Lab 08 - C Preprocessor

Slides:

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Lab8.pdf

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Lab 8 Slides

Exercise 5

1. char** cs1010_read_line_array(size_t k) will include the \n character.

C Preprocessing

1. Use #define to define a constant to make your program more readable.

Macro

A macro is a code snippet that is substituted into the program and expanded during pre-processing.

Example:

#include "cs1010.h"
#define SQUARE(x) x * x
int main() {
    // Will output 25
    cs1010_println_long(SQUARE(5));
    // Will output 16.0000
    cs1010_println_double(SQUARE(4.0));
    return 0;
}

Generic Types

We can use a generic type (or type parameter) to restrict the type of the arguments used in a macro.

Example:

#include "cs1010.h"
#define SWAP(T, x, y) {T t; t = x; x = y; y = t}
int main() {
    long a = 1;
    long b = 2;
    SWAP(long, a, b); // Now a == 2 && b == 1
    char m[4] = "abc";
    char n[4] = "123";
    SWAP(char *, m, n);
    // Now m is "123" and n is "abc"
    return 0;
}

Pitfall

Be careful with situations like this:

#include "cs1010.h"
#define SQUARE(x) x * x
int main() {
    cs1010_println_long(SQUARE(5 + 1));
    // The above gets expanded to 5 + 1 * 5 + 1
    return 0;
}

Therefore, we should always use brackets around the arguments of a macro, i.e., SQUARE(x) (x) * (x) is safe.

Bonus Info

1. There are five major types of operations which are core to algorithm optimization: insertion, removal, retrieval, searching and sorting.

Searching and Sorting

Binary Search

1. Probably the most powerful search algorithm for simple arrays.

2. The idea of search space.

3. Sorted means non-descending in CS.

Comparison-Based Sort

The idea is the pair-wised comparison is important.

Bubble Sort

1. There are some better cases when the time complexity is $O(N)$.

Insertion Sort

1. When the array is sorted, the time complexity is $O(N)$

Selection Sort

1. The time complexity is always $O(N)$

Counting Sort

1. To use it on negative indices, use the idea of mapping. For example, -9 to 0.

Exercise 6

1. Start from the minimum point, have two directions.

2. Every time see $log(n)$, try thinking about binary search.

3. Every time see $O(N)$, which means can done in one iteration.