Move kernel baseline tests to front_end.

pkg/kernel/testcases/input/DeltaBlue.dart

Index: pkg/kernel/testcases/input/DeltaBlue.dart
diff --git a/pkg/kernel/testcases/input/DeltaBlue.dart b/pkg/kernel/testcases/input/DeltaBlue.dart
deleted file mode 100644
index 1b58f52f5e18b55881b197b0d7aa89e6fe51285c..0000000000000000000000000000000000000000
--- a/pkg/kernel/testcases/input/DeltaBlue.dart
+++ /dev/null
@@ -1,705 +0,0 @@
-// 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.
- */
-
-main() {
-  new DeltaBlue().run();
-}
-
-/// Benchmark class required to report results.
-class 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>[
-        STRONG_PREFERRED,
-        PREFERRED,
-        STRONG_DEFAULT,
-        NORMAL,
-        WEAK_DEFAULT,
-        WEAKEST
-      ][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 = const Strength(0, "required");
-const STRONG_PREFERRED = const Strength(1, "strongPreferred");
-const PREFERRED = const Strength(2, "preferred");
-const STRONG_DEFAULT = const Strength(3, "strongDefault");
-const NORMAL = const Strength(4, "normal");
-const WEAK_DEFAULT = const Strength(5, "weakDefault");
-const WEAKEST = const 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(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.remove(c);
-    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));
-  }
-
-  /**
-   * 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 = new Plan();
-    List<Constraint> todo = sources;
-    while (todo.length > 0) {
-      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.length > 0) {
-      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.length > 0) {
-      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 = 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("v$i", 0);
-    if (prev != null) new EqualityConstraint(prev, v, REQUIRED);
-    if (i == 0) first = v;
-    if (i == n) last = v;
-    prev = v;
-  }
-  new StayConstraint(last, STRONG_DEFAULT);
-  EditConstraint edit = new 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:");
-      print("Expected last value to be $i but it was ${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 = new Planner();
-  Variable scale = new Variable("scale", 10);
-  Variable offset = new Variable("offset", 1000);
-  Variable src = null, dst = null;
-
-  List<Variable> dests = <Variable>[];
-  for (int i = 0; i < n; i++) {
-    src = new Variable("src", i);
-    dst = new Variable("dst", i);
-    dests.add(dst);
-    new StayConstraint(src, NORMAL);
-    new 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 = new 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;