c - 自由(): invalid next size (normal) with qsort()

Question

当对大小为 210*8 的种子数据集运行此代码时，我在预测函数中的 qsort() 行之后收到错误。它不在 qsort() 之后执行。

我不确定 qsort 是否导致了此错误或为什么会发生此错误，但如果有任何见解，我们将不胜感激。

执行 qsort 语句时出现错误。

我的代码:

`include stdio.h
    include stdlib.h
    include string.h
    include math.h

    typedef struct point{
        int class;
        float coords[7], dist;
    }point;

    int argmax(int arr[], int n){
        int marg = -1, mxf = -1, i;
        for (i =0; i<= n; i++){
            if (arr[i] > mxf){
                mxf = arr[i];
                marg = i;
            }
        }
        return marg;
    }

    float get_accuracy(int pred[], int act[], int n){
        float cor = 0;
        int i;
        for (i = 0; i< n; i++){
            if (pred[i] == act[i]) cor +=1;
        }
        return (cor*100.0)/n ;
    }

    float get_avg(float arr[], int n){
        float sum = 0;
        int i;
        for (i = 0; i<n; i++){
            sum +=  arr[i];
        }
        return sum/n;
    }

    point *shuffle(point *dataset, int rows, int features, int groups, int classes)
    {
        int i,j,k,l,m = 0;
        point *shuffled_dataset;
        shuffled_dataset = (point *)malloc(sizeof(point)*rows);
        for(i=0; i<rows/classes; i++,m++)
        {
            for(j=0; j<rows/(groups*classes); j++)
            {
                for(k=0; k<classes; k++,m++)
                {
                    shuffled_dataset[m] = dataset[rows/classes*k + i];
                    /*for(l=0; l<features; l++)
                    {
                        shuffled_dataset[m].coords[l] = dataset[rows/classes*k + i].coords[l];
                    }*/
                }
                i++;
            }
            i--;
        }
        return shuffled_dataset;
    }


    float minkowski_dist(float* x, float* y, int len, int p){
        int i;
        float sum=0;
        for(i=0;i < len; i++){
            sum += pow(fabs(x[i] - y[i]),p);
        }
        return pow(sum,1/p);
    }

    int comparison(const void *a, const void *b) {
        point *ia = (point *)a;
        point *ib = (point *)b;
        return (int)(100.f*ia->dist - 100.f*ib->dist);
    }

    int predict(point test_point, point train[], int n, int k, int p, int classes, int features){
        int i;
        printf("Hi\n");
        for (i = 0; i < n; i++)
        {
            train[i].dist = minkowski_dist(test_point.coords, train[i].coords, features, p);
            printf("%d.\t", i+1);
            print_point(train[i]);
        }
        qsort (train, n-1, sizeof(train[0]), comparison);
        int freq[classes+1];
        for (i = 0; i < classes+1; ++i)
            freq[i] = 0;
        for (i = 0; i < k; i++)  
           freq[train[i].class]++; 
        return argmax(freq,classes);
    }

    float rFoldKNN(point *arr, int num, int r, int k, int p,  int classes, int features){
        int gsize = num/r;
        int i, j, h;
        int pred[gsize], act[gsize];
        point cval[gsize], train[num - gsize];
        float acc[r];
        for(i=0; i<r; i++)
        {
            int cind = 0, tind = 0;
            for(j=0; j<gsize; j++)
            {
                cval[cind++] = arr[gsize*i+j];
                for(k=0; k<r; k++)
                {
                    if(k!=i)
                    {
                        train[tind++] = arr[gsize*k+j];
                    }
                }
            }
            for(j=0; j<gsize; j++)
            {
                printf("%d\t%d\n", tind, cind);
                pred[j] = predict(cval[j], train,  num-gsize, k,  p, classes, features);
                act[j] = cval[j].class;
            }
            acc[i] = get_accuracy(pred, act,  gsize);
        }
        return get_avg(acc,r);
    }

    int main()
    {
        FILE *fp;
        int r = 10, p = 5, k = 10;
        int rows = 210;
        int columns = 8;
        int classes = 3;
        int size = rows * columns; /*Assumed size of the dataset*/
        float *data;          /*Creating an array of assumed size as 1d(split after every 8 values to get the next row)*/
        int count = 0;
        int i, j;
        float accuracies [k][p], maxac = -1.0;;
        int maxk, maxp;
        float c;
        point *all;
        all = (point *)malloc(sizeof(point)*rows);
        data = (float*)malloc(sizeof(float*)*size);
        if ((fp = fopen("seeds_dataset.txt", "r")) == NULL)
        {
            printf("Error reading file!");
            exit(1);
        }
        for(i = 0; i < rows; i++){
            for (j = 0 ; j < columns; j++){
                fscanf(fp,"%f",&c);
                if (j == columns-1)
                    all[i].class = c;
                else
                    all[i].coords[j] = c;
            }
        }
        fclose(fp);
        for(i=0; i<rows; i++)
        {
            printf("%d.\t", i+1);
            print_point(all[i]);
        }
        all = shuffle(all, rows, columns-1, 10, classes);
        printf("Hi\n");
        for(i=0; i<rows; i++)
        {
            printf("%d.\t", i+1);
            print_point(all[i]);
        }
        for (i = 1; i <= k; ++i){
            for (j = 1; j <= p; ++j){
                accuracies[i][j] = rFoldKNN(all, rows, r, i, j, classes, columns-1);
                if (accuracies[i][j] > maxac){
                    maxac = accuracies[i][j];
                    maxk = i;
                    maxp = j;
                }
            }
        }
        printf("best validation accuracy %f  best k %d best p %d ",maxac, maxk, maxp );
        return 0;
    }

`

Answer 1

free(): invalid next size 是当您损坏了 malloc 使用的内存区域时经常收到的错误消息，例如写入超出了内存的末尾分配的 block ，破坏内存分配函数使用的内联记帐信息。

考虑到您的问题中实际代码的稀缺(或者，在您更新之后，您似乎没有缩小到更准确地定位的巨大代码量问题)，这就是我能提供的尽可能多的细节。我的建议是检查您的代码是否有未正确使用分配内存的区域。