Code and databases refactoring is a technique commonly used in computer programming, and particularly in data engineering. It involves restructuring computer code without modifying its external behavior or functionality. Find out all you need to know about this method: definition, benefits, techniques, training…
In computer programming, it is sometimes necessary to add a function to a program at the last minute, before the new version is released.
However, there may not be enough time to add this function in an organized, structured way, in line with the rest of the code. As a result, functionality can be added in a haphazard way, in the hope that everything will run smoothly.
However, when the code is not sufficiently clean or optimized, it may be necessary to postpone certain tasks to avoid the project falling behind schedule. This creates a “technical debt”.
Fortunately, there is a way of reducing this technical debt by improving code cleanliness: refactoring databases
What is Code and Databases Refactoring?
Code and Databases Refactoring is the process of restructuring computer code without changing its original functionality. The aim is to improve internal code by making numerous changes without altering the code’s external behavior.
Computer programmers and software developers can use code refactoring to improve software design, structure and implementation.
Code and Databases Refactoring also improves code readability and reduces complexity. It can also help developers detect bugs or hidden vulnerabilities in their software.
There are many approaches to refactoring, but the most widely used is the application of a series of basic, standardized actions sometimes referred to as “micro-refactorings”.
The changes made to the existing source code preserve the software’s behavior and functionality, because they are so minimal that they are unlikely to create or introduce new errors.
The process involves making numerous small changes to the program’s source code. It is possible, for example, to improve the structure of the source code at one point and extend the same change systematically to different points in the program.
The idea is that these small changes to the body of the code can have a cumulative effect. In this way, the changes preserve the software’s original behavior and do not alter it.
Refactoring was invented by Martin Fowler, who combined the best practices of the software development industry into a specific list of methods described in his book Refactoring: Improving the Design of Existing Code.
What's the point of Code and Databases Refactoring?
Code and Databases Refactoring improves code in a number of ways. Firstly, it makes code more efficient by reducing dependencies and complexities.
It also simplifies code maintenance and reuse, increasing efficiency and readability. Code and Databases Refactoring makes code easier to read and understand.
Finally, it enables software developers to detect and correct bugs and vulnerabilities in the code more easily. These modifications are made to the code without changing the functions of the program itself.
What is a "dirty" code?
The main purpose of refactoring is to make the code cleaner. The term “dirty” code is used to refer to code that is difficult to maintain and update, and even more challenging to understand and translate.
Often, this problem arises from tight deadlines during development and the need to add or update features even if the backend doesn’t appear as it should.
However, the cleaner the code is, the easier it is to modify or improve it in future iterations. This is a real advantage for programmers.
If the code is not cleaned up, it can lead to a snowball effect and slow down future improvements. Developers will be forced to spend extra time understanding and navigating the code before making changes.
The concept of dirty code encompasses code that is too extensive to be easily manipulated, incomplete or incorrectly applied object-oriented programming principles, or unnecessary coupling.
Likewise, this term can refer to code that requires repeated modifications at different points for desired changes to work correctly. Finally, it can refer to code that is not needed and can be removed without impacting the overall functionality.
On the contrary, clean code is easier to read, understand, and maintain. It simplifies the future development of the software and allows for a higher-quality product to be delivered more quickly.
When should you refactor your code?
Refactoring can be done after the deployment of a product, before adding updates or new features to existing code, or as part of daily programming tasks.
When the process is carried out after deployment, it is done before developers start the next project.
This is the best time in the software delivery lifecycle to intervene because developers have maximum availability and more time to work on the changes required by the source code.
However, it is preferable to address refactoring before adding updates or new features to existing code. This allows developers to build more easily on the existing code since the code will be simplified and more readable.
Finally, an organization proficient in refactoring can practice it as a regular process. A developer can review existing code whenever they need to add elements to check if it is structured optimally. If not, refactoring can be a good solution.
Code and Databases Refactoring and Data Science
In the field of Data Science, refactoring can be used to enhance the performance of a data pipeline. Thanks to this technique, data processing can be reduced from several tens of hours to just a few minutes.
Furthermore, database refactoring involves changing the schema of a database to improve its design while preserving its behavior and informational semantics.
This technique does not alter how the data is interpreted or used, without fixing bugs or adding new features. The system continues to operate normally.
Refactoring a database is more complex than refactoring code because it is necessary to maintain informational semantics and not just behavioral semantics.
The goal may be to evolve the database schema, address design issues in an old database schema, or implement a series of small, low-risk changes.
Advantages and disadvantages of refactoring
Refactoring brings several advantages. It makes the code easier to read and understand, simplifies maintenance, and aids in bug detection.
This technique also encourages a deeper understanding of the code because developers must consider how their code will interact with the base. Furthermore, the fact that refactoring does not change the original functionality of the code helps to avoid altering the project.
However, refactoring also presents several challenges. This process can be time-consuming if the development team acts hastily and refactoring is not properly planned in advance.
Similarly, without a specific goal, refactoring can lead to delays and extra work. Finally, this method alone is not sufficient to address software vulnerabilities.
Refactoring techniques
Several different techniques can be used for refactoring, and it’s important to choose the optimal method based on the circumstances.
The “red, green” technique is widely used in Agile development and involves three steps. Developers start by identifying what needs to be developed, then test their project. Finally, code refactoring is performed to improve it.
On the other hand, the Inline method focuses on simplifying the code by eliminating unnecessary elements. Another approach is to move functionalities between objects to create new data classes.
The Extraction technique involves breaking down the code into smaller pieces and moving them to a different method. The fragmented code is replaced with a call to the new method.
As an alternative, abstraction refactoring reduces duplicated code volume.
This approach is suitable when a large amount of data needs to be refactored. Lastly, the composition technique simplifies the code to reduce duplications by using different refactoring methods like extraction and inline.
Code and Databases Refactoring: tips and tricks
To successfully refactor code, it’s important to adopt best practices. First and foremost, plan carefully to ensure that you allocate time for this operation.
It’s also important to address refactoring before adding updates or new features to existing code. The goal is to reduce technical debt.
Additionally, proceed in small steps to allow developers to receive feedback very early in the process. This will help them detect any potential bugs.
Developers should also set clear objectives and determine the scope and goals of the project very early in the code refactoring process. This will prevent delays and additional work.
Frequent testing also ensures that refactoring doesn’t introduce new bugs, while automation tools help gain speed and simplicity.
Keep in mind that refactoring is not intended to fix software vulnerabilities. Debugging and troubleshooting should be conducted in parallel.
The code should be regularly reviewed to understand its different elements like variables and objects. Regularly perform refactoring and patching for maximum return on investment.
Finally, focus on code deduplication to reduce complexity and resource wastage. These various practices will help you maximize the benefits of refactoring.
How to become a programming expert
To master computer programming and techniques like code refactoring, you can choose DataScientest. All our Data Science training programs start with a dedicated module on Python programming.
You will learn how to use the Python language and its software libraries dedicated to Data Science, such as NumPy. The other modules cover databases, Machine Learning, DataViz, and Business Intelligence.
At the end of your chosen training, you will have all the skills required to work in one of the Data Science professions, such as Data Engineer, Data Analyst, or Data Scientist.
Our training programs provide a diploma issued by Mines ParisTech PSL Executive Education or the University of Sorbonne. You can also obtain a certification recognized by the State or an industrial certification from Microsoft Azure or Amazon Web Services.
All our programs can be completed through Continuing Education, bootcamps, or apprenticeships. The entire course is done online via the internet and combines learning on a coached platform with Masterclasses.
As an organization recognized by the State, DataScientest is eligible for different state financing options; Don’t wait any longer and discover our training programs!
