红黑树的删除压力测试和完整性检查

　　之前的文章写了红黑树的实现，因为自己实现了插入和删除的算法。为了测试算法的性能，以及算法的正确性，又写了几个函数，用来检查一棵树是否是红黑树，并进行压力测试，代码如下：

import 'dart:math';
import 'package:data_struct/tree/tree.dart';

void run() {
  var size = 100000, loops = 1024;
  check(size, loops);
  stress(size);
}

void check(int size, int loops) {
  var rd = Random();
  for (var i = 0; i < loops; i++) {
    print('the $i times check...');

    var arr = List.generate(size, (_) => rd.nextDouble() * size);
    var tree = RBTree.from(arr);
    var bh = _checkIsRBTree(tree);
    print('black height: $bh

');

    for (var d in arr) {
      tree.delete(d);
      _checkIsRBTree(tree);
    }

    tree = RBTree.from(arr);
    for (var d in arr) {
      tree.quickDelete(d);
      _checkIsRBTree(tree);
    }
  }
}

void stress(int size) {
  var rd = Random();
  var arr = List.generate(size, (_) => rd.nextDouble() * size);

  var tree = RBTree.from(arr);
  var st = DateTime.now();
  for (var d in arr) tree.delete(d);
  var ft = DateTime.now();
  print('my delete implement cost:	${ft.difference(st)}');

  tree = RBTree.from(arr);
  st = DateTime.now();
  for (var d in arr) tree.quickDelete(d);
  ft = DateTime.now();
  print('    linux implement cost:	${ft.difference(st)}');
}

void traverse(RBTNode r, void func(RBTNode r)) {
  if (r != null) {
    traverse(r.left, func);
    func(r);
    traverse(r.right, func);
  }
}

int _checkIsRBTree(RBTree t) {
  assert(t.isEmpty || (!t.isEmpty && t.root.isBlack));
  return _goThrough(t.root);
}

int _goThrough(RBTNode r) {
  if (r == null) return 0;
  assert(r.isBlack || (r.isRed && r.parent.isBlack));
  var lbh = _goThrough(r.left);
  var rbh = _goThrough(r.right);
  assert(lbh == rbh);
  return lbh + (r.isRed ? 0 : 1);
}