Refactoring with Codemods to Automate API Modifications

Clear a Stale Function Toggle

Let’s begin with a easy but sensible instance to reveal the
energy of codemods. Think about you’re utilizing a function
toggle in your
codebase to manage the discharge of unfinished or experimental options.
As soon as the function is stay in manufacturing and dealing as anticipated, the subsequent
logical step is to wash up the toggle and any associated logic.

As an illustration, contemplate the next code:

const knowledge = featureToggle('feature-new-product-list') ? { identify: 'Product' } : undefined; 

As soon as the function is absolutely launched and now not wants a toggle, this
will be simplified to:

const knowledge = { identify: 'Product' }; 

The duty includes discovering all cases of featureToggle within the
codebase, checking whether or not the toggle refers to
feature-new-product-list, and eradicating the conditional logic surrounding
it. On the similar time, different function toggles (like
feature-search-result-refinement, which can nonetheless be in improvement)
ought to stay untouched. The codemod must perceive the construction
of the code to use modifications selectively.

Understanding the AST

Earlier than we dive into writing the codemod, let’s break down how this
particular code snippet appears to be like in an AST. You should utilize instruments like AST
Explorer to visualise how supply code and AST
are mapped. It’s useful to know the node sorts you are interacting
with earlier than making use of any modifications.

The picture under exhibits the syntax tree by way of ECMAScript syntax. It
comprises nodes like Identifier (for variables), StringLiteral (for the
toggle identify), and extra summary nodes like CallExpression and
ConditionalExpression.

Determine 2: The Summary Syntax Tree illustration of the function toggle examine

On this AST illustration, the variable knowledge is assigned utilizing a
ConditionalExpression. The take a look at a part of the expression calls
featureToggle('feature-new-product-list'). If the take a look at returns true,
the consequent department assigns { identify: 'Product' } to knowledge. If
false, the alternate department assigns undefined.

For a job with clear enter and output, I desire writing checks first,
then implementing the codemod. I begin by defining a adverse case to
guarantee we don’t by accident change issues we need to depart untouched,
adopted by an actual case that performs the precise conversion. I start with
a easy state of affairs, implement it, then add a variation (like checking if
featureToggle is named inside an if assertion), implement that case, and
guarantee all checks move.

This strategy aligns properly with Check-Pushed Improvement (TDD), even
in the event you don’t follow TDD repeatedly. Understanding precisely what the
transformation’s inputs and outputs are earlier than coding improves security and
effectivity, particularly when tweaking codemods.

With jscodeshift, you’ll be able to write checks to confirm how the codemod
behaves:

const rework = require("../remove-feature-new-product-list"); defineInlineTest(   rework,   {},   `   const knowledge = featureToggle('feature-new-product-list') ? { identify: 'Product' } : undefined;   `,   `   const knowledge = { identify: 'Product' };   `,   "delete the toggle feature-new-product-list in conditional operator" ); 

The defineInlineTest perform from jscodeshift means that you can outline
the enter, anticipated output, and a string describing the take a look at’s intent.
Now, operating the take a look at with a traditional jest command will fail as a result of the
codemod isn’t written but.

The corresponding adverse case would make sure the code stays unchanged
for different function toggles:

defineInlineTest(   rework,   {},   `   const knowledge = featureToggle('feature-search-result-refinement') ? { identify: 'Product' } : undefined;   `,   `   const knowledge = featureToggle('feature-search-result-refinement') ? { identify: 'Product' } : undefined;   `,   "don't change different function toggles" ); 

Writing the Codemod

Let’s begin by defining a easy rework perform. Create a file
known as rework.js with the next code construction:

module.exports = perform(fileInfo, api, choices) {   const j = api.jscodeshift;   const root = j(fileInfo.supply);   // manipulate the tree nodes right here   return root.toSource(); }; 

This perform reads the file right into a tree and makes use of jscodeshift’s API to
question, modify, and replace the nodes. Lastly, it converts the AST again to
supply code with .toSource().

Now we will begin implementing the rework steps:

1. Discover all cases of featureToggle.
2. Confirm that the argument handed is 'feature-new-product-list'.
3. Exchange your entire conditional expression with the consequent half,
   successfully eradicating the toggle.

Right here’s how we obtain this utilizing jscodeshift:

module.exports = perform (fileInfo, api, choices) {   const j = api.jscodeshift;   const root = j(fileInfo.supply);   // Discover ConditionalExpression the place the take a look at is featureToggle('feature-new-product-list')   root     .discover(j.ConditionalExpression, {       take a look at: {         callee: { identify: "featureToggle" },         arguments: [{ value: "feature-new-product-list" }],       },     })     .forEach((path) => {       // Exchange the ConditionalExpression with the 'consequent'       j(path).replaceWith(path.node.consequent);     });   return root.toSource(); }; 

The codemod above:

• Finds ConditionalExpression nodes the place the take a look at calls
  featureToggle('feature-new-product-list').
• Replaces your entire conditional expression with the resultant (i.e., {
identify: 'Product' }), eradicating the toggle logic and leaving simplified code
  behind.

This instance demonstrates how straightforward it’s to create a helpful
transformation and apply it to a big codebase, considerably lowering
guide effort.

You’ll want to jot down extra take a look at instances to deal with variations like
if-else statements, logical expressions (e.g.,
!featureToggle('feature-new-product-list')), and so forth to make the
codemod strong in real-world eventualities.

As soon as the codemod is prepared, you’ll be able to try it out on a goal codebase,
such because the one you are engaged on. jscodeshift gives a command-line
device that you need to use to use the codemod and report the outcomes.

$ jscodeshift -t transform-name src/ 

After validating the outcomes, examine that each one useful checks nonetheless
move and that nothing breaks—even in the event you’re introducing a breaking change.
As soon as glad, you’ll be able to commit the modifications and lift a pull request as
a part of your regular workflow.

Codemods Enhance Code High quality and Maintainability

Codemods aren’t simply helpful for managing breaking API modifications—they’ll
considerably enhance code high quality and maintainability. As codebases
evolve, they typically accumulate technical debt, together with outdated function
toggles, deprecated strategies, or tightly coupled elements. Manually
refactoring these areas will be time-consuming and error-prone.

By automating refactoring duties, codemods assist maintain your codebase clear
and freed from legacy patterns. Frequently making use of codemods means that you can
implement new coding requirements, take away unused code, and modernize your
codebase with out having to manually modify each file.

Refactoring an Avatar Element

Now, let’s have a look at a extra complicated instance. Suppose you’re working with
a design system that features an Avatar element tightly coupled with a
Tooltip. Every time a consumer passes a identify prop into the Avatar, it
routinely wraps the avatar with a tooltip.

Determine 3: A avatar element with a tooltip

Right here’s the present Avatar implementation:

import { Tooltip } from "@design-system/tooltip"; const Avatar = ({ identify, picture }: AvatarProps) => {   if (identify) {     return (                            );   }   return ; }; 

The purpose is to decouple the Tooltip from the Avatar element,
giving builders extra flexibility. Builders ought to be capable to resolve
whether or not to wrap the Avatar in a Tooltip. Within the refactored model,
Avatar will merely render the picture, and customers can apply a Tooltip
manually if wanted.

Right here’s the refactored model of Avatar:

const Avatar = ({ picture }: AvatarProps) => {   return ; }; 

Now, customers can manually wrap the Avatar with a Tooltip as
wanted:

import { Tooltip } from "@design-system/tooltip"; import { Avatar } from "@design-system/avatar"; const UserProfile = () => {   return (                    ); }; 

The problem arises when there are tons of of Avatar usages unfold
throughout the codebase. Manually refactoring every occasion could be extremely
inefficient, so we will use a codemod to automate this course of.

Utilizing instruments like AST Explorer, we will
examine the element and see which nodes symbolize the Avatar utilization
we’re focusing on. An Avatar element with each identify and picture props
is parsed into an summary syntax tree as proven under:

Determine 4: AST of the Avatar element utilization

Writing the Codemod

Let’s break down the transformation into smaller duties:

• Discover Avatar utilization within the element tree.
• Test if the identify prop is current.
• If not, do nothing.
• If current:
• Create a Tooltip node.
• Add the identify to the Tooltip.
• Take away the identify from Avatar.
• Add Avatar as a baby of the Tooltip.
• Exchange the unique Avatar node with the brand new Tooltip.

To start, we’ll discover all cases of Avatar (I’ll omit among the
checks, however it is best to write comparability checks first).

defineInlineTest(     { default: rework, parser: "tsx" },     {},     `          `,     `                      `,     "wrap avatar with tooltip when identify is offered"   ); 

Much like the featureToggle instance, we will use root.discover with
search standards to find all Avatar nodes:

root   .discover(j.JSXElement, {     openingElement: { identify: { identify: "Avatar" } },   })   .forEach((path) => {     // now we will deal with every Avatar occasion   }); 

Subsequent, we examine if the identify prop is current:

root   .discover(j.JSXElement, {     openingElement: { identify: { identify: "Avatar" } },   })   .forEach((path) => {     const avatarNode = path.node;     const nameAttr = avatarNode.openingElement.attributes.discover(       (attr) => attr.identify.identify === "identify"     );     if (nameAttr) {       const tooltipElement = createTooltipElement(         nameAttr.worth.worth,         avatarNode       );       j(path).replaceWith(tooltipElement);     }   }); 

For the createTooltipElement perform, we use the
jscodeshift API to create a brand new JSX node, with the identify
prop utilized to the Tooltip and the Avatar
element as a baby. Lastly, we name replaceWith to
exchange the present path.

Right here’s a preview of the way it appears to be like in
Hypermod, the place the codemod is written on
the left. The highest half on the best is the unique code, and the underside
half is the remodeled outcome:

Determine 5: Run checks inside hypermod earlier than apply it to your codebase

This codemod searches for all cases of Avatar. If a
identify prop is discovered, it removes the identify prop
from Avatar, wraps the Avatar inside a
Tooltip, and passes the identify prop to the
Tooltip.

By now, I hope it’s clear that codemods are extremely helpful and
that the workflow is intuitive, particularly for large-scale modifications the place
guide updates could be an enormous burden. Nonetheless, that is not the entire
image. Within the subsequent part, I’ll make clear among the challenges
and the way we will deal with these less-than-ideal features.

Leveraging Supply Graphs and Check-Pushed Codemods

To deal with these complexities, codemods needs to be used alongside different
methods. As an illustration, a couple of years in the past, I participated in a design
system elements rewrite challenge at Atlassian. We addressed this problem by
first looking the supply graph, which contained nearly all of inside
element utilization. This allowed us to know how elements have been used,
whether or not they have been imported beneath completely different names, or whether or not sure
public props have been regularly used. After this search part, we wrote our
take a look at instances upfront, guaranteeing we lined nearly all of use instances, and
then developed the codemod.

In conditions the place we could not confidently automate the improve, we
inserted feedback or “TODOs” on the name websites. This allowed the
builders operating the script to deal with particular instances manually. Often,
there have been solely a handful of such cases, so this strategy nonetheless proved
useful for upgrading variations.

Using Current Code Standardization Instruments

As you’ll be able to see, there are many edge instances to deal with, particularly in
codebases past your management—equivalent to exterior dependencies. This
complexity signifies that utilizing codemods requires cautious supervision and a
evaluation of the outcomes.

Nonetheless, in case your codebase has standardization instruments in place, equivalent to a
linter that enforces a specific coding model, you’ll be able to leverage these
instruments to cut back edge instances. By imposing a constant construction, instruments
like linters assist slender down the variations in code, making the
transformation simpler and minimizing sudden points.

As an illustration, you might use linting guidelines to limit sure patterns,
equivalent to avoiding nested conditional (ternary) operators or imposing named
exports over default exports. These guidelines assist streamline the codebase,
making codemods extra predictable and efficient.

Moreover, breaking down complicated transformations into smaller, extra
manageable ones means that you can sort out particular person points extra exactly. As
we’ll quickly see, composing smaller codemods could make dealing with complicated
modifications extra possible.

Codemod Composition

Let’s revisit the function toggle removing instance mentioned earlier. Within the code snippet
we now have a toggle known as feature-convert-new have to be eliminated:

import { featureToggle } from "./utils/featureToggle"; const convertOld = (enter: string) => {   return enter.toLowerCase(); }; const convertNew = (enter: string) => {   return enter.toUpperCase(); }; const outcome = featureToggle("feature-convert-new")   ? convertNew("Whats up, world")   : convertOld("Whats up, world"); console.log(outcome); 

The codemod for take away a given toggle works wonderful, and after operating the codemod,
we would like the supply to appear to be this:

const convertNew = (enter: string) => {   return enter.toUpperCase(); }; const outcome = convertNew("Whats up, world"); console.log(outcome); 

Nonetheless, past eradicating the function toggle logic, there are further duties to
deal with:

• Take away the unused convertOld perform.
• Clear up the unused featureToggle import.

In fact, you might write one large codemod to deal with all the pieces in a
single move and take a look at it collectively. Nonetheless, a extra maintainable strategy is
to deal with codemod logic like product code: break the duty into smaller,
impartial items—similar to how you’d usually refactor manufacturing
code.

Breaking It Down

We will break the large transformation down into smaller codemods and
compose them. The benefit of this strategy is that every transformation
will be examined individually, masking completely different instances with out interference.
Furthermore, it means that you can reuse and compose them for various
functions.

As an illustration, you may break it down like this:

• A metamorphosis to take away a selected function toggle.
• One other transformation to wash up unused imports.
• A metamorphosis to take away unused perform declarations.

By composing these, you’ll be able to create a pipeline of transformations:

import { removeFeatureToggle } from "./remove-feature-toggle"; import { removeUnusedImport } from "./remove-unused-import"; import { removeUnusedFunction } from "./remove-unused-function"; import { createTransformer } from "./utils"; const removeFeatureConvertNew = removeFeatureToggle("feature-convert-new"); const rework = createTransformer([   removeFeatureConvertNew,   removeUnusedImport,   removeUnusedFunction, ]); export default rework; 

On this pipeline, the transformations work as follows:

1. Take away the feature-convert-new toggle.
2. Clear up the unused import assertion.
3. Take away the convertOld perform because it’s now not used.

Determine 6: Compose transforms into a brand new rework

You may also extract further codemods as wanted, combining them in
varied orders relying on the specified final result.

Determine 7: Put completely different transforms right into a pipepline to kind one other rework

The createTransformer Operate

The implementation of the createTransformer perform is comparatively
simple. It acts as a higher-order perform that takes an inventory of
smaller rework capabilities, iterates via the record to use them to
the foundation AST, and at last converts the modified AST again into supply
code.

import { API, Assortment, FileInfo, JSCodeshift, Choices } from "jscodeshift"; sort TransformFunction = { (j: JSCodeshift, root: Assortment): void }; const createTransformer =   (transforms: TransformFunction[]) =>   (fileInfo: FileInfo, api: API, choices: Choices) => {     const j = api.jscodeshift;     const root = j(fileInfo.supply);     transforms.forEach((rework) => rework(j, root));     return root.toSource(choices.printOptions || { quote: "single" });   }; export { createTransformer }; 

For instance, you might have a rework perform that inlines
expressions assigning the function toggle name to a variable, so in later
transforms you don’t have to fret about these instances anymore:

const shouldEnableNewFeature = featureToggle('feature-convert-new'); if (!shouldEnableNewFeature && someOtherLogic) {   //... } 

Turns into this:

if (!featureToggle('feature-convert-new') && someOtherLogic) {   //... } 

Over time, you may construct up a group of reusable, smaller
transforms, which may significantly ease the method of dealing with tough edge
instances. This strategy proved extremely efficient in our work refining design
system elements. As soon as we transformed one bundle—such because the button
element—we had a couple of reusable transforms outlined, like including feedback
initially of capabilities, eradicating deprecated props, or creating aliases
when a bundle is already imported above.

Every of those smaller transforms will be examined and used independently
or mixed for extra complicated transformations, which hastens subsequent
conversions considerably. Because of this, our refinement work grew to become extra
environment friendly, and these generic codemods at the moment are relevant to different inside
and even exterior React codebases.

Since every rework is comparatively standalone, you’ll be able to fine-tune them
with out affecting different transforms or the extra complicated, composed ones. For
occasion, you may re-implement a rework to enhance efficiency—like
lowering the variety of node-finding rounds—and with complete take a look at
protection, you are able to do this confidently and safely.

Utilizing JavaParser in a Java Codebase

JavaParser will be helpful for making breaking API modifications or refactoring
giant Java codebases in a structured, automated method.

Assume we now have the next code in FeatureToggleExample.java, which
checks the toggle feature-convert-new and branches accordingly:

public class FeatureToggleExample {     public void execute() {         if (FeatureToggle.isEnabled("feature-convert-new")) {           newFeature();         } else {           oldFeature();         }     }     void newFeature() {         System.out.println("New Function Enabled");     }     void oldFeature() {         System.out.println("Previous Function");     } }

We will outline a customer to search out if statements checking for
FeatureToggle.isEnabled, after which exchange them with the corresponding
true department—just like how we dealt with the function toggle codemod in
JavaScript.

// Customer to take away function toggles class FeatureToggleVisitor extends VoidVisitorAdapter {     @Override     public void go to(IfStmt ifStmt, Void arg) {         tremendous.go to(ifStmt, arg);         if (ifStmt.getCondition().isMethodCallExpr()) {             MethodCallExpr methodCall = ifStmt.getCondition().asMethodCallExpr();             if (methodCall.getNameAsString().equals("isEnabled") &&                 methodCall.getScope().isPresent() &&                 methodCall.getScope().get().toString().equals("FeatureToggle")) {                 BlockStmt thenBlock = ifStmt.getThenStmt().asBlockStmt();                 ifStmt.exchange(thenBlock);             }         }     } } 

This code defines a customer sample utilizing
JavaParser to traverse and manipulate the AST. The
FeatureToggleVisitor appears to be like for if statements
that decision FeatureToggle.isEnabled() and replaces your entire
if assertion with the true department.

You may also outline guests to search out unused strategies and take away
them:

class UnusedMethodRemover extends VoidVisitorAdapter {     personal Set calledMethods = new HashSet();     personal Listing methodsToRemove = new ArrayList();     // Gather all known as strategies     @Override     public void go to(MethodCallExpr n, Void arg) {         tremendous.go to(n, arg);         calledMethods.add(n.getNameAsString());     }     // Gather strategies to take away if not known as     @Override     public void go to(MethodDeclaration n, Void arg) {         tremendous.go to(n, arg);         String methodName = n.getNameAsString();         if (!calledMethods.comprises(methodName) && !methodName.equals("fundamental")) {             methodsToRemove.add(n);         }     }     // After visiting, take away the unused strategies     public void removeUnusedMethods() {         for (MethodDeclaration technique : methodsToRemove) {             technique.take away();         }     } } 

This code defines a customer, UnusedMethodRemover, to detect and
take away unused strategies. It tracks all known as strategies within the calledMethods
set and checks every technique declaration. If a way isn’t known as and isn’t
fundamental, it provides it to the record of strategies to take away. As soon as all strategies are
processed, it removes any unused strategies from the AST.

Composing Java Guests

You possibly can chain these guests collectively and apply them to your codebase
like so:

public class FeatureToggleRemoverWithCleanup {     public static void fundamental(String[] args) {         strive {             String filePath = "src/take a look at/java/com/instance/Instance.java";             CompilationUnit cu = StaticJavaParser.parse(new FileInputStream(filePath));             // Apply transformations             FeatureToggleVisitor toggleVisitor = new FeatureToggleVisitor();             cu.settle for(toggleVisitor, null);             UnusedMethodRemover remover = new UnusedMethodRemover();             cu.settle for(remover, null);             remover.removeUnusedMethods();             // Write the modified code again to the file             strive (FileOutputStream fos = new FileOutputStream(filePath)) {                 fos.write(cu.toString().getBytes());             }             System.out.println("Code transformation accomplished efficiently.");         } catch (IOException e) {             e.printStackTrace();         }     } } 

Every customer is a unit of transformation, and the customer sample in
JavaParser makes it straightforward to compose them.

Variations Between OpenRewrite and JavaParser or jscodeshift

The important thing distinction between OpenRewrite and instruments like JavaParser or
jscodeshift lies of their strategy to code transformation:

• OpenRewrite’s Lossless Semantic Bushes (LSTs) seize each the
  syntactic and semantic that means of the code, enabling extra correct
  transformations.
• JavaParser and jscodeshift depend on conventional ASTs, which focus
  totally on the syntactic construction. Whereas highly effective, they could not all the time
  seize the nuances of how the code behaves semantically.

Moreover, OpenRewrite affords a big library of community-driven
refactoring recipes, making it simpler to use widespread transformations with out
needing to jot down customized codemods from scratch.

Hypermod

Hypermod introduces AI help to the codemod writing course of.
As a substitute of manually crafting the codemod logic, builders can describe
the specified transformation in plain English, and Hypermod will generate
the codemod utilizing jscodeshift. This makes codemod creation extra
accessible, even for builders who is probably not aware of AST
manipulation.

You possibly can compose, take a look at, and deploy a codemod to any repository
linked to Hypermod. It might run the codemod and generate a pull
request with the proposed modifications, permitting you to evaluation and approve
them. This integration makes your entire course of from codemod improvement
to deployment far more streamlined.

Codemod.com

Codemod.com is a community-driven platform the place builders
can share and uncover codemods. Should you want a selected codemod for a
widespread refactoring job or migration, you’ll be able to seek for present
codemods. Alternatively, you’ll be able to publish codemods you’ve created to assist
others within the developer neighborhood.

Should you’re migrating an API and want a codemod to deal with it,
Codemod.com can prevent time by providing pre-built codemods for
many widespread transformations, lowering the necessity to write one from
scratch.