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 regulate the discharge of unfinished or experimental options.
As soon as the function is reside in manufacturing and dealing as anticipated, the following
logical step is to scrub up the toggle and any associated logic.

As an example, take into account the next code:

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

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

const information = { title: 'Product' };

The duty entails 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 growth)
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 seems to be in an AST. You need to use instruments like AST
Explorer to visualise how supply code and AST
are mapped. It’s useful to grasp the node varieties you are interacting
with earlier than making use of any modifications.

The picture beneath exhibits the syntax tree when it comes to ECMAScript syntax. It
comprises 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 function 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 want writing assessments first,
then implementing the codemod. I begin by defining a unfavourable case to
guarantee we don’t by chance change issues we need to depart untouched,
adopted by an actual case that performs the precise conversion. I start with
a easy situation, implement it, then add a variation (like checking if
featureToggle known as inside an if assertion), implement that case, and
guarantee all assessments cross.

This strategy aligns nicely with Check-Pushed Growth (TDD), even
for those who don’t observe TDD frequently. Figuring out 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 assessments to confirm how the codemod
behaves:

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

defineInlineTest(
  remodel,
  {},
  `
  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 operate 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 standard jest command will fail as a result of the
codemod isn’t written but.

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

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

Writing the Codemod

Let’s begin by defining a easy remodel operate. Create a file
referred to as remodel.js with the next code construction:

module.exports = operate(fileInfo, api, choices) {
  const j = api.jscodeshift;
  const root = j(fileInfo.supply);

  // manipulate the tree nodes right here

  return root.toSource();
};

This operate 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 remodel steps:

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

Right here’s how we obtain this utilizing jscodeshift:

module.exports = operate (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) => {
      // Change 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 all the 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 lowering
handbook effort.

You’ll want to write 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 sturdy in real-world situations.

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

$ jscodeshift -t transform-name src/

After validating the outcomes, test that every one useful assessments nonetheless
cross and that nothing breaks—even for those who’re introducing a breaking change.
As soon as happy, 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 usually accumulate technical debt, together with outdated function
toggles, deprecated strategies, or tightly coupled elements. Manually
refactoring these areas might be time-consuming and error-prone.

By automating refactoring duties, codemods assist maintain your codebase clear
and freed from legacy patterns. Commonly 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 part tightly coupled with a
Tooltip. Each 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 (
      
        
      
    );
  }

  return ;
};

The purpose is to decouple the Tooltip from the Avatar part,
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 a whole lot of Avatar usages unfold
throughout the codebase. Manually refactoring every occasion can be extremely
inefficient, so we will use a codemod to automate this course of.

Utilizing instruments like AST Explorer, we will
examine the part and see which nodes symbolize 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.
• Test 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.
• Change the unique Avatar node with the brand new Tooltip.

To start, we’ll discover all cases of Avatar (I’ll omit a few of the
assessments, however you must write comparability assessments first).

defineInlineTest(
    { default: remodel, parser: "tsx" },
    {},
    `
    
    `,
    `
    
      
    
    `,
    "wrap avatar with tooltip when title is supplied"
  );

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

root
  .discover(j.JSXElement, {
    openingElement: { title: { title: "Avatar" } },
  })
  .forEach((path) => {
    // now we will 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 operate, 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
substitute the present path.

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

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

This codemod searches for all cases 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 modifications the place
handbook updates can be an enormous burden. Nevertheless, that is not the entire
image. Within the subsequent part, I’ll make clear a few of the challenges
and the way we will handle these less-than-ideal points.

Leveraging Supply Graphs and Check-Pushed Codemods

To deal with these complexities, codemods must be used alongside different
strategies. As an example, a couple of years in the past, I participated in a design
system elements rewrite mission at Atlassian. We addressed this difficulty by
first looking the supply graph, which contained nearly all of inner
part utilization. This allowed us to grasp how elements have been used,
whether or not they have been imported underneath completely different names, or whether or not sure
public props have been continuously used. After this search part, we wrote our
take a look at instances upfront, making certain 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 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
evaluate of the outcomes.

Nevertheless, in case your codebase has standardization instruments in place, equivalent to a
linter that enforces a selected coding model, you’ll be able to 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 surprising points.

As an example, you would 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’ve a toggle referred to as feature-convert-new should be eliminated:

import { featureToggle } from "./utils/featureToggle";

const convertOld = (enter: string) => {
  return enter.toLowerCase();
};

const convertNew = (enter: string) => {
  return enter.toUpperCase();
};

const consequence = featureToggle("feature-convert-new")
  ? convertNew("Hey, world")
  : convertOld("Hey, world");

console.log(consequence);

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

const convertNew = (enter: string) => {
  return enter.toUpperCase();
};

const consequence = convertNew("Hey, world");

console.log(consequence);

Nevertheless, past eradicating the function toggle logic, there are extra duties to
deal with:

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

In fact, you would write one large codemod to deal with every little thing in a
single cross and take a look at it collectively. Nevertheless, a extra maintainable strategy is
to deal with codemod logic like product code: break the duty into smaller,
impartial items—identical to how you’d usually refactor manufacturing
code.

Breaking It Down

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

As an example, you would possibly break it down like this:

• A metamorphosis to take away a selected function toggle.
• One other transformation to scrub up unused imports.
• A metamorphosis to take away unused operate 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 remodel = createTransformer([
  removeFeatureConvertNew,
  removeUnusedImport,
  removeUnusedFunction,
]);

export default remodel;

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 operate because it’s now not used.

Determine 6: Compose transforms into a brand new remodel

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

Determine 7: Put completely different transforms right into a pipepline to type one other remodel

The createTransformer Perform

The implementation of the createTransformer operate is comparatively
simple. It acts as a higher-order operate that takes a listing of
smaller remodel features, iterates by means of the listing to use them to
the foundation AST, and eventually 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((remodel) => remodel(j, root));
    return root.toSource(choices.printOptions || { quote: "single" });
  };

export { createTransformer };

For instance, you would have a remodel operate 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 would possibly construct up a set of reusable, smaller
transforms, which may significantly ease the method of dealing with difficult 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
part—we had a couple of reusable transforms outlined, like including feedback
initially of features, eradicating deprecated props, or creating aliases
when a bundle is already imported above.

Every of those smaller transforms might be examined and used independently
or mixed for extra complicated transformations, which hurries up subsequent
conversions considerably. Consequently, 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 remodel 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 would possibly re-implement a remodel 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 might be helpful for making breaking API modifications or refactoring
giant Java codebases in a structured, automated manner.

Assume we’ve 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("Outdated Function");
    }
}

We are able to outline a customer to seek out if statements checking for
FeatureToggle.isEnabled, after which substitute 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.substitute(thenBlock);
            }
        }
    }
}

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

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

class UnusedMethodRemover extends VoidVisitorAdapter {
    non-public Set calledMethods = new HashSet();
    non-public Checklist methodsToRemove = new ArrayList();

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

    // Accumulate 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.comprises(methodName) && !methodName.equals("most important")) {
            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
most important, it provides it to the listing 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 most important(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 strategy to code transformation:

• OpenRewrite’s Lossless Semantic Timber (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 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 write down 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 might not be acquainted with AST
manipulation.

You possibly can compose, take a look at, and deploy a codemod to any repository
linked to Hypermod. It may run the codemod and generate a pull
request with the proposed modifications, permitting you to evaluate and approve
them. This integration makes all the course of from codemod growth
to deployment way more streamlined.

Codemod.com

Codemod.com is a community-driven platform the place builders
can share and uncover codemods. For those who want a selected codemod for a
widespread refactoring process 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.

For those who’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, lowering the necessity to write one from
scratch.