GitHub Copilot for Code Refactoring - Part 2

Introduction

Hello all, welcome to a new episode of GitHub Copilot. In today's episode, we are looking at refactoring approaches. In one of the previous episodes, we covered some of the areas of refactoring. There are a number of approaches, and we covered some in today's demo. We will be covering how we can use refactoring of the code with the help of Copilot, following patterns like the guard clause, decompose method, and consolidation. We'll also look at the bumpy road code complexity pattern where code goes into ups and downs, adding maintainability issues. By the end, if we know the refactoring approach, it's very easy to convert the code into a particular format. We will also see how GitHub Copilot can help us identify the corresponding approach.

So, without further ado, let's go directly into the demo. I will be showing the demo using JavaScript today.

Guard Clause

Starting with the first example - get payment amount. There are multiple else conditions, which can be optimized with a proper refactoring approach. The concern here is, even though the result gets the amount here itself, the system will execute until the return comes. Hence, there is no need for the system to wait till the return if the result is available.

Using the guard pattern here for refactoring, I used Copilot to optimize my code using the guard pattern or guard clause. I expected it to return early instead of waiting for all conditions to complete.

Decomposing Method

The second approach is decomposing. By decomposing the code into multiple levels, we can improve readability. Multiple conditions in an if statement or detailed expressions take time to understand. We can decompose these conditions and calculations for better readability.

Consolidation

Next, we have the check employees method. It's a simple method with repetitive condition checks returning the same value. We can consolidate these conditions. Consolidating multiple conditions or nested conditions makes the code more readable and maintainable.

Error Handling

Another example is optimizing error codes. Returning explicit error codes like -23 may not be as clear for maintenance. Replacing error codes with exception handling refactors the code for better readability.

Pre-checks

For exception handling in file management, replacing file not found exceptions with a pre-check improves the reliability. By ensuring the file exists before proceeding, exceptions can be minimized.

Pipeline Refactoring

For conditional loops, refactoring using a pipeline improves performance. Instead of looping through a list conditionally, the filter and map functions make the code efficient and concise.

Substitute Algorithm

For nested loops checking multiple values, we can use a substitute algorithm. This involves converting the values into arrays and performing a one-time check using array methods.

Maintainability

Maintainable code requires future-proofing changes, like using constants instead of hard-coded values. By defining constants and using them in calculations, we enhance code maintainability.

Bumpy Road Pattern

The bumpy road pattern refers to code with multiple if loops in multiple levels, adding complexity. Copilot can help identify and fix this by breaking the function into multiple methods, simplifying the structure.

Identifying Refactoring Patterns

Sometimes, identifying the refactoring pattern may be challenging. Copilot can suggest suitable refactoring approaches. If a senior developer suggests a method, Copilot can help refactor the code accordingly.

Keywords

• GitHub Copilot
• Code Refactoring
• Guard Clause
• Decomposing Method
• Consolidation
• Error Handling
• Pre-checks
• Pipeline Refactoring
• Substitute Algorithm
• Maintainability
• Bumpy Road Pattern

FAQ

Q: What is a guard clause? A: A guard clause is a refactoring pattern that returns early from a method or function if a certain condition is met, thus avoiding unnecessary processing.

Q: How does decomposing a method help in readability? A: Decomposing a method into smaller, well-defined functions makes the code more readable and easier to maintain.

Q: When should I use consolidation in refactoring? A: Use consolidation when you have repetitive conditional checks that can be combined into a single condition for better readability and maintenance.

Q: What is the benefit of replacing error codes with exception handling? A: Exception handling is explicit and makes it clear when an error occurs, improving code readability and maintainability.

Q: Why should I use pre-checks instead of exceptions? A: Pre-checks prevent exceptions by handling possible error conditions before they lead to exceptions, making the code more robust.

Q: How can pipelines refactor conditional loops? A: Pipelines like filter and map functions can replace loops with conditions, making the code more efficient and easier to understand.

Q: What is a substitute algorithm in the context of refactoring? A: A substitute algorithm replaces nested loops and multiple value checks with more efficient data structures and methods, like arrays and array methods.

Q: How can I improve code maintainability? A: Use constants for values instead of hard-coding them, ensure clear and well-defined function separations, and handle exceptions appropriately.

Q: What is the bumpy road pattern? A: The bumpy road pattern describes code that has excessive nested if loops, making it complex and hard to maintain.

Q: How can GitHub Copilot help in identifying refactoring patterns? A: Copilot can suggest suitable refactoring approaches for your code, making the refactoring process easier even if you are not sure which pattern to use.