Refactoring with Codemods to Automate API Adjustments

Clear a Stale Characteristic Toggle

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

As an example, contemplate the next code:

const information = featureToggle('feature-new-product-list') ?  title: 'Product'  : undefined;

As soon as the characteristic is totally launched and not wants a toggle, this
could be simplified to:

const information =  title: 'Product' ;

The duty entails discovering all situations 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 identical time, different characteristic 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 adjustments 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 varieties you are interacting
with earlier than making use of any adjustments.

The picture beneath exhibits the syntax tree when it comes to ECMAScript syntax. It
accommodates nodes like Identifier (for variables), StringLiteral (for the
toggle title), and extra summary nodes like CallExpression and
ConditionalExpression.

Determine 2: The Summary Syntax Tree illustration of the characteristic toggle test

On this AST illustration, the variable information 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 title: 'Product' to information. If
false, the alternate department assigns undefined.

For a process with clear enter and output, I favor writing assessments first,
then implementing the codemod. I begin by defining a unfavorable case to
guarantee we don’t unintentionally change issues we wish 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 known as inside an if assertion), implement that case, and
guarantee all assessments go.

This method aligns effectively with Check-Pushed Improvement (TDD), even
when you don’t follow TDD recurrently. Realizing precisely what the
transformation’s inputs and outputs are earlier than coding improves security and
effectivity, particularly when tweaking codemods.

With jscodeshift, you possibly can write assessments to confirm how the codemod
behaves:

const rework = require("../remove-feature-new-product-list");

defineInlineTest(
  rework,
  ,
  `
  const information = featureToggle('feature-new-product-list') ?  title: 'Product'  : undefined;
  `,
  `
  const information =  title: 'Product' ;
  `,
  "delete the toggle feature-new-product-list in conditional operator"
);

The defineInlineTest perform from jscodeshift permits you to 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 standard jest command will fail as a result of the
codemod isn’t written but.

The corresponding unfavorable case would make sure the code stays unchanged
for different characteristic toggles:

defineInlineTest(
  rework,
  ,
  `
  const information = featureToggle('feature-search-result-refinement') ?  title: 'Product'  : undefined;
  `,
  `
  const information = featureToggle('feature-search-result-refinement') ?  title: 'Product'  : undefined;
  `,
  "don't change different characteristic toggles"
);

Writing the Codemod

Let’s begin by defining a easy rework perform. Create a file
referred to 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 are able to begin implementing the rework steps:

1. Discover all situations of featureToggle.
2. Confirm that the argument handed is 'feature-new-product-list'.
3. Substitute the whole 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:  title: "featureToggle" ,
        arguments: [ value: "feature-new-product-list" ],
      ,
    )
    .forEach((path) => 
      // Substitute 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 the whole conditional expression with the ensuing (i.e.,
title: 'Product' ), eradicating the toggle logic and leaving simplified code
  behind.

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

You’ll want to put in writing 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 possibly can check it out on a goal codebase,
such because the one you are engaged on. jscodeshift supplies a command-line
device that you should utilize to use the codemod and report the outcomes.

$ jscodeshift -t transform-name src/

After validating the outcomes, test that each one practical assessments nonetheless
go and that nothing breaks—even when you’re introducing a breaking change.
As soon as happy, you possibly can commit the adjustments 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 adjustments—they will
considerably enhance code high quality and maintainability. As codebases
evolve, they usually accumulate technical debt, together with outdated characteristic
toggles, deprecated strategies, or tightly coupled parts. Manually
refactoring these areas could be time-consuming and error-prone.

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

Refactoring an Avatar Part

Now, let’s have a look at a extra advanced instance. Suppose you’re working with
a design system that features an Avatar part tightly coupled with a
Tooltip. Every time a person passes a title prop into the Avatar, it
robotically wraps the avatar with a tooltip.

Determine 3: A avatar part with a tooltip

Right here’s the present Avatar implementation:

import  Tooltip  from "@design-system/tooltip";

const Avatar = ( title, picture : AvatarProps) => 
  if (title) 
    return (
      <Tooltip content material=title>
        <CircleImage picture=picture />
      </Tooltip>
    );
  

  return <CircleImage picture=picture />;
;

The purpose is to decouple the Tooltip from the Avatar part,
giving builders extra flexibility. Builders ought to be capable of 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 <CircleImage picture=picture />;
;

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 (
    <Tooltip content material="Juntao Qiu">
      <Avatar picture="/juntao.qiu.avatar.png" />
    </Tooltip>
  );
;

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

Utilizing instruments like AST Explorer, we are able to
examine the part and see which nodes characterize the Avatar utilization
we’re focusing on. An Avatar part with each title and picture props
is parsed into an summary syntax tree as proven beneath:

Determine 4: AST of the Avatar part utilization

Writing the Codemod

Let’s break down the transformation into smaller duties:

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

To start, we’ll discover all situations of Avatar (I’ll omit a number of the
assessments, however you need to write comparability assessments first).

defineInlineTest(
     default: rework, parser: "tsx" ,
    ,
    `
    <Avatar title="Juntao Qiu" picture="/juntao.qiu.avatar.png" />
    `,
    `
    <Tooltip content material="Juntao Qiu">
      <Avatar picture="/juntao.qiu.avatar.png" />
    </Tooltip>
    `,
    "wrap avatar with tooltip when title is supplied"
  );

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

root
  .discover(j.JSXElement, 
    openingElement:  title:  title: "Avatar"  ,
  )
  .forEach((path) => 
    // now we are able to deal with every Avatar occasion
  );

Subsequent, we test if the title prop is current:

root
  .discover(j.JSXElement, 
    openingElement:  title:  title: "Avatar"  ,
  )
  .forEach((path) => 
    const avatarNode = path.node;

    const nameAttr = avatarNode.openingElement.attributes.discover(
      (attr) => attr.title.title === "title"
    );

    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 title
prop utilized to the Tooltip and the Avatar
part 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 situations of Avatar. If a
title prop is discovered, it removes the title prop
from Avatar, wraps the Avatar inside a
Tooltip, and passes the title 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 adjustments the place
guide updates could be an enormous burden. Nevertheless, that is not the entire
image. Within the subsequent part, I’ll make clear a number of the challenges
and the way we are able to tackle these less-than-ideal features.

Leveraging Supply Graphs and Check-Pushed Codemods

To deal with these complexities, codemods needs to be used alongside different
strategies. As an example, just a few years in the past, I participated in a design
system parts rewrite mission at Atlassian. We addressed this problem by
first looking the supply graph, which contained nearly all of inner
part utilization. This allowed us to know how parts had been used,
whether or not they had been imported below totally different names, or whether or not sure
public props had been regularly used. After this search part, we wrote our
take a look at instances upfront, guaranteeing we coated 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 situations, so this method nonetheless proved
useful for upgrading variations.

Using Present Code Standardization Instruments

As you possibly can see, there are many edge instances to deal with, particularly in
codebases past your management—corresponding to exterior dependencies. This
complexity signifies that utilizing codemods requires cautious supervision and a
overview of the outcomes.

Nevertheless, in case your codebase has standardization instruments in place, corresponding to a
linter that enforces a specific coding type, you possibly can leverage these
instruments to scale back edge instances. By imposing a constant construction, instruments
like linters assist slim down the variations in code, making the
transformation simpler and minimizing sudden points.

As an example, you might use linting guidelines to limit sure patterns,
corresponding 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 advanced transformations into smaller, extra
manageable ones permits you to sort out particular person points extra exactly. As
we’ll quickly see, composing smaller codemods could make dealing with advanced
adjustments extra possible.

Codemod Composition

Let’s revisit the characteristic toggle elimination instance mentioned earlier. Within the code snippet
now we have a toggle referred to 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 superb, 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);

Nevertheless, past eradicating the characteristic toggle logic, there are extra 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 the whole lot in a
single go and take a look at it collectively. Nevertheless, a extra maintainable method is
to deal with codemod logic like product code: break the duty into smaller,
impartial items—similar to how you’ll usually refactor manufacturing
code.

Breaking It Down

We are able to break the large transformation down into smaller codemods and
compose them. The benefit of this method is that every transformation
could be examined individually, masking totally different instances with out interference.
Furthermore, it permits you to reuse and compose them for various
functions.

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

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

By composing these, you possibly can 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 not used.

Determine 6: Compose transforms into a brand new rework

It’s also possible to extract extra codemods as wanted, combining them in
varied orders relying on the specified consequence.

Determine 7: Put totally 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 a listing of
smaller rework features, iterates by means of the checklist 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) => ;

export  createTransformer ;

For instance, you might have a rework perform that inlines
expressions assigning the characteristic 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 set of reusable, smaller
transforms, which may tremendously ease the method of dealing with tough edge
instances. This method proved extremely efficient in our work refining design
system parts. As soon as we transformed one package deal—such because the button
part—we had just a few reusable transforms outlined, like including feedback
firstly of features, eradicating deprecated props, or creating aliases
when a package deal is already imported above.

Every of those smaller transforms could be examined and used independently
or mixed for extra advanced transformations, which quickens subsequent
conversions considerably. In consequence, our refinement work grew to become extra
environment friendly, and these generic codemods are actually relevant to different inner
and even exterior React codebases.

Since every rework is comparatively standalone, you possibly can fine-tune them
with out affecting different transforms or the extra advanced, composed ones. For
occasion, you may re-implement a rework to enhance efficiency—like
decreasing 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 could be helpful for making breaking API adjustments or refactoring
massive Java codebases in a structured, automated approach.

Assume now we 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 Characteristic Enabled");
    

    void oldFeature() 
        System.out.println("Previous Characteristic");
    

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

// Customer to take away characteristic toggles
class FeatureToggleVisitor extends VoidVisitorAdapter<Void> 
    @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 the whole
if assertion with the true department.

It’s also possible to outline guests to search out unused strategies and take away
them:

class UnusedMethodRemover extends VoidVisitorAdapter<Void> 
    personal Set<String> calledMethods = new HashSet<>();
    personal Record<MethodDeclaration> methodsToRemove = new ArrayList<>();

    // Acquire all referred to as strategies
    @Override
    public void go to(MethodCallExpr n, Void arg) 
        tremendous.go to(n, arg);
        calledMethods.add(n.getNameAsString());
    

    // Acquire strategies to take away if not referred to as
    @Override
    public void go to(MethodDeclaration n, Void arg) 
        tremendous.go to(n, arg);
        String methodName = n.getNameAsString();
        if (!calledMethods.accommodates(methodName) && !methodName.equals("major")) 
            methodsToRemove.add(n);
        
    

    // After visiting, take away the unused strategies
    public void removeUnusedMethods() 
        for (MethodDeclaration methodology : methodsToRemove) 
            methodology.take away();
        
    

This code defines a customer, UnusedMethodRemover, to detect and
take away unused strategies. It tracks all referred to as strategies within the calledMethods
set and checks every methodology declaration. If a technique isn’t referred to as and isn’t
major, it provides it to the checklist 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 major(String[] args) 
        attempt 
            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
            attempt (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 simple 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 method to code transformation:

• OpenRewrite’s Lossless Semantic Bushes (LSTs) seize each the
  syntactic and semantic which 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 might not at all times
  seize the nuances of how the code behaves semantically.

Moreover, OpenRewrite gives a big library of community-driven
refactoring recipes, making it simpler to use widespread transformations with out
needing to put in writing customized codemods from scratch.

Hypermod

Hypermod introduces AI help to the codemod writing course of.
As an alternative 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 will not be accustomed to AST
manipulation.

You possibly can compose, take a look at, and deploy a codemod to any repository
linked to Hypermod. It will probably run the codemod and generate a pull
request with the proposed adjustments, permitting you to overview and approve
them. This integration makes the whole course of from codemod improvement
to deployment way more streamlined.

Codemod.com

Codemod.com is a community-driven platform the place builders
can share and uncover codemods. In the event you want a selected codemod for a
widespread refactoring process or migration, you possibly can seek for current
codemods. Alternatively, you possibly can publish codemods you’ve created to assist
others within the developer neighborhood.

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