// 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. | |

/// 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. | |

import 'package:benchmark_harness/benchmark_harness.dart'; | |

/// 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. | |

main() { | |

const DeltaBlue().report(); | |

} | |

/// Benchmark class required to report results. | |

class DeltaBlue extends BenchmarkBase { | |

const DeltaBlue() : super("DeltaBlue"); | |

void run() { | |

chainTest(100); | |

projectionTest(100); | |

} | |

} | |

/// 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 { | |

final int value; | |

final String name; | |

const Strength(this.value, this.name); | |

Strength nextWeaker() => const <Strength>[ | |

WEAKEST, | |

WEAK_DEFAULT, | |

NORMAL, | |

STRONG_DEFAULT, | |

PREFERRED, | |

STRONG_REFERRED | |

][value]; | |

static bool stronger(Strength s1, Strength s2) { | |

return s1.value < s2.value; | |

} | |

static bool weaker(Strength s1, Strength s2) { | |

return s1.value > s2.value; | |

} | |

static Strength weakest(Strength s1, Strength s2) { | |

return weaker(s1, s2) ? s1 : s2; | |

} | |

static Strength strongest(Strength s1, Strength s2) { | |

return stronger(s1, s2) ? s1 : s2; | |

} | |

} | |

// Compile time computed constants. | |

const REQUIRED = Strength(0, "required"); | |

const STRONG_REFERRED = Strength(1, "strongPreferred"); | |

const PREFERRED = Strength(2, "preferred"); | |

const STRONG_DEFAULT = Strength(3, "strongDefault"); | |

const NORMAL = Strength(4, "normal"); | |

const WEAK_DEFAULT = Strength(5, "weakDefault"); | |

const WEAKEST = Strength(6, "weakest"); | |

abstract class Constraint { | |

final Strength strength; | |

const Constraint(this.strength); | |

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) { | |

print("Could not satisfy a required constraint!"); | |

} | |

return null; | |

} | |

markInputs(mark); | |

Variable out = output(); | |

Constraint overridden = out.determinedBy; | |

if (overridden != null) overridden.markUnsatisfied(); | |

out.determinedBy = this; | |

if (!planner.addPropagate(this, mark)) print("Cycle encountered"); | |

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 | |

/// keybord, a clock, or some arbitraty 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(this.myOutput, Strength strength) : super(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. | |

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(Variable v, Strength str) : super(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(Variable v, Strength str) : super(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(this.v1, this.v2, Strength strength) : super(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. | |

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( | |

Variable src, this.scale, this.offset, Variable dest, Strength strength) | |

: super(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(Variable v1, Variable v2, Strength strength) | |

: super(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 { | |

List<Constraint> constraints = <Constraint>[]; | |

Constraint determinedBy; | |

int mark = 0; | |

Strength walkStrength = WEAKEST; | |

bool stay = true; | |

int value; | |

final String name; | |

Variable(this.name, 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.removeWhere((e) => c == e); | |

if (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 satifying | |

/// 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)) { | |

// NOOP | |

} | |

} | |

/// 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(); | |

List<Constraint> unsatisfied = removePropagateFrom(out); | |

Strength strength = REQUIRED; | |

do { | |

for (int i = 0; i < unsatisfied.length; i++) { | |

Constraint u = unsatisfied[i]; | |

if (u.strength == strength) incrementalAdd(u); | |

} | |

strength = strength.nextWeaker(); | |

} 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(List<Constraint> sources) { | |

int mark = newMark(); | |

Plan plan = Plan(); | |

List<Constraint> todo = sources; | |

while (todo.isNotEmpty) { | |

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(List<Constraint> constraints) { | |

List<Constraint> sources = <Constraint>[]; | |

for (int i = 0; i < constraints.length; i++) { | |

Constraint c = constraints[i]; | |

// 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) { | |

List<Constraint> todo = <Constraint>[c]; | |

while (todo.isNotEmpty) { | |

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. | |

List<Constraint> removePropagateFrom(Variable out) { | |

out.determinedBy = null; | |

out.walkStrength = WEAKEST; | |

out.stay = true; | |

List<Constraint> unsatisfied = <Constraint>[]; | |

List<Variable> todo = <Variable>[out]; | |

while (todo.isNotEmpty) { | |

Variable v = todo.removeLast(); | |

for (int i = 0; i < v.constraints.length; i++) { | |

Constraint c = v.constraints[i]; | |

if (!c.isSatisfied()) unsatisfied.add(c); | |

} | |

Constraint determining = v.determinedBy; | |

for (int i = 0; i < v.constraints.length; i++) { | |

Constraint next = v.constraints[i]; | |

if (next != determining && next.isSatisfied()) { | |

next.recalculate(); | |

todo.add(next.output()); | |

} | |

} | |

} | |

return unsatisfied; | |

} | |

void addConstraintsConsumingTo(Variable v, List<Constraint> coll) { | |

Constraint determining = v.determinedBy; | |

for (int i = 0; i < v.constraints.length; i++) { | |

Constraint c = v.constraints[i]; | |

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 { | |

List<Constraint> list = <Constraint>[]; | |

void addConstraint(Constraint c) { | |

list.add(c); | |

} | |

int size() => list.length; | |

void execute() { | |

for (int i = 0; i < list.length; i++) { | |

list[i].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 accomodated. The cost in this case is, | |

/// of course, very low. Typical situations lie somewhere between these | |

/// two extremes. | |

void chainTest(int n) { | |

planner = Planner(); | |

Variable prev, first, last; | |

// Build chain of n equality constraints. | |

for (int i = 0; i <= n; i++) { | |

Variable v = Variable("v", 0); | |

if (prev != null) EqualityConstraint(prev, v, REQUIRED); | |

if (i == 0) first = v; | |

if (i == n) last = v; | |

prev = v; | |

} | |

StayConstraint(last, STRONG_DEFAULT); | |

EditConstraint edit = EditConstraint(first, PREFERRED); | |

Plan plan = planner.extractPlanFromConstraints(<Constraint>[edit]); | |

for (int i = 0; i < 100; i++) { | |

first.value = i; | |

plan.execute(); | |

if (last.value != i) { | |

print("Chain test failed.\n{last.value)\n{i}"); | |

} | |

} | |

} | |

/// 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(); | |

Variable scale = Variable("scale", 10); | |

Variable offset = Variable("offset", 1000); | |

Variable src, dst; | |

List<Variable> dests = <Variable>[]; | |

for (int i = 0; i < n; i++) { | |

src = Variable("src", i); | |

dst = Variable("dst", i); | |

dests.add(dst); | |

StayConstraint(src, NORMAL); | |

ScaleConstraint(src, scale, offset, dst, REQUIRED); | |

} | |

change(src, 17); | |

if (dst.value != 1170) print("Projection 1 failed"); | |

change(dst, 1050); | |

if (src.value != 5) print("Projection 2 failed"); | |

change(scale, 5); | |

for (int i = 0; i < n - 1; i++) { | |

if (dests[i].value != i * 5 + 1000) print("Projection 3 failed"); | |

} | |

change(offset, 2000); | |

for (int i = 0; i < n - 1; i++) { | |

if (dests[i].value != i * 5 + 2000) print("Projection 4 failed"); | |

} | |

} | |

void change(Variable v, int newValue) { | |

EditConstraint edit = EditConstraint(v, PREFERRED); | |

Plan plan = planner.extractPlanFromConstraints(<EditConstraint>[edit]); | |

for (int i = 0; i < 10; i++) { | |

v.value = newValue; | |

plan.execute(); | |

} | |

edit.destroyConstraint(); | |

} | |

Planner planner; |