我在课堂上为一个项目编写代码，并且产生了异常的结果。行和列的值最终以数百万的随机数结尾，最终会引发异常，我不明白为什么。
#include <iostream>
using namespace std;
class SparseRow {
protected:
int row;
int col;
int value;
public:
SparseRow();
SparseRow(int inRow, int inCol, int inVal);
SparseRow(const SparseRow& newRow);
SparseRow& operator=(const SparseRow& newRow);
~SparseRow();
void display();
int getRow();
int getCol();
int getValue();
void setRow(int inRow);
void setCol(int inCol);
void setValue(int inVal);
};
class SparseMatrix {
protected:
int noRows;
int noCols;
int commonValue;
int noSparseValues;
SparseRow *myMatrix;
void setNoSparseValues(int noSV);
public:
SparseMatrix();
SparseMatrix(int rows, int cols, int cv, int noSV);
SparseMatrix(const SparseMatrix& matrix);
SparseMatrix& operator=(const SparseMatrix& matrix);
~SparseMatrix();
void readMatrix();
SparseMatrix* transpose();
SparseMatrix* multiply(SparseMatrix& M);
SparseMatrix* add(SparseMatrix& M);
void display();
void displayMatrix();
int getNoRows();
int getNoCols();
int getCommonValue();
int getNoSparseValues();
int getValue(int row, int col);
void setValue(int row, int col, int val);
};
SparseRow::SparseRow() {
row = -1;
col = -1;
value = 0;
}
SparseRow::SparseRow(int inRow, int inCol, int inVal) {
row = inRow;
col = inCol;
value = inVal;
}
SparseRow::SparseRow(const SparseRow& newRow) {
row = newRow.row;
col = newRow.col;
value = newRow.value;
}
SparseRow& SparseRow::operator=(const SparseRow& newRow) {
if (this != &newRow) {
row = newRow.row;
col = newRow.col;
value = newRow.value;
}
return *this;
}
SparseRow::~SparseRow() {
cout << "Deleting SparseRow with values: " << endl;
display();
}
void SparseRow::display() {
cout << "Row: " << row << ", Column: " << col << ", Value: " << value << endl;
}
int SparseRow::getRow() {
return row;
}
int SparseRow::getCol() {
return col;
}
int SparseRow::getValue() {
return value;
}
void SparseRow::setRow(int inRow) {
row = inRow;
}
void SparseRow::setCol(int inCol) {
col = inCol;
}
void SparseRow::setValue(int inVal) {
value = inVal;
}
SparseMatrix::SparseMatrix() {
noRows = 0;
noCols = 0;
commonValue = 0;
noSparseValues = 0;
}
SparseMatrix::SparseMatrix(int rows, int cols, int cv, int noSV) {
noRows = rows;
noCols = cols;
commonValue = cv;
noSparseValues = noSV;
myMatrix = new SparseRow[rows * cols];
}
SparseMatrix::SparseMatrix(const SparseMatrix& matrix) {
noRows = matrix.noRows;
noCols = matrix.noCols;
commonValue = matrix.commonValue;
noSparseValues = matrix.noSparseValues;
myMatrix = matrix.myMatrix;
}
SparseMatrix& SparseMatrix::operator=(const SparseMatrix& matrix) {
if (this != &matrix) {
delete[] myMatrix;
noRows = matrix.noRows;
noCols = matrix.noCols;
commonValue = matrix.commonValue;
noSparseValues = matrix.noSparseValues;
myMatrix = matrix.myMatrix;
}
return *this;
}
SparseMatrix::~SparseMatrix() {
cout << "Deleting SparseMatrix with values: " << endl;
display();
delete[] myMatrix;
}
void SparseMatrix::readMatrix() {
int count = 0;
int val;
for (int i = 0; i < noRows; i++) {
for (int j = 0; j < noCols; j++) {
cin >> val;
if (val != commonValue) {
myMatrix[count].setRow(i);
myMatrix[count].setCol(j);
myMatrix[count].setValue(val);
// Why does C++ prevent me from calling a constructor on objects in an array? It doesn't make sense.
count++;
}
}
}
if (count != noSparseValues) {
cout << "ERROR: Incorrect number of sparse values! Changing to correct number." << endl;
noSparseValues = count;
}
}
SparseMatrix* SparseMatrix::transpose() {
SparseMatrix *newMatrix = new SparseMatrix(noCols, noRows, commonValue, noSparseValues);
for (int i = 0; i < noSparseValues; i++) {
newMatrix->setValue(myMatrix[i].getCol(), myMatrix[i].getRow(), myMatrix[i].getValue());
}
return newMatrix;
}
SparseMatrix* SparseMatrix::multiply(SparseMatrix& M) {
if (noCols != M.getNoRows()) {
cout << "ERROR: Matrices cannot be multiplied!" << endl;
return NULL;
}
SparseMatrix *newMatrix = new SparseMatrix(noRows, M.getNoCols(), commonValue, noRows * M.getNoCols());
// Why does C++ prevent me from creating an array to store this information? It doesn't make sense.
int SVCount = 0;
for (int i = 0; i < noRows; i++) {
for (int j = 0; j < M.getNoCols(); j++) {
int sum = 0;
for (int k = 0; k < noCols; k++) {
sum += getValue(i, k) * M.getValue(k, j);
}
if (sum != newMatrix->getCommonValue()) {
SVCount++;
}
newMatrix->setValue(i, j, sum);
}
}
newMatrix->setNoSparseValues(SVCount);
return newMatrix;
}
SparseMatrix* SparseMatrix::add(SparseMatrix& M) {
if (noRows != M.getNoRows() || noCols != M.getNoCols()) {
cout << "ERROR: Matrices cannot be added!" << endl;
return NULL;
}
SparseMatrix *newMatrix = new SparseMatrix(noRows, noCols, commonValue + M.getCommonValue(), noRows * noCols);
int SVCount = 0;
for (int i = 0; i < noRows; i++) {
for (int j = 0; j < noCols; j++) {
int sum = getValue(i, j) + M.getValue(i, j);
if (sum != newMatrix->getCommonValue()) {
SVCount++;
}
newMatrix->setValue(i, j, sum);
}
}
newMatrix->setNoSparseValues(SVCount);
return newMatrix;
}
void SparseMatrix::display() {
for (int i = 0; i < noSparseValues; i++) {
myMatrix[i].display();
}
}
void SparseMatrix::displayMatrix() {
for (int i = 0; i < noRows; i++) {
for (int j = 0; j < noCols; j++) {
cout << getValue(i, j) << " ";
}
cout << endl;
}
}
int SparseMatrix::getNoRows() {
return noRows;
}
int SparseMatrix::getNoCols() {
return noCols;
}
int SparseMatrix::getCommonValue() {
return commonValue;
}
int SparseMatrix::getNoSparseValues() {
return noSparseValues;
}
void SparseMatrix::setNoSparseValues(int noSV) {
noSparseValues = noSV;
}
int SparseMatrix::getValue(int row, int col) {
for (int i = 0; i < noSparseValues; i++) {
if (myMatrix[i].getRow() == row && myMatrix[i].getCol() == col) {
return myMatrix[i].getValue();
}
}
return commonValue;
}
void SparseMatrix::setValue(int row, int col, int val) {
bool replacingSparse = (getValue(row, col) != commonValue);
bool replacingWithSparse = (val != commonValue);
int index = -1;
if (replacingSparse) {
for (int i = 0; i < noSparseValues; i++) {
if (myMatrix[i].getRow() == row && myMatrix[i].getCol() == col) {
index = i;
break;
}
}
if (replacingWithSparse) {
myMatrix[index].setValue(val);
}
else {
for (int i = index; i < noSparseValues; i++) {
myMatrix[i] = myMatrix[i + 1];
}
noSparseValues--;
}
}
else {
if (replacingWithSparse) {
for (int i = 0; i < noSparseValues; i++) {
if (myMatrix[i].getRow() > row || (myMatrix[i].getRow() >= row && myMatrix[i].getCol() > col)) {
index = i;
break;
}
}
for (int i = noSparseValues; i > index; i--) {
myMatrix[i] = myMatrix[i - 1];
}
myMatrix[index].setRow(row);
myMatrix[index].setCol(col);
myMatrix[index].setValue(val);
noSparseValues++;
}
}
}
int main() {
int n, m, cv, noNSV;
SparseMatrix* temp;
cin >> n >> m >> cv >> noNSV;
SparseMatrix* firstOne = new SparseMatrix(n, m, cv, noNSV);
firstOne->readMatrix();
cin >> n >> m >> cv >> noNSV;
SparseMatrix* secondOne = new SparseMatrix(n, m, cv, noNSV);
secondOne->readMatrix();
cout << "First one in sparse matrix format" << endl;
firstOne->display();
cout << "First one in normal matrix format" << endl;
firstOne->displayMatrix();
cout << "Second one in sparse matrix format" << endl;
secondOne->display();
cout << "Second one in normal matrix format" << endl;
secondOne->displayMatrix();
cout << "After Transpose first one in normal format" << endl;
temp = firstOne->transpose();
temp->displayMatrix();
cout << "After Transpose second one in normal format" << endl;
temp = secondOne->transpose();
temp->displayMatrix();
cout << "Multiplication of matrices in sparse matrix form:" << endl;
temp = secondOne->multiply(*firstOne);
temp->display();
cout << "Addition of matrices in sparse matrix form:" << endl;
temp = secondOne->add(*firstOne);
temp->display();
}
输入：
3 3 0 3
2 2 2
0 0 0
0 0 0
3 3 0 3
2 2 2
0 0 0
0 0 0
预期输出：（格式不完全相同，但数字应相同）
First one in sparse matrix format
0, 0, 2
0, 1, 2
0, 2, 2
First one in normal matrix format
2 2 2
0 0 0
0 0 0
Second one in sparse matrix format
0, 0, 2
0, 1, 2
0, 2, 2
Second one in normal matrix format
2 2 2
0 0 0
0 0 0
After Transpose first one
2 0 0
2 0 0
2 0 0
After Transpose second one
2 0 0
2 0 0
2 0 0
Multiplication of matrices in sparse matrix form:
0, 0, 4
0, 1, 4
0, 2, 4
Addition of matrices in sparse matrix form:
0, 0, 4
0, 1, 4
0, 2, 4
实际输出：
First one in sparse matrix format
Row: 0, Column: 0, Value: 2
Row: 0, Column: 1, Value: 2
Row: 0, Column: 2, Value: 2
First one in normal matrix format
2 2 2
0 0 0
0 0 0
Second one in sparse matrix format
Row: 0, Column: 0, Value: 2
Row: 0, Column: 1, Value: 2
Row: 0, Column: 2, Value: 2
Second one in normal matrix format
2 2 2
0 0 0
0 0 0
After Transpose first one in normal format
0 0 0
2 0 0
2 0 0
After Transpose second one in normal format
0 0 0
2 0 0
2 0 0
Multiplication of matrices in sparse matrix form:
Row: 0, Column: 1, Value: 4
Row: 0, Column: 2, Value: 4
Row: 369, Column: -33686019, Value: 9
Addition of matrices in sparse matrix form:
(Exceptions thrown here, line 222 in code)
引发异常：
Project1.exe has triggered a breakpoint.
Unhandled exception at 0x777E8499 (ntdll.dll) in Project1.exe: 0xC0000374: A heap has been corrupted (parameters: 0x77825890).
答案 0 :(得分：1)
我将只解决发布代码中的一些问题。
他们的显式使用总是容易出错，并且在每个新版本的标准中都越来越不鼓励这样做。
在OP的代码中，他们拥有管理内存资源的责任，但是在C ++中，当对象超出范围时，它们不会自动调用对象的析构函数。
这就是像std::unique_ptr这样的智能指针所能做的。
让我们看看main中会发生什么：
int n, m, cv, noNSV;
SparseMatrix* temp; // <- Declaration far from initialization
cin >> n >> m >> cv >> noNSV;
SparseMatrix* firstOne = new SparseMatrix(n, m, cv, noNSV);
// ^^^^^^^^^^^^^^^^ Why?
// ...
temp = firstOne->transpose(); // <- Here the pointer is initialized
// ...
temp = secondOne->transpose(); // <- Here the pointer is overwritten, but the allocated memory
// isn't released, it leaks.
// ...
temp = secondOne->multiply(*firstOne); // <- Again...
// ...
temp = secondOne->add(*firstOne); // <- ...and again
// ...
// No 'delete' calls at the end, so no destructor is called for the previously allocated objects
在这里使用指针的唯一原因是SparseMatrix::transpose()旨在返回一个指针，但是它可以轻松地重新运行SparseMatrix（返回值优化可以避免不必要的复制）。
每次new的调用都应对应一个delete，并且由于transpose之类的函数返回指向新分配对象的指针，因此delete temp;应该在覆盖{{ 1}}，以确保调用了正确的析构函数。
但是，在C ++中，我们应该利用RAII（资源获取就是初始化，也称为范围绑定资源管理）：
temp这实际上与先前的观点有关，例如复制分配操作符在发布的代码段中实现：
{ // <- Start of a scope
int n, m, cv, noNSV;
std::cin >> n >> m >> cv >> noNSV;
// Declare a variable using the constructor. Its lifetime begins here.
SparseMatrix firstOne(n, m, cv, noNSV);
// The same for 'secondOne'
// ...
// SparseSparse::transpose() here should return a SparseMatrix, not a pointer
SparseMatrix temp = firstOne.transpose();
// ...
// Here the matrix is reassigned (which can be cheap if move semantic is implemented)
temp = secondOne.transpose();
// ...
temp = secondOne.multiply(firstOne); // <- Again...
// ...
} // <- End of scope, all the destructors are called. No leaks.
对此功能和其他特殊功能的正确实现将利用“复制和交换”习惯用法，在此处进行了详细介绍：
What is the copy-and-swap idiom?
此外，关于OP的阅读功能中的此评论：
SparseMatrix& SparseMatrix::operator=(const SparseMatrix& matrix) {
if (this != &matrix) { // <- debatable, see copy-and-swap idiom
delete[] myMatrix; // <- putted here makes this function not exception safe ^^
noRows = matrix.noRows;
noCols = matrix.noCols;
commonValue = matrix.commonValue;
noSparseValues = matrix.noSparseValues;
myMatrix = matrix.myMatrix; // <- The pointer is overwritten, but this is shallow copy
// what you need is a deep copy of the array
}
return *this;
}
请求者可以在此处使用new的放置参数（新放置）：
for (int i = 0; i < noRows; i++) {
for (int j = 0; j < noCols; j++) {
cin >> val;
if (val != commonValue) {
myMatrix[count].setRow(i);
myMatrix[count].setCol(j);
myMatrix[count].setValue(val);
// Why does C++ prevent me from calling a constructor on objects in an array? It doesn't make sense.
count++;
}
}
}
OP还有许多其他问题要解决。