This content originally appeared on DEV Community and was authored by MegaWatts
Solving complex problems is more than just a technical challenge; it’s a journey of continuous learning and growth. As a growing backend developer, I’ve always been driven by the desire to develop efficient, scalable, and maintainable server-side logic. Recently, I faced a challenge that tested my skills, thought process, and determination.
I was tasked with optimizing the business logic at the server-side for an equipment management system. Equipment are to be serviced based on data from different components of the equipment inputted by the user. Initially, the criteria for servicing an equipment were based on the engine and tire components. Management decided to add another criterion for servicing, which added to the complexity of the system.
At that time, the existing implementation of the logic wasn’t up to par. It lacked reusability, separation of concerns, and was difficult to understand. Here are the steps I took to solve the challenge:
Understand the Requirements
Before diving into coding, I made a concerted effort to understand the requirements of the system. This included:
The functionality the system needs to provide.
The various modules or components required.
How these components will interact with each other.
Identify Core Components
I identified the core components of the system. An equipment was modeled as a class using other components like engine, tire, and fuel consumption properties. Each component represented a distinct part of the functionality:
Equipment Management
Component Management
Service Management
A UML Class Diagram to state the relationships between classes was created.
Define Responsibilities Clearly
Each class was designed to have a single responsibility. This approach makes classes easier to understand, maintain, and reuse. For example:
The Equipment class handles general equipment details.
The Engine class manages engine-specific properties and behaviors.
The ServiceManager class handles the logic for determining when an equipment needs servicing.
Use Interfaces and Abstract Classes
Interfaces and abstract classes help in defining contracts and promoting code reuse. I used them to outline the basic structure and functionality that concrete classes should implement.
python
from abc import ABC, abstractmethod
class Component(ABC):
@abstractmethod
def needs_service(self) -> bool:
pass
Implement Concrete Classes
I implemented the concrete classes that adhere to the interfaces or extend the abstract classes. This ensures that the classes are consistent and reusable.
python
class Engine(Component):
def __init__(self, hours_run: int):
self.hours_run = hours_run
def needs_service(self) -> bool:
return self.hours_run > 1000
class Tire(Component):
def __init__(self, wear_level: float):
self.wear_level = wear_level
def needs_service(self) -> bool:
return self.wear_level > 0.8
Use Design Patterns
I studied and implemented design patterns to promote reusability and simplicity. Using the Factory pattern, I was able to produce reusable and simple components.
python
class ComponentFactory:
@staticmethod
def create_component(component_type: str, **kwargs) -> Component:
if component_type == "engine":
return Engine(**kwargs)
elif component_type == "tire":
return Tire(**kwargs)
else:
raise ValueError("Unknown component type")
Keep It Simple
I adhered to the KISS principle by ensuring each class does one thing and does it well. This made the codebase easier to understand and maintain.
Write Tests
I wrote unit tests for each class to ensure they work as expected. This also makes future changes easier and safer.
python
import unittest
class TestEngine(unittest.TestCase):
def test_needs_service(self):
engine = Engine(hours_run=1200)
self.assertTrue(engine.needs_service())
if __name__ == "__main__":
unittest.main()
By following these steps, I was able to create classes that adhere to the KISS principle, making the codebase easier to maintain and extend. The result of refactoring the code was a dramatic improvement in the application's design. It became easy to understand, maintain, and extend. This experience not only solved a critical problem but also deepened my understanding of software design principles.
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This content originally appeared on DEV Community and was authored by MegaWatts
MegaWatts | Sciencx (2024-06-30T00:22:06+00:00) Overcoming Challenges. Retrieved from https://www.scien.cx/2024/06/30/overcoming-challenges/
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