June 24, 2023

Refactoring Legacy Code Using Clean Code Principles in C and Python

In the world of software development, it’s not uncommon to encounter legacy code that is difficult to understand, maintain, and extend. Refactoring is the practice of restructuring existing code without changing its external behavior to make it more readable, maintainable, and efficient. In this blog post, we will explore the application of clean code principles to refactor legacy code in C and Python, with extensive examples to demonstrate the concepts in detail.

Understanding Legacy Code

Legacy code is characterized by outdated and hard-to-maintain code that often lacks proper documentation and structure. Refactoring legacy code is essential to modernize and improve the overall quality of the codebase. Clean code principles, as defined by Robert C. Martin in his book “Clean Code,” provide guidelines for writing clear, readable, and maintainable code.

Clean Code Principles

1. Meaningful Names

One of the fundamental principles of clean code is using meaningful and descriptive names for variables, functions, and classes. In C and Python, meaningful names enhance the readability and understanding of the code.

Example in C:

1
2
3
4
5

// Bad naming
int x; // What does x represent?

// Good naming
int numberOfStudents; // Clearly indicates the purpose

Example in Python:

1
2
3
4
5

# Bad naming
a = 10  # What does 'a' represent?

# Good naming
number_of_students = 10  # Clearly indicates the purpose

2. Avoiding Magic Numbers

Magic numbers are hardcoded constants in the code that lack explanation, making the code less maintainable and prone to errors. Using named constants or enums improves the understandability of the code.

Example in C:

1
2
3
4
5
6

// Magic number
if (status == 1) { // What does 1 represent?

// Named constant
#define SUCCESS 1
if (status == SUCCESS) { // Clearly indicates success

Example in Python:

1
2
3
4
5
6

# Magic number
if result == 200:  # What does 200 represent?

# Named constant
SUCCESS_CODE = 200
if result == SUCCESS_CODE:  # Clearly indicates success

3. Single Responsibility Principle

Each function or module should have a single responsibility, making it easier to understand, test, and maintain.

Example in C:

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14

// Bad practice
void processDataAndSaveToFile() {
  // Process data
  // Save to file
}

// Good practice
void processData() {
  // Process data
}

void saveToFile() {
  // Save to file
}

Example in Python:

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11

# Bad practice
def process_data_and_save_to_file():
  # Process data
  # Save to file

# Good practice
def process_data():
  # Process data

def save_to_file():
  # Save to file

Refactoring Legacy Code

Now that we have an understanding of clean code principles, let’s apply these principles to refactor some legacy code examples in both C and Python.

Refactoring Example in C

Consider the following legacy C code:

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13

#include <stdio.h>

int main() {
  int a = 5, b = 6;
  int c;
  printf("Enter the value of c: ");
  scanf("%d", &c);
  int sum = a + b + c;
  int product = a * b * c;
  printf("Sum: %d\n", sum);
  printf("Product: %d\n", product);
  return 0;
}

Refactored Code:

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24

#include <stdio.h>

#define INITIAL_VALUE_A 5
#define INITIAL_VALUE_B 6

int calculateSum(int a, int b, int c) {
  return a + b + c;
}

int calculateProduct(int a, int b, int c) {
  return a * b * c;
}

int main() {
  int a = INITIAL_VALUE_A, b = INITIAL_VALUE_B;
  int c;
  printf("Enter the value of c: ");
  scanf("%d", &c);
  int sum = calculateSum(a, b, c);
  int product = calculateProduct(a, b, c);
  printf("Sum: %d\n", sum);
  printf("Product: %d\n", product);
  return 0;
}

In the refactored code, we have used meaningful names for variables, avoided magic numbers by using named constants, and separated the calculations into distinct functions following the single responsibility principle.

Refactoring Example in Python

Now let’s consider a legacy Python code snippet:

 1
 2
 3
 4
 5
 6
 7
 8
 9
10

def calculate_area(length, width):
    area = length * width
    print("Area:", area)

def main():
    l = 5
    w = 3
    calculate_area(l, w)

main()

Refactored Code:

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13

def calculate_rectangle_area(length, width):
    return length * width

def display_area(area):
    print("Area:", area)

def main():
    length = 5
    width = 3
    area = calculate_rectangle_area(length, width)
    display_area(area)

main()

In the refactored Python code, we have followed meaningful naming conventions, separated the calculations and display logic into distinct functions, and improved the overall readability and maintainability of the code.

Conclusion

Refactoring legacy code using clean code principles in C and Python is crucial for improving the quality, readability, and maintainability of the codebase. By applying principles such as meaningful names, avoiding magic numbers, and adhering to the single responsibility principle, we can transform legacy code into clean, efficient, and modern code that is easier to understand and maintain.

In this blog post, we have demonstrated practical examples of refactoring legacy code in both C and Python, highlighting the importance of clean code principles in the refactoring process. By embracing these principles, developers can effectively tackle legacy code challenges and create a more robust and maintainable codebase.

I hope this blog post provides valuable insights into the refactoring of legacy code using clean code principles in C and Python. Happy coding!

➡️ libc - limits header

⬅️ libc - stdbool header

Go back to Posts.