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 manage 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 wash up the toggle and any associated logic.

As an illustration, take into account the next code:

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

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

const information = { identify: 'Product' };

The duty includes 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 similar 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 seems to be in an AST. You should 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 adjustments.

The picture beneath reveals the syntax tree when it comes to ECMAScript syntax. It
accommodates 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 characteristic toggle verify

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 { identify: 'Product' } to information. 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 unfavourable case to
guarantee we don’t by chance 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 known as inside an if assertion), implement that case, and
guarantee all checks cross.

This method aligns effectively with Check-Pushed Improvement (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 possibly can write checks to confirm how the codemod
behaves:

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

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

The defineInlineTest operate from jscodeshift lets you outline
the enter, anticipated output, and a string describing the take a look at’s intent.
Now, working 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 characteristic toggles:

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

Writing the Codemod

Let’s begin by defining a easy rework operate. Create a file
referred to as rework.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 rework steps:

1. Discover all situations 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 = 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: { 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 ensuing (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 decreasing
handbook 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 situations.

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, verify that every one purposeful checks nonetheless
cross and that nothing breaks—even for those who’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’ll
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 elements. Manually
refactoring these areas may be time-consuming and error-prone.

By automating refactoring duties, codemods assist preserve your codebase clear
and freed from legacy patterns. Repeatedly making use of codemods lets you
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. At any time when a person passes a identify prop into the Avatar, it
robotically 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 (
      <Tooltip content material={identify}>
        <CircleImage picture={picture} />
      </Tooltip>
    );
  }

  return <CircleImage picture={picture} />;
};

The purpose is to decouple the Tooltip from the Avatar element,
giving builders extra flexibility. Builders ought to be capable to determine
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 lot 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 characterize the Avatar utilization
we’re concentrating on. An Avatar element with each identify and picture props
is parsed into an summary syntax tree as proven beneath:

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 toddler of the Tooltip.
• Exchange 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
checks, however it’s best to write comparability checks first).

defineInlineTest(
    { default: rework, parser: "tsx" },
    {},
    `
    <Avatar identify="Juntao Qiu" picture="/juntao.qiu.avatar.png" />
    `,
    `
    <Tooltip content material="Juntao Qiu">
      <Avatar picture="/juntao.qiu.avatar.png" />
    </Tooltip>
    `,
    "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 verify 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 operate, 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 toddler. Lastly, we name replaceWith to
exchange 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 precise 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
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 adjustments the place
handbook updates could be an enormous burden. Nonetheless, that is not the entire
image. Within the subsequent part, I’ll make clear a number of the challenges
and the way we will handle these less-than-ideal elements.

Leveraging Supply Graphs and Check-Pushed Codemods

To deal with these complexities, codemods ought to be used alongside different
methods. As an illustration, 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 out the supply graph, which contained nearly all of inside
element utilization. This allowed us to grasp how elements have been used,
whether or not they have been imported below completely different names, or whether or not sure
public props have been ceaselessly used. After this search section, 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 working the script to deal with particular instances manually. Normally,
there have been solely a handful of such situations, so this method nonetheless proved
helpful for upgrading variations.

Using Current Code Standardization Instruments

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

Nonetheless, in case your codebase has standardization instruments in place, similar to a
linter that enforces a specific coding model, you possibly can leverage these
instruments to cut back edge instances. By implementing 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 would use linting guidelines to limit sure patterns,
similar to avoiding nested conditional (ternary) operators or implementing 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 lets you deal with particular person points extra exactly. As
we’ll quickly see, composing smaller codemods could make dealing with complicated
adjustments extra possible.

Codemod Composition

Let’s revisit the characteristic toggle removing instance mentioned earlier. Within the code snippet
now we have 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 outcome = featureToggle("feature-convert-new")
  ? convertNew("Hi there, world")
  : convertOld("Hi there, world");

console.log(outcome);

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

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

const outcome = convertNew("Hi there, world");

console.log(outcome);

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

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

After all, you would write one massive codemod to deal with every little thing in a
single cross and take a look at it collectively. Nonetheless, a extra maintainable method is
to deal with codemod logic like product code: break the duty into smaller,
unbiased items—similar to how you’ll usually refactor manufacturing
code.

Breaking It Down

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

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

• A metamorphosis to take away a particular characteristic toggle.
• One other transformation to wash up unused imports.
• A metamorphosis to take away unused operate 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 operate because it’s not used.

Determine 6: Compose transforms into a brand new rework

You can too extract further codemods as wanted, combining them in
varied orders relying on the specified consequence.

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

The createTransformer Perform

The implementation of the createTransformer operate is comparatively
simple. It acts as a higher-order operate that takes an inventory of
smaller rework capabilities, iterates by way of the checklist 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((rework) => rework(j, root));
    return root.toSource(choices.printOptions || { quote: "single" });
  };

export { createTransformer };

For instance, you would have a rework operate 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 would possibly construct up a group of reusable, smaller
transforms, which might significantly ease the method of dealing with tough edge
instances. This method proved extremely efficient in our work refining design
system elements. As soon as we transformed one package deal—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 package deal is already imported above.

Every of those smaller transforms may be examined and used independently
or mixed for extra complicated transformations, which quickens subsequent
conversions considerably. Consequently, our refinement work turned 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 possibly can fine-tune them
with out affecting different transforms or the extra complicated, composed ones. For
occasion, you would possibly 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 may be helpful for making breaking API adjustments or refactoring
massive Java codebases in a structured, automated means.

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 will outline a customer to seek out if statements checking for
FeatureToggle.isEnabled, after which exchange them with the corresponding
true department—just 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 seems to be for if statements
that decision FeatureToggle.isEnabled() and replaces your entire
if assertion with the true department.

You can too outline guests to seek out unused strategies and take away
them:

class UnusedMethodRemover extends VoidVisitorAdapter<Void> {
    personal Set<String> calledMethods = new HashSet<>();
    personal Checklist<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("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 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’ll be able to chain these guests collectively and apply them to your codebase
like so:

public class FeatureToggleRemoverWithCleanup {
    public static void most important(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 method 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 might 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 frequent transformations with out
needing to jot 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 is probably not conversant in AST
manipulation.

You’ll be able to compose, take a look at, and deploy a codemod to any repository
linked to Hypermod. It could actually run the codemod and generate a pull
request with the proposed adjustments, permitting you to evaluate and approve
them. This integration makes your entire 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. If you happen to want a particular codemod for a
frequent refactoring job or migration, you possibly can seek for present
codemods. Alternatively, you possibly can publish codemods you’ve created to assist
others within the developer group.

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