| // Copyright 2011 Google Inc. All Rights Reserved. |
| // Copyright 1996 John Maloney and Mario Wolczko |
| // |
| // This file is part of GNU Smalltalk. |
| // |
| // GNU Smalltalk is free software; you can redistribute it and/or modify it |
| // under the terms of the GNU General Public License as published by the Free |
| // Software Foundation; either version 2, or (at your option) any later version. |
| // |
| // GNU Smalltalk is distributed in the hope that it will be useful, but WITHOUT |
| // ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS |
| // FOR A PARTICULAR PURPOSE. See the GNU General Public License for more |
| // details. |
| // |
| // You should have received a copy of the GNU General Public License along with |
| // GNU Smalltalk; see the file COPYING. If not, write to the Free Software |
| // Foundation, 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. |
| // |
| // Translated first from Smalltalk to JavaScript, and finally to |
| // Dart by Google 2008-2010. |
| |
| // This version is further simplified to only use language constructs supported |
| // by the Dart-to-Wasm prototype in 2020. |
| |
| /** |
| * A Dart implementation of the DeltaBlue constraint-solving |
| * algorithm, as described in: |
| * |
| * "The DeltaBlue Algorithm: An Incremental Constraint Hierarchy Solver" |
| * Bjorn N. Freeman-Benson and John Maloney |
| * January 1990 Communications of the ACM, |
| * also available as University of Washington TR 89-08-06. |
| * |
| * Beware: this benchmark is written in a grotesque style where |
| * the constraint model is built by side-effects from constructors. |
| * I've kept it this way to avoid deviating too much from the original |
| * implementation. |
| */ |
| |
| void main() { |
| new DeltaBlue().run(); |
| } |
| |
| /// Benchmark class required to report results. |
| class DeltaBlue { |
| void run() { |
| chainTest(100000); |
| projectionTest(100000); |
| } |
| } |
| |
| /** |
| * Strengths are used to measure the relative importance of constraints. |
| * New strengths may be inserted in the strength hierarchy without |
| * disrupting current constraints. Strengths cannot be created outside |
| * this class, so == can be used for value comparison. |
| */ |
| class Strength { |
| static int nextWeaker(int s) => s + 1; |
| |
| static bool stronger(int s1, int s2) { |
| return s1 < s2; |
| } |
| |
| static bool weaker(int s1, int s2) { |
| return s1 > s2; |
| } |
| |
| static int weakest(int s1, int s2) { |
| return weaker(s1, s2) ? s1 : s2; |
| } |
| |
| static int strongest(int s1, int s2) { |
| return stronger(s1, s2) ? s1 : s2; |
| } |
| } |
| |
| // Compile time computed constants. |
| const REQUIRED = 0; |
| const STRONG_PREFERRED = 1; |
| const PREFERRED = 2; |
| const STRONG_DEFAULT = 3; |
| const NORMAL = 4; |
| const WEAK_DEFAULT = 5; |
| const WEAKEST = 6; |
| |
| abstract class Constraint { |
| final Planner planner; |
| final int strength; |
| |
| Constraint(this.planner, this.strength); |
| |
| @pragma("vm:never-inline") |
| bool isSatisfied(); |
| void markUnsatisfied(); |
| void addToGraph(); |
| void removeFromGraph(); |
| void chooseMethod(int mark); |
| void markInputs(int mark); |
| bool inputsKnown(int mark); |
| Variable output(); |
| void execute(); |
| void recalculate(); |
| |
| /// Activate this constraint and attempt to satisfy it. |
| void addConstraint() { |
| addToGraph(); |
| planner.incrementalAdd(this); |
| } |
| |
| /** |
| * Attempt to find a way to enforce this constraint. If successful, |
| * record the solution, perhaps modifying the current dataflow |
| * graph. Answer the constraint that this constraint overrides, if |
| * there is one, or nil, if there isn't. |
| * Assume: I am not already satisfied. |
| */ |
| Constraint satisfy(int mark) { |
| chooseMethod(mark); |
| if (!isSatisfied()) { |
| if (strength == REQUIRED) { |
| errorRequiredConstraint(); |
| } |
| return null; |
| } |
| markInputs(mark); |
| Variable out = output(); |
| Constraint overridden = out.determinedBy; |
| if (overridden != null) overridden.markUnsatisfied(); |
| out.determinedBy = this; |
| if (!planner.addPropagate(this, mark)) errorCycleEncountered(); |
| out.mark = mark; |
| return overridden; |
| } |
| |
| void destroyConstraint() { |
| if (isSatisfied()) planner.incrementalRemove(this); |
| removeFromGraph(); |
| } |
| |
| /** |
| * Normal constraints are not input constraints. An input constraint |
| * is one that depends on external state, such as the mouse, the |
| * keyboard, a clock, or some arbitrary piece of imperative code. |
| */ |
| bool isInput() => false; |
| } |
| |
| /** |
| * Abstract superclass for constraints having a single possible output variable. |
| */ |
| abstract class UnaryConstraint extends Constraint { |
| final Variable myOutput; |
| bool satisfied = false; |
| |
| UnaryConstraint(Planner planner, this.myOutput, int strength) |
| : super(planner, strength) { |
| addConstraint(); |
| } |
| |
| /// Adds this constraint to the constraint graph |
| void addToGraph() { |
| myOutput.addConstraint(this); |
| satisfied = false; |
| } |
| |
| /// Decides if this constraint can be satisfied and records that decision. |
| void chooseMethod(int mark) { |
| satisfied = (myOutput.mark != mark) && |
| Strength.stronger(strength, myOutput.walkStrength); |
| } |
| |
| /// Returns true if this constraint is satisfied in the current solution. |
| @pragma("vm:never-inline") |
| bool isSatisfied() => satisfied; |
| |
| void markInputs(int mark) { |
| // has no inputs. |
| } |
| |
| /// Returns the current output variable. |
| Variable output() => myOutput; |
| |
| /** |
| * Calculate the walkabout strength, the stay flag, and, if it is |
| * 'stay', the value for the current output of this constraint. Assume |
| * this constraint is satisfied. |
| */ |
| void recalculate() { |
| myOutput.walkStrength = strength; |
| myOutput.stay = !isInput(); |
| if (myOutput.stay) execute(); // Stay optimization. |
| } |
| |
| /// Records that this constraint is unsatisfied. |
| void markUnsatisfied() { |
| satisfied = false; |
| } |
| |
| bool inputsKnown(int mark) => true; |
| |
| void removeFromGraph() { |
| if (myOutput != null) myOutput.removeConstraint(this); |
| satisfied = false; |
| } |
| } |
| |
| /** |
| * Variables that should, with some level of preference, stay the same. |
| * Planners may exploit the fact that instances, if satisfied, will not |
| * change their output during plan execution. This is called "stay |
| * optimization". |
| */ |
| class StayConstraint extends UnaryConstraint { |
| StayConstraint(Planner planner, Variable v, int str) : super(planner, v, str); |
| |
| void execute() { |
| // Stay constraints do nothing. |
| } |
| } |
| |
| /** |
| * A unary input constraint used to mark a variable that the client |
| * wishes to change. |
| */ |
| class EditConstraint extends UnaryConstraint { |
| EditConstraint(Planner planner, Variable v, int str) : super(planner, v, str); |
| |
| /// Edits indicate that a variable is to be changed by imperative code. |
| bool isInput() => true; |
| |
| void execute() { |
| // Edit constraints do nothing. |
| } |
| } |
| |
| // Directions. |
| const int NONE = 1; |
| const int FORWARD = 2; |
| const int BACKWARD = 0; |
| |
| /** |
| * Abstract superclass for constraints having two possible output |
| * variables. |
| */ |
| abstract class BinaryConstraint extends Constraint { |
| Variable v1; |
| Variable v2; |
| int direction = NONE; |
| |
| BinaryConstraint(Planner planner, this.v1, this.v2, int strength) |
| : super(planner, strength) { |
| addConstraint(); |
| } |
| |
| /** |
| * Decides if this constraint can be satisfied and which way it |
| * should flow based on the relative strength of the variables related, |
| * and record that decision. |
| */ |
| void chooseMethod(int mark) { |
| if (v1.mark == mark) { |
| direction = |
| (v2.mark != mark && Strength.stronger(strength, v2.walkStrength)) |
| ? FORWARD |
| : NONE; |
| } |
| if (v2.mark == mark) { |
| direction = |
| (v1.mark != mark && Strength.stronger(strength, v1.walkStrength)) |
| ? BACKWARD |
| : NONE; |
| } |
| if (Strength.weaker(v1.walkStrength, v2.walkStrength)) { |
| direction = |
| Strength.stronger(strength, v1.walkStrength) ? BACKWARD : NONE; |
| } else { |
| direction = |
| Strength.stronger(strength, v2.walkStrength) ? FORWARD : BACKWARD; |
| } |
| } |
| |
| /// Add this constraint to the constraint graph. |
| void addToGraph() { |
| v1.addConstraint(this); |
| v2.addConstraint(this); |
| direction = NONE; |
| } |
| |
| /// Answer true if this constraint is satisfied in the current solution. |
| @pragma("vm:never-inline") |
| bool isSatisfied() => direction != NONE; |
| |
| /// Mark the input variable with the given mark. |
| void markInputs(int mark) { |
| input().mark = mark; |
| } |
| |
| /// Returns the current input variable |
| Variable input() => direction == FORWARD ? v1 : v2; |
| |
| /// Returns the current output variable. |
| Variable output() => direction == FORWARD ? v2 : v1; |
| |
| /** |
| * Calculate the walkabout strength, the stay flag, and, if it is |
| * 'stay', the value for the current output of this |
| * constraint. Assume this constraint is satisfied. |
| */ |
| void recalculate() { |
| Variable ihn = input(), out = output(); |
| out.walkStrength = Strength.weakest(strength, ihn.walkStrength); |
| out.stay = ihn.stay; |
| if (out.stay) execute(); |
| } |
| |
| /// Record the fact that this constraint is unsatisfied. |
| void markUnsatisfied() { |
| direction = NONE; |
| } |
| |
| bool inputsKnown(int mark) { |
| Variable i = input(); |
| return i.mark == mark || i.stay || i.determinedBy == null; |
| } |
| |
| void removeFromGraph() { |
| if (v1 != null) v1.removeConstraint(this); |
| if (v2 != null) v2.removeConstraint(this); |
| direction = NONE; |
| } |
| } |
| |
| /** |
| * Relates two variables by the linear scaling relationship: "v2 = |
| * (v1 * scale) + offset". Either v1 or v2 may be changed to maintain |
| * this relationship but the scale factor and offset are considered |
| * read-only. |
| */ |
| |
| class ScaleConstraint extends BinaryConstraint { |
| final Variable scale; |
| final Variable offset; |
| |
| ScaleConstraint(Planner planner, Variable src, this.scale, this.offset, |
| Variable dest, int strength) |
| : super(planner, src, dest, strength); |
| |
| /// Adds this constraint to the constraint graph. |
| void addToGraph() { |
| super.addToGraph(); |
| scale.addConstraint(this); |
| offset.addConstraint(this); |
| } |
| |
| void removeFromGraph() { |
| super.removeFromGraph(); |
| if (scale != null) scale.removeConstraint(this); |
| if (offset != null) offset.removeConstraint(this); |
| } |
| |
| void markInputs(int mark) { |
| super.markInputs(mark); |
| scale.mark = offset.mark = mark; |
| } |
| |
| /// Enforce this constraint. Assume that it is satisfied. |
| void execute() { |
| if (direction == FORWARD) { |
| v2.value = v1.value * scale.value + offset.value; |
| } else { |
| v1.value = (v2.value - offset.value) ~/ scale.value; |
| } |
| } |
| |
| /** |
| * Calculate the walkabout strength, the stay flag, and, if it is |
| * 'stay', the value for the current output of this constraint. Assume |
| * this constraint is satisfied. |
| */ |
| void recalculate() { |
| Variable ihn = input(), out = output(); |
| out.walkStrength = Strength.weakest(strength, ihn.walkStrength); |
| out.stay = ihn.stay && scale.stay && offset.stay; |
| if (out.stay) execute(); |
| } |
| } |
| |
| /** |
| * Constrains two variables to have the same value. |
| */ |
| class EqualityConstraint extends BinaryConstraint { |
| EqualityConstraint(Planner planner, Variable v1, Variable v2, int strength) |
| : super(planner, v1, v2, strength); |
| |
| /// Enforce this constraint. Assume that it is satisfied. |
| void execute() { |
| output().value = input().value; |
| } |
| } |
| |
| /** |
| * A constrained variable. In addition to its value, it maintain the |
| * structure of the constraint graph, the current dataflow graph, and |
| * various parameters of interest to the DeltaBlue incremental |
| * constraint solver. |
| **/ |
| class Variable { |
| ConstraintList constraints = new ConstraintList(); |
| Constraint determinedBy; |
| int mark = 0; |
| int walkStrength = WEAKEST; |
| bool stay = true; |
| int value; |
| |
| Variable(this.value); |
| |
| /** |
| * Add the given constraint to the set of all constraints that refer |
| * this variable. |
| */ |
| void addConstraint(Constraint c) { |
| constraints.add(c); |
| } |
| |
| /// Removes all traces of c from this variable. |
| void removeConstraint(Constraint c) { |
| constraints.remove(c); |
| if (identical(determinedBy, c)) determinedBy = null; |
| } |
| } |
| |
| class Planner { |
| int currentMark = 0; |
| |
| /** |
| * Attempt to satisfy the given constraint and, if successful, |
| * incrementally update the dataflow graph. Details: If satisfying |
| * the constraint is successful, it may override a weaker constraint |
| * on its output. The algorithm attempts to resatisfy that |
| * constraint using some other method. This process is repeated |
| * until either a) it reaches a variable that was not previously |
| * determined by any constraint or b) it reaches a constraint that |
| * is too weak to be satisfied using any of its methods. The |
| * variables of constraints that have been processed are marked with |
| * a unique mark value so that we know where we've been. This allows |
| * the algorithm to avoid getting into an infinite loop even if the |
| * constraint graph has an inadvertent cycle. |
| */ |
| void incrementalAdd(Constraint c) { |
| int mark = newMark(); |
| for (Constraint overridden = c.satisfy(mark); |
| overridden != null; |
| overridden = overridden.satisfy(mark)); |
| } |
| |
| /** |
| * Entry point for retracting a constraint. Remove the given |
| * constraint and incrementally update the dataflow graph. |
| * Details: Retracting the given constraint may allow some currently |
| * unsatisfiable downstream constraint to be satisfied. We therefore collect |
| * a list of unsatisfied downstream constraints and attempt to |
| * satisfy each one in turn. This list is traversed by constraint |
| * strength, strongest first, as a heuristic for avoiding |
| * unnecessarily adding and then overriding weak constraints. |
| * Assume: [c] is satisfied. |
| */ |
| void incrementalRemove(Constraint c) { |
| Variable out = c.output(); |
| c.markUnsatisfied(); |
| c.removeFromGraph(); |
| ConstraintList unsatisfied = removePropagateFrom(out); |
| int strength = REQUIRED; |
| do { |
| for (var it = unsatisfied.iterator; !it.done; it.advance()) { |
| Constraint u = it.current; |
| if (u.strength == strength) incrementalAdd(u); |
| } |
| strength = Strength.nextWeaker(strength); |
| } while (strength != WEAKEST); |
| } |
| |
| /// Select a previously unused mark value. |
| int newMark() => ++currentMark; |
| |
| /** |
| * Extract a plan for resatisfaction starting from the given source |
| * constraints, usually a set of input constraints. This method |
| * assumes that stay optimization is desired; the plan will contain |
| * only constraints whose output variables are not stay. Constraints |
| * that do no computation, such as stay and edit constraints, are |
| * not included in the plan. |
| * Details: The outputs of a constraint are marked when it is added |
| * to the plan under construction. A constraint may be appended to |
| * the plan when all its input variables are known. A variable is |
| * known if either a) the variable is marked (indicating that has |
| * been computed by a constraint appearing earlier in the plan), b) |
| * the variable is 'stay' (i.e. it is a constant at plan execution |
| * time), or c) the variable is not determined by any |
| * constraint. The last provision is for past states of history |
| * variables, which are not stay but which are also not computed by |
| * any constraint. |
| * Assume: [sources] are all satisfied. |
| */ |
| Plan makePlan(ConstraintList sources) { |
| int mark = newMark(); |
| Plan plan = new Plan(); |
| ConstraintList todo = sources; |
| while (!todo.isEmpty) { |
| Constraint c = todo.removeLast(); |
| if (c.output().mark != mark && c.inputsKnown(mark)) { |
| plan.addConstraint(c); |
| c.output().mark = mark; |
| addConstraintsConsumingTo(c.output(), todo); |
| } |
| } |
| return plan; |
| } |
| |
| /** |
| * Extract a plan for resatisfying starting from the output of the |
| * given [constraints], usually a set of input constraints. |
| */ |
| Plan extractPlanFromConstraints(ConstraintList constraints) { |
| ConstraintList sources = new ConstraintList(); |
| for (var it = constraints.iterator; !it.done; it.advance()) { |
| Constraint c = it.current; |
| // if not in plan already and eligible for inclusion. |
| if (c.isInput() && c.isSatisfied()) sources.add(c); |
| } |
| return makePlan(sources); |
| } |
| |
| /** |
| * Recompute the walkabout strengths and stay flags of all variables |
| * downstream of the given constraint and recompute the actual |
| * values of all variables whose stay flag is true. If a cycle is |
| * detected, remove the given constraint and answer |
| * false. Otherwise, answer true. |
| * Details: Cycles are detected when a marked variable is |
| * encountered downstream of the given constraint. The sender is |
| * assumed to have marked the inputs of the given constraint with |
| * the given mark. Thus, encountering a marked node downstream of |
| * the output constraint means that there is a path from the |
| * constraint's output to one of its inputs. |
| */ |
| bool addPropagate(Constraint c, int mark) { |
| ConstraintList todo = new ConstraintList()..add(c); |
| while (!todo.isEmpty) { |
| Constraint d = todo.removeLast(); |
| if (d.output().mark == mark) { |
| incrementalRemove(c); |
| return false; |
| } |
| d.recalculate(); |
| addConstraintsConsumingTo(d.output(), todo); |
| } |
| return true; |
| } |
| |
| /** |
| * Update the walkabout strengths and stay flags of all variables |
| * downstream of the given constraint. Answer a collection of |
| * unsatisfied constraints sorted in order of decreasing strength. |
| */ |
| ConstraintList removePropagateFrom(Variable out) { |
| out.determinedBy = null; |
| out.walkStrength = WEAKEST; |
| out.stay = true; |
| ConstraintList unsatisfied = new ConstraintList(); |
| VariableStack todo = new VariableStack()..push(out); |
| while (!todo.isEmpty) { |
| Variable v = todo.pop(); |
| for (var it = v.constraints.iterator; !it.done; it.advance()) { |
| Constraint c = it.current; |
| if (!c.isSatisfied()) unsatisfied.add(c); |
| } |
| Constraint determining = v.determinedBy; |
| for (var it = v.constraints.iterator; !it.done; it.advance()) { |
| Constraint next = it.current; |
| if (next != determining && next.isSatisfied()) { |
| next.recalculate(); |
| todo.push(next.output()); |
| } |
| } |
| } |
| return unsatisfied; |
| } |
| |
| void addConstraintsConsumingTo(Variable v, ConstraintList coll) { |
| Constraint determining = v.determinedBy; |
| for (var it = v.constraints.iterator; !it.done; it.advance()) { |
| Constraint c = it.current; |
| if (c != determining && c.isSatisfied()) coll.add(c); |
| } |
| } |
| } |
| |
| /** |
| * A Plan is an ordered list of constraints to be executed in sequence |
| * to resatisfy all currently satisfiable constraints in the face of |
| * one or more changing inputs. |
| */ |
| class Plan { |
| ConstraintList list = new ConstraintList(); |
| |
| void addConstraint(Constraint c) { |
| list.add(c); |
| } |
| |
| void execute() { |
| for (var it = list.iterator; !it.done; it.advance()) { |
| it.current.execute(); |
| } |
| } |
| } |
| |
| /** |
| * This is the standard DeltaBlue benchmark. A long chain of equality |
| * constraints is constructed with a stay constraint on one end. An |
| * edit constraint is then added to the opposite end and the time is |
| * measured for adding and removing this constraint, and extracting |
| * and executing a constraint satisfaction plan. There are two cases. |
| * In case 1, the added constraint is stronger than the stay |
| * constraint and values must propagate down the entire length of the |
| * chain. In case 2, the added constraint is weaker than the stay |
| * constraint so it cannot be accommodated. The cost in this case is, |
| * of course, very low. Typical situations lie somewhere between these |
| * two extremes. |
| */ |
| void chainTest(int n) { |
| Planner planner = new Planner(); |
| Variable prev = null, first = null, last = null; |
| // Build chain of n equality constraints. |
| for (int i = 0; i <= n; i++) { |
| Variable v = new Variable(0); |
| if (prev != null) new EqualityConstraint(planner, prev, v, REQUIRED); |
| if (i == 0) first = v; |
| if (i == n) last = v; |
| prev = v; |
| } |
| new StayConstraint(planner, last, STRONG_DEFAULT); |
| EditConstraint edit = new EditConstraint(planner, first, PREFERRED); |
| Plan plan = |
| planner.extractPlanFromConstraints(new ConstraintList()..add(edit)); |
| for (int i = 0; i < 100; i++) { |
| first.value = i; |
| plan.execute(); |
| if (last.value != i) { |
| errorChainTestFailed(i, last.value); |
| } |
| } |
| log(last.value); |
| } |
| |
| /** |
| * This test constructs a two sets of variables related to each |
| * other by a simple linear transformation (scale and offset). The |
| * time is measured to change a variable on either side of the |
| * mapping and to change the scale and offset factors. |
| */ |
| void projectionTest(int n) { |
| Planner planner = new Planner(); |
| Variable scale = new Variable(10); |
| Variable offset = new Variable(1000); |
| Variable src = null, dst = null; |
| |
| VariableStack dests = new VariableStack(); |
| for (int i = 0; i < n; i++) { |
| src = new Variable(i); |
| dst = new Variable(i); |
| dests.push(dst); |
| new StayConstraint(planner, src, NORMAL); |
| new ScaleConstraint(planner, src, scale, offset, dst, REQUIRED); |
| } |
| change(planner, src, 17); |
| log(dst.value); |
| if (dst.value != 1170) errorProjectionFailed(1); |
| change(planner, dst, 1050); |
| log(src.value); |
| if (src.value != 5) errorProjectionFailed(2); |
| change(planner, scale, 5); |
| int expected = (n - 2) * 5 + 1000; |
| for (var vars = dests.clone()..pop(); !vars.isEmpty;) { |
| if (vars.pop().value != expected) errorProjectionFailed(3); |
| expected -= 5; |
| } |
| log(expected); |
| change(planner, offset, 2000); |
| expected = (n - 2) * 5 + 2000; |
| for (var vars = dests.clone()..pop(); !vars.isEmpty;) { |
| if (vars.pop().value != expected) errorProjectionFailed(4); |
| expected -= 5; |
| } |
| log(expected); |
| } |
| |
| void change(Planner planner, Variable v, int newValue) { |
| EditConstraint edit = new EditConstraint(planner, v, PREFERRED); |
| Plan plan = |
| planner.extractPlanFromConstraints(new ConstraintList()..add(edit)); |
| for (int i = 0; i < 10; i++) { |
| v.value = newValue; |
| plan.execute(); |
| } |
| edit.destroyConstraint(); |
| } |
| |
| // The classes below are the added replacements for the Dart built-in lists: |
| |
| class VariableStack { |
| VariableStackElement top; |
| |
| void push(Variable variable) { |
| top = new VariableStackElement(variable, top); |
| } |
| |
| Variable pop() { |
| Variable topVar = top.variable; |
| top = top.next; |
| return topVar; |
| } |
| |
| bool get isEmpty => top == null; |
| |
| VariableStack clone() => new VariableStack()..top = top; |
| } |
| |
| class VariableStackElement { |
| final Variable variable; |
| final VariableStackElement next; |
| |
| VariableStackElement(this.variable, this.next); |
| } |
| |
| class ConstraintList { |
| ConstraintListElement dummy; |
| |
| ConstraintList() { |
| dummy = new ConstraintListElement(null); |
| dummy.next = dummy; |
| dummy.prev = dummy; |
| } |
| |
| bool get isEmpty => identical(dummy.next, dummy); |
| |
| void add(Constraint constraint) { |
| ConstraintListElement element = new ConstraintListElement(constraint); |
| element.prev = dummy.prev; |
| element.next = dummy; |
| dummy.prev.next = element; |
| dummy.prev = element; |
| } |
| |
| Constraint removeLast() { |
| assert(!isEmpty); |
| ConstraintListElement last = dummy.prev; |
| last.remove(); |
| return last.value; |
| } |
| |
| void remove(Constraint constraint) { |
| for (var elem = dummy.next; elem != dummy; elem = elem.next) { |
| if (identical(elem.value, constraint)) { |
| elem.remove(); |
| return; |
| } |
| } |
| } |
| |
| ConstraintListIterator get iterator => new ConstraintListIterator(this); |
| } |
| |
| class ConstraintListElement { |
| final Constraint value; |
| ConstraintListElement next; |
| ConstraintListElement prev; |
| |
| ConstraintListElement(this.value); |
| |
| void remove() { |
| prev.next = next; |
| next.prev = prev; |
| } |
| } |
| |
| class ConstraintListIterator { |
| ConstraintListElement currentElement; |
| |
| ConstraintListIterator(ConstraintList list) |
| : currentElement = list.dummy.next; |
| |
| Constraint get current => currentElement.value; |
| |
| bool get done => currentElement.value == null; |
| |
| void advance() => currentElement = currentElement.next; |
| } |
| |
| // This function is called a few times during successful execution to output |
| // some numbers. The values can then be checked to verify the execution. |
| |
| void log(int x) { |
| print(x); |
| } |
| |
| // If an error occurs, one of the following functions is called instead of the |
| // usual printing. These should be implemented to signal the error in an |
| // appropriate way. |
| |
| void errorRequiredConstraint() { |
| // Could not satisfy a required constraint! |
| print(-1); |
| } |
| |
| void errorCycleEncountered() { |
| // Cycle encountered. |
| print(-2); |
| } |
| |
| void errorChainTestFailed(int a, int b) { |
| // Chain test failed: |
| // Expected last value to be $a but it was $b. |
| print(-3); |
| print(a); |
| print(b); |
| } |
| |
| void errorProjectionFailed(int n) { |
| // Projection $n failed. |
| print(-4); |
| print(n); |
| } |