected = MatchError::quit(0xB2, 1); let got = dfa.try_search_fwd(&input);
assert_eq!(Err(expected), got);
let input = Input::new("123β").range(..3); let expected = MatchError::quit(0xCE, 3); let got = dfa.try_search_fwd(&input);
assert_eq!(Err(expected), got);
}
// See the analogous test in src/hybrid/dfa.rs and src/dfa/dense.rs. #[test] fn heuristic_unicode_reverse() { let dfa = DFA::builder()
.configure(DFA::config().unicode_word_boundary(true))
.thompson(thompson::Config::new().reverse(true))
.build(r"\b[0-9]+\b")
.unwrap()
.to_sparse()
.unwrap();
let input = Input::new("β123").range(2..); let expected = MatchError::quit(0xB2, 1); let got = dfa.try_search_rev(&input);
assert_eq!(Err(expected), got);
let input = Input::new("123β").range(..3); let expected = MatchError::quit(0xCE, 3); let got = dfa.try_search_rev(&input);
assert_eq!(Err(expected), got);
}
}
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