//! Term search use hir_def::type_ref::Mutability; use hir_ty::db::HirDatabase; use itertools::Itertools; use rustc_hash::{FxHashMap, FxHashSet}; use crate::{ModuleDef, ScopeDef, Semantics, SemanticsScope, Type}; mod expr; pub use expr::Expr; mod tactics; /// Key for lookup table to query new types reached. #[derive(Debug, Hash, PartialEq, Eq)] enum NewTypesKey { ImplMethod, StructProjection, } /// Helper enum to squash big number of alternative trees into `Many` variant as there is too many /// to take into account. #[derive(Debug)] enum AlternativeExprs { /// There are few trees, so we keep track of them all Few(FxHashSet), /// There are too many trees to keep track of Many, } impl AlternativeExprs { /// Construct alternative trees /// /// # Arguments /// `threshold` - threshold value for many trees (more than that is many) /// `exprs` - expressions iterator fn new(threshold: usize, exprs: impl Iterator) -> AlternativeExprs { let mut it = AlternativeExprs::Few(Default::default()); it.extend_with_threshold(threshold, exprs); it } /// Get type trees stored in alternative trees (or `Expr::Many` in case of many) /// /// # Arguments /// `ty` - Type of expressions queried (this is used to give type to `Expr::Many`) fn exprs(&self, ty: &Type) -> Vec { match self { AlternativeExprs::Few(exprs) => exprs.iter().cloned().collect(), AlternativeExprs::Many => vec![Expr::Many(ty.clone())], } } /// Extend alternative expressions /// /// # Arguments /// `threshold` - threshold value for many trees (more than that is many) /// `exprs` - expressions iterator fn extend_with_threshold(&mut self, threshold: usize, mut exprs: impl Iterator) { match self { AlternativeExprs::Few(tts) => { while let Some(it) = exprs.next() { if tts.len() > threshold { *self = AlternativeExprs::Many; break; } tts.insert(it); } } AlternativeExprs::Many => (), } } } /// # Lookup table for term search /// /// Lookup table keeps all the state during term search. /// This means it knows what types and how are reachable. /// /// The secondary functionality for lookup table is to keep track of new types reached since last /// iteration as well as keeping track of which `ScopeDef` items have been used. /// Both of them are to speed up the term search by leaving out types / ScopeDefs that likely do /// not produce any new results. #[derive(Default, Debug)] struct LookupTable { /// All the `Expr`s in "value" produce the type of "key" data: FxHashMap, /// New types reached since last query by the `NewTypesKey` new_types: FxHashMap>, /// ScopeDefs that are not interesting any more exhausted_scopedefs: FxHashSet, /// ScopeDefs that were used in current round round_scopedef_hits: FxHashSet, /// Amount of rounds since scopedef was first used. rounds_since_sopedef_hit: FxHashMap, /// Types queried but not present types_wishlist: FxHashSet, /// Threshold to squash trees to `Many` many_threshold: usize, } impl LookupTable { /// Initialize lookup table fn new(many_threshold: usize) -> Self { let mut res = Self { many_threshold, ..Default::default() }; res.new_types.insert(NewTypesKey::ImplMethod, Vec::new()); res.new_types.insert(NewTypesKey::StructProjection, Vec::new()); res } /// Find all `Expr`s that unify with the `ty` fn find(&self, db: &dyn HirDatabase, ty: &Type) -> Option> { self.data .iter() .find(|(t, _)| t.could_unify_with_deeply(db, ty)) .map(|(t, tts)| tts.exprs(t)) } /// Same as find but automatically creates shared reference of types in the lookup /// /// For example if we have type `i32` in data and we query for `&i32` it map all the type /// trees we have for `i32` with `Expr::Reference` and returns them. fn find_autoref(&self, db: &dyn HirDatabase, ty: &Type) -> Option> { self.data .iter() .find(|(t, _)| t.could_unify_with_deeply(db, ty)) .map(|(t, it)| it.exprs(t)) .or_else(|| { self.data .iter() .find(|(t, _)| { Type::reference(t, Mutability::Shared).could_unify_with_deeply(db, &ty) }) .map(|(t, it)| { it.exprs(t) .into_iter() .map(|expr| Expr::Reference(Box::new(expr))) .collect() }) }) } /// Insert new type trees for type /// /// Note that the types have to be the same, unification is not enough as unification is not /// transitive. For example Vec and FxHashSet both unify with Iterator, /// but they clearly do not unify themselves. fn insert(&mut self, ty: Type, exprs: impl Iterator) { match self.data.get_mut(&ty) { Some(it) => it.extend_with_threshold(self.many_threshold, exprs), None => { self.data.insert(ty.clone(), AlternativeExprs::new(self.many_threshold, exprs)); for it in self.new_types.values_mut() { it.push(ty.clone()); } } } } /// Iterate all the reachable types fn iter_types(&self) -> impl Iterator + '_ { self.data.keys().cloned() } /// Query new types reached since last query by key /// /// Create new key if you wish to query it to avoid conflicting with existing queries. fn new_types(&mut self, key: NewTypesKey) -> Vec { match self.new_types.get_mut(&key) { Some(it) => std::mem::take(it), None => Vec::new(), } } /// Mark `ScopeDef` as exhausted meaning it is not interesting for us any more fn mark_exhausted(&mut self, def: ScopeDef) { self.exhausted_scopedefs.insert(def); } /// Mark `ScopeDef` as used meaning we managed to produce something useful from it fn mark_fulfilled(&mut self, def: ScopeDef) { self.round_scopedef_hits.insert(def); } /// Start new round (meant to be called at the beginning of iteration in `term_search`) /// /// This functions marks some `ScopeDef`s as exhausted if there have been /// `MAX_ROUNDS_AFTER_HIT` rounds after first using a `ScopeDef`. fn new_round(&mut self) { for def in &self.round_scopedef_hits { let hits = self.rounds_since_sopedef_hit.entry(*def).and_modify(|n| *n += 1).or_insert(0); const MAX_ROUNDS_AFTER_HIT: u32 = 2; if *hits > MAX_ROUNDS_AFTER_HIT { self.exhausted_scopedefs.insert(*def); } } self.round_scopedef_hits.clear(); } /// Get exhausted `ScopeDef`s fn exhausted_scopedefs(&self) -> &FxHashSet { &self.exhausted_scopedefs } /// Types queried but not found fn take_types_wishlist(&mut self) -> FxHashSet { std::mem::take(&mut self.types_wishlist) } } /// Context for the `term_search` function #[derive(Debug)] pub struct TermSearchCtx<'a, DB: HirDatabase> { /// Semantics for the program pub sema: &'a Semantics<'a, DB>, /// Semantic scope, captures context for the term search pub scope: &'a SemanticsScope<'a>, /// Target / expected output type pub goal: Type, /// Configuration for term search pub config: TermSearchConfig, } /// Configuration options for the term search #[derive(Debug, Clone, Copy)] pub struct TermSearchConfig { /// Enable borrow checking, this guarantees the outputs of the `term_search` to borrow-check pub enable_borrowcheck: bool, /// Indicate when to squash multiple trees to `Many` as there are too many to keep track pub many_alternatives_threshold: usize, /// Depth of the search eg. number of cycles to run pub depth: usize, } impl Default for TermSearchConfig { fn default() -> Self { Self { enable_borrowcheck: true, many_alternatives_threshold: 1, depth: 6 } } } /// # Term search /// /// Search for terms (expressions) that unify with the `goal` type. /// /// # Arguments /// * `ctx` - Context for term search /// /// Internally this function uses Breadth First Search to find path to `goal` type. /// The general idea is following: /// 1. Populate lookup (frontier for BFS) from values (local variables, statics, constants, etc) /// as well as from well knows values (such as `true/false` and `()`) /// 2. Iteratively expand the frontier (or contents of the lookup) by trying different type /// transformation tactics. For example functions take as from set of types (arguments) to some /// type (return type). Other transformations include methods on type, type constructors and /// projections to struct fields (field access). /// 3. Once we manage to find path to type we are interested in we continue for single round to see /// if we can find more paths that take us to the `goal` type. /// 4. Return all the paths (type trees) that take us to the `goal` type. /// /// Note that there are usually more ways we can get to the `goal` type but some are discarded to /// reduce the memory consumption. It is also unlikely anyone is willing ti browse through /// thousands of possible responses so we currently take first 10 from every tactic. pub fn term_search(ctx: &TermSearchCtx<'_, DB>) -> Vec { let module = ctx.scope.module(); let mut defs = FxHashSet::default(); defs.insert(ScopeDef::ModuleDef(ModuleDef::Module(module))); ctx.scope.process_all_names(&mut |_, def| { defs.insert(def); }); let mut lookup = LookupTable::new(ctx.config.many_alternatives_threshold); // Try trivial tactic first, also populates lookup table let mut solutions: Vec = tactics::trivial(ctx, &defs, &mut lookup).collect(); // Use well known types tactic before iterations as it does not depend on other tactics solutions.extend(tactics::famous_types(ctx, &defs, &mut lookup)); for _ in 0..ctx.config.depth { lookup.new_round(); solutions.extend(tactics::type_constructor(ctx, &defs, &mut lookup)); solutions.extend(tactics::free_function(ctx, &defs, &mut lookup)); solutions.extend(tactics::impl_method(ctx, &defs, &mut lookup)); solutions.extend(tactics::struct_projection(ctx, &defs, &mut lookup)); solutions.extend(tactics::impl_static_method(ctx, &defs, &mut lookup)); // Discard not interesting `ScopeDef`s for speedup for def in lookup.exhausted_scopedefs() { defs.remove(def); } } solutions.into_iter().filter(|it| !it.is_many()).unique().collect() }