我正在尝试按级别顺序打印b树，但它会继续崩溃。我不确定什么是真正的原因，但我认为它因为指针而崩溃。我试图使用我在网上找到的功能，通过每个级别并将其放入队列并打印出来，但我遇到了这个问题。如果有人有另一种方式，请告诉我。
// C++ program for B-Tree insertion
#include<iostream>
#include <queue>
using namespace std;
int ComparisonCount = 0;
// A BTree node
class BTreeNode
{
int *keys; // An array of keys
int t; // Minimum degree (defines the range for number of keys)
BTreeNode **C; // An array of child pointers
int n; // Current number of keys
bool leaf; // Is true when node is leaf. Otherwise false
public:
BTreeNode(int _t, bool _leaf); // Constructor
// A utility function to insert a new key in the subtree rooted with
// this node. The assumption is, the node must be non-full when this
// function is called
void insertNonFull(int k);
// A utility function to split the child y of this node. i is index of y in
// child array C[]. The Child y must be full when this function is called
void splitChild(int i, BTreeNode *y);
// A function to traverse all nodes in a subtree rooted with this node
void traverse();
// A function to search a key in subtree rooted with this node.
BTreeNode *search(int k); // returns NULL if k is not present.
// Make BTree friend of this so that we can access private members of this
// class in BTree functions
friend class BTree;
};
// A BTree
class BTree
{
BTreeNode *root; // Pointer to root node
int t; // Minimum degree
public:
// Constructor (Initializes tree as empty)
BTree(int _t)
{
root = NULL; t = _t;
}
// function to traverse the tree
void traverse()
{
if (root != NULL) root->traverse();
}
// function to search a key in this tree
BTreeNode* search(int k)
{
return (root == NULL) ? NULL : root->search(k);
}
// The main function that inserts a new key in this B-Tree
void insert(int k);
};
// Constructor for BTreeNode class
BTreeNode::BTreeNode(int t1, bool leaf1)
{
// Copy the given minimum degree and leaf property
t = t1;
leaf = leaf1;
// Allocate memory for maximum number of possible keys
// and child pointers
keys = new int[2 * t - 1];
C = new BTreeNode *[2 * t];
// Initialize the number of keys as 0
n = 0;
}
// Function to traverse all nodes in a subtree rooted with this node
/*void BTreeNode::traverse()
{
// There are n keys and n+1 children, travers through n keys
// and first n children
int i;
for (i = 0; i < n; i++)
{
// If this is not leaf, then before printing key[i],
// traverse the subtree rooted with child C[i].
if (leaf == false)
{
ComparisonCount++;
C[i]->traverse();
}
cout << " " << keys[i];
}
// Print the subtree rooted with last child
if (leaf == false)
{
ComparisonCount++;
C[i]->traverse();
}
}*/
// Function to search key k in subtree rooted with this node
BTreeNode *BTreeNode::search(int k)
{
// Find the first key greater than or equal to k
int i = 0;
while (i < n && k > keys[i])
i++;
// If the found key is equal to k, return this node
if (keys[i] == k)
{
ComparisonCount++;
return this;
}
// If key is not found here and this is a leaf node
if (leaf == true)
{
ComparisonCount++;
return NULL;
}
// Go to the appropriate child
return C[i]->search(k);
}
// The main function that inserts a new key in this B-Tree
void BTree::insert(int k)
{
// If tree is empty
if (root == NULL)
{
ComparisonCount++;
// Allocate memory for root
root = new BTreeNode(t, true);
root->keys[0] = k; // Insert key
root->n = 1; // Update number of keys in root
}
else // If tree is not empty
{
// If root is full, then tree grows in height
if (root->n == 2 * t - 1)
{
ComparisonCount++;
// Allocate memory for new root
BTreeNode *s = new BTreeNode(t, false);
// Make old root as child of new root
s->C[0] = root;
// Split the old root and move 1 key to the new root
s->splitChild(0, root);
// New root has two children now. Decide which of the
// two children is going to have new key
int i = 0;
if (s->keys[0] < k)
{
ComparisonCount++;
i++;
}s->C[i]->insertNonFull(k);
// Change root
root = s;
}
else // If root is not full, call insertNonFull for root
root->insertNonFull(k);
}
}
// A utility function to insert a new key in this node
// The assumption is, the node must be non-full when this
// function is called
void BTreeNode::insertNonFull(int k)
{
// Initialize index as index of rightmost element
int i = n - 1;
// If this is a leaf node
if (leaf == true)
{
ComparisonCount++;
// The following loop does two things
// a) Finds the location of new key to be inserted
// b) Moves all greater keys to one place ahead
while (i >= 0 && keys[i] > k)
{
keys[i + 1] = keys[i];
i--;
}
// Insert the new key at found location
keys[i + 1] = k;
n = n + 1;
}
else // If this node is not leaf
{
// Find the child which is going to have the new key
while (i >= 0 && keys[i] > k)
i--;
// See if the found child is full
if (C[i + 1]->n == 2 * t - 1)
{
ComparisonCount++;
// If the child is full, then split it
splitChild(i + 1, C[i + 1]);
// After split, the middle key of C[i] goes up and
// C[i] is splitted into two. See which of the two
// is going to have the new key
if (keys[i + 1] < k)
i++;
}
C[i + 1]->insertNonFull(k);
}
}
// A utility function to split the child y of this node
// Note that y must be full when this function is called
void BTreeNode::splitChild(int i, BTreeNode *y)
{
// Create a new node which is going to store (t-1) keys
// of y
BTreeNode *z = new BTreeNode(y->t, y->leaf);
z->n = t - 1;
// Copy the last (t-1) keys of y to z
for (int j = 0; j < t - 1; j++)
z->keys[j] = y->keys[j + t];
// Copy the last t children of y to z
if (y->leaf == false)
{
ComparisonCount++;
for (int j = 0; j < t; j++)
z->C[j] = y->C[j + t];
}
// Reduce the number of keys in y
y->n = t - 1;
// Since this node is going to have a new child,
// create space of new child
for (int j = n; j >= i + 1; j--)
C[j + 1] = C[j];
// Link the new child to this node
C[i + 1] = z;
// A key of y will move to this node. Find location of
// new key and move all greater keys one space ahead
for (int j = n - 1; j >= i; j--)
keys[j + 1] = keys[j];
// Copy the middle key of y to this node
keys[i] = y->keys[t - 1];
// Increment count of keys in this node
n = n + 1;
}
void BTreeNode::traverse()
{
std::queue<BTreeNode*> queue;
queue.push(this);
while (!queue.empty())
{
BTreeNode* current = queue.front();
queue.pop();
int i;
for (i = 0; i < n; i++)
{
if (leaf == false)
queue.push(current->C[i]);
cout << " " << current->keys[i] << endl;
}
if (leaf == false)
queue.push(current->C[i]);
}
}
// Driver program to test above functions
int main()
{
BTree t(4); // A B-Tree with minium degree 4
srand(29324);
for (int i = 0; i<200; i++)
{
int p = rand() % 10000;
t.insert(p);
}
cout << "Traversal of the constucted tree is ";
t.traverse();
int k = 6;
(t.search(k) != NULL) ? cout << "\nPresent" : cout << "\nNot Present";
k = 28;
(t.search(k) != NULL) ? cout << "\nPresent" : cout << "\nNot Present";
cout << "There are " << ComparisonCount << " comparison." << endl;
system("pause");
return 0;
}
答案 0 :(得分：1)
您的遍历代码使用this的字段值，就好像它们是循环体中current节点的值一样。
您需要将current->粘贴在循环体中的成员引用之前（在标有＆＃34; // *＆＃34;的行中）：
while (!queue.empty())
{
BTreeNode* current = queue.front();
queue.pop();
int i;
for (i = 0; i < current->n; i++) //*
{
if (current->leaf == false) //*
queue.push(current->C[i]);
cout << " " << current->keys[i] << endl;
}
if (current->leaf == false) //*
queue.push(current->C[i]);
}
这是一个强有力的指标，即所有符合current->条件的东西都希望生活在this的函数中，因此不需要明确命名。
您的代码组织起来比我们在这里得到的大多数调试请求更有条理，更令人愉快，但它仍然相当脆弱，它包含了很多像if (current->leaf == false)而不是if (not current->is_leaf)这样的臭味位。
您可能希望在将其付诸实际时将其发布在Code Review上;我确信那些经验丰富的编程人员可以为您提供有关如何改进代码的大量宝贵建议。
为了简化原型设计和开发，我强烈建议如下：
std::vector<>而不是裸阵列assert()进行文档化和检查 - 本地不变量/Wall /Wextra编译代码并进行清理，以便始终编译而不会发出警告另外，不要随意使用int;不能变为负数的基本类型是unsigned（节点度，当前键数等）。
P.S。：通过在键数上固定顺序来构建一致的B树会更容易（即，对于某些K，键的数量可以在K和2 * K之间变化）。固定指针数量的顺序会使事情变得更加困难，其结果之一就是“订单”键的数量。 2（其中一个节点允许有2到4个指针）可以在1到3之间变化。对于大多数处理B树的人来说，这将是一个意想不到的景象！