org.jetbrains.kotlin.resolve.calls.inference.NewConstraintSystem.kt Maven / Gradle / Ivy

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/*
 * Copyright 2010-2020 JetBrains s.r.o. and Kotlin Programming Language contributors.
 * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
 */

package org.jetbrains.kotlin.resolve.calls.inference

import org.jetbrains.kotlin.resolve.calls.components.PostponedArgumentsAnalyzerContext
import org.jetbrains.kotlin.resolve.calls.inference.components.ConstraintSystemCompletionContext
import org.jetbrains.kotlin.resolve.calls.inference.model.Constraint
import org.jetbrains.kotlin.resolve.calls.inference.model.ConstraintStorage
import org.jetbrains.kotlin.resolve.calls.inference.model.ConstraintSystemError
import org.jetbrains.kotlin.resolve.checkers.EmptyIntersectionTypeInfo
import org.jetbrains.kotlin.types.model.KotlinTypeMarker
import org.jetbrains.kotlin.types.model.TypeVariableMarker

interface NewConstraintSystem {
    val hasContradiction: Boolean
    val errors: List

    fun getBuilder(): ConstraintSystemBuilder

    // after this method we shouldn't mutate system via ConstraintSystemBuilder
    fun asReadOnlyStorage(): ConstraintStorage

    fun asConstraintSystemCompleterContext(): ConstraintSystemCompletionContext
    fun asPostponedArgumentsAnalyzerContext(): PostponedArgumentsAnalyzerContext
    fun resolveForkPointsConstraints()

    fun getEmptyIntersectionTypeKind(types: Collection): EmptyIntersectionTypeInfo?
}

/**
 * In some cases we're not only adding constraints linearly to the system, but sometimes we need to consider several variants of constraints
 *
 * For example, from smartcast we've got a value of a type A & A that we'd like to pass as an argument to the parameter
 * of type A (where Xv and Yv are the type variables of the current call)
 *
 * So, we've got a subtyping constraint
 * A & A <: A
 *
 * And we might go with the first intersection component, having the following variables constraint set: {Xv=Int,Yv=String}
 * Or, if we'd consider the second component it would be {Xv=E, Yv=F}
 *
 * And all existing and future constraints might work differently depending on which option we've chosen.
 * Thus, ideally we need to create two versions of the constraint system and try to resolve each of them.
 * But that lead to exponential complexity, so we only use some set of heuristics for that
 *
 * Lately, we call such situation a "fork point" and each of the options a "fork point branch"
 * Each branch is defined by the set of constraints that need to be added to the system if we choose the particular branch.
 */
typealias ForkPointData = List
typealias ForkPointBranchDescription = Set>