Refactoring with Codemods to Automate API Modifications

As a library developer, you might create a well-liked utility that a whole lot of
hundreds of builders depend on day by day, corresponding to lodash or React. Over time,
utilization patterns may emerge that transcend your preliminary design. When this
occurs, you might want to increase an API by including parameters or modifying
operate signatures to repair edge instances. The problem lies in rolling out
these breaking adjustments with out disrupting your customers’ workflows.

That is the place codemods are available—a robust software for automating
large-scale code transformations, permitting builders to introduce breaking
API adjustments, refactor legacy codebases, and preserve code hygiene with
minimal handbook effort.

On this article, we’ll discover what codemods are and the instruments you may
use to create them, corresponding to jscodeshift, hypermod.io, and codemod.com. We’ll stroll by real-world examples,
from cleansing up characteristic toggles to refactoring part hierarchies.
You’ll additionally discover ways to break down complicated transformations into smaller,
testable items—a follow generally known as codemod composition—to make sure
flexibility and maintainability.

By the top, you’ll see how codemods can grow to be an important a part of your
toolkit for managing large-scale codebases, serving to you retain your code clear
and maintainable whereas dealing with even probably the most difficult refactoring
duties.

Breaking Modifications in APIs

Returning to the situation of the library developer, after the preliminary
launch, new utilization patterns emerge, prompting the necessity to prolong an
API—maybe by including a parameter or modifying a operate signature to
make it simpler to make use of.

For easy adjustments, a primary find-and-replace within the IDE may work. In
extra complicated instances, you may resort to utilizing instruments like sed
or awk. Nonetheless, when your library is extensively adopted, the
scope of such adjustments turns into tougher to handle. You’ll be able to’t make sure how
extensively the modification will impression your customers, and the very last thing
you need is to interrupt present performance that doesn’t want
updating.

A typical strategy is to announce the breaking change, launch a brand new
model, and ask customers emigrate at their very own tempo. However this workflow,
whereas acquainted, usually does not scale nicely, particularly for main shifts.
Think about React’s transition from class parts to operate parts
with hooks—a paradigm shift that took years for giant codebases to completely
undertake. By the point groups managed emigrate, extra breaking adjustments have been
usually already on the horizon.

For library builders, this case creates a burden. Sustaining
a number of older variations to help customers who haven’t migrated is each
expensive and time-consuming. For customers, frequent adjustments danger eroding belief.
They could hesitate to improve or begin exploring extra secure options,
which perpetuating the cycle.

However what should you might assist customers handle these adjustments mechanically?
What should you might launch a software alongside your replace that refactors
their code for them—renaming features, updating parameter order, and
eradicating unused code with out requiring handbook intervention?

That’s the place codemods are available. A number of libraries, together with React
and Subsequent.js, have already embraced codemods to easy the trail for model
bumps. For instance, React offers codemods to deal with the migration from
older API patterns, just like the previous Context API, to newer ones.

So, what precisely is the codemod we’re speaking about right here?

What’s a Codemod?

A codemod (code modification) is an automatic script used to remodel
code to observe new APIs, syntax, or coding requirements. Codemods use
Summary Syntax Tree (AST) manipulation to use constant, large-scale
adjustments throughout codebases. Initially developed at Fb, codemods helped
engineers handle refactoring duties for giant initiatives like React. As
Fb scaled, sustaining the codebase and updating APIs turned
more and more tough, prompting the event of codemods.

Manually updating hundreds of information throughout totally different repositories was
inefficient and error-prone, so the idea of codemods—automated scripts
that rework code—was launched to deal with this downside.

The method sometimes entails three important steps:

Parsing the code into an AST, the place every a part of the code is
represented as a tree construction.
Modifying the tree by making use of a metamorphosis, corresponding to renaming a
operate or altering parameters.
Rewriting the modified tree again into the supply code.

By utilizing this strategy, codemods be sure that adjustments are utilized
constantly throughout each file in a codebase, lowering the possibility of human
error. Codemods also can deal with complicated refactoring eventualities, corresponding to
adjustments to deeply nested constructions or eradicating deprecated API utilization.

If we visualize the method, it could look one thing like this:

Determine 1: The three steps of a typical codemod course of

The concept of a program that may “perceive” your code after which carry out
automated transformations isn’t new. That’s how your IDE works while you
run refactorings like Extract Perform, Rename Variable, or Inline Perform.
Basically, your IDE parses the supply code into ASTs and applies
predefined transformations to the tree, saving the end result again into your
information.

For contemporary IDEs, many issues occur beneath the hood to make sure adjustments
are utilized appropriately and effectively, corresponding to figuring out the scope of
the change and resolving conflicts like variable identify collisions. Some
refactorings even immediate you to enter parameters, corresponding to when utilizing
Change Perform Declaration, the place you may modify the
order of parameters or default values earlier than finalizing the change.

Use jscodeshift in JavaScript Codebases

Let’s take a look at a concrete instance to grasp how we might run a
codemod in a JavaScript challenge. The JavaScript group has a number of
instruments that make this work possible, together with parsers that convert supply
code into an AST, in addition to transpilers that may rework the tree into
different codecs (that is how TypeScript works). Moreover, there are
instruments that assist apply codemods to complete repositories mechanically.

Probably the most standard instruments for writing codemods is jscodeshift, a toolkit maintained by Fb.
It simplifies the creation of codemods by offering a robust API to
manipulate ASTs. With jscodeshift, builders can seek for particular
patterns within the code and apply transformations at scale.

You need to use jscodeshift to establish and substitute deprecated API calls
with up to date variations throughout a complete challenge.

Let’s break down a typical workflow for composing a codemod
manually.

Clear a Stale Function Toggle

Let’s begin with a easy but sensible instance to display 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 reside in manufacturing and dealing as anticipated, the following
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') ? { identify: 'Product' } : undefined;

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

const information = { identify: '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 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 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 adjustments.

The picture under reveals the syntax tree when it comes to 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 characteristic toggle test

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

For a process with clear enter and output, I want writing checks first,
then implementing the codemod. I begin by defining a unfavorable case to
guarantee we don’t by accident change issues we wish 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 checks cross.

This strategy aligns nicely with Take a look at-Pushed Growth (TDD), even
should you don’t follow TDD repeatedly. 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 may 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 permits you to outline
the enter, anticipated output, and a string describing the check’s intent.
Now, working the check with a traditional 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') ? { 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
known 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:

Discover all cases of featureToggle.
Confirm that the argument handed is 'feature-new-product-list'.
Substitute 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 check is featureToggle('feature-new-product-list')
  root
    .discover(j.ConditionalExpression, {
      check: {
        callee: { identify: "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 check 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 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 check 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 may try it out on a goal codebase,
such because the one you are engaged on. jscodeshift offers a command-line
software that you should use to use the codemod and report the outcomes.

$ jscodeshift -t transform-name src/

After validating the outcomes, test that each one useful checks nonetheless
cross and that nothing breaks—even should you’re introducing a breaking change.
As soon as happy, you may 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 might be time-consuming and error-prone.

By automating refactoring duties, codemods assist hold your codebase clear
and freed from legacy patterns. Recurrently 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 Element

Now, let’s take 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. Every time a person passes a identify prop into the Avatar, it
mechanically 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 = ({ identify, picture }: AvatarProps) => {
  if (identify) {
    return (
      
        
      
    );
  }

  return ;
};

The aim is to decouple the Tooltip from the Avatar part,
giving builders extra flexibility. Builders ought to have the ability 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 could 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 concentrating on. An Avatar part with each identify and picture props
is parsed into an summary syntax tree as proven under:

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.
Examine 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.
Substitute the unique Avatar node with the brand new Tooltip.

To start, we’ll discover all cases of Avatar (I’ll omit a number of the
checks, however you need 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 test 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
part as a baby. Lastly, we name replaceWith to
substitute the present path.

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

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 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 tackle these less-than-ideal facets.

Fixing Frequent Pitfalls of Codemods

As a seasoned developer, you recognize the “comfortable path” is barely a small half
of the complete image. There are quite a few eventualities to think about when writing
a metamorphosis script to deal with code mechanically.

Builders write code in a wide range of kinds. For instance, somebody
may import the Avatar part however give it a unique identify as a result of
they could have one other Avatar part from a unique package deal:

import { Avatar as AKAvatar } from "@design-system/avatar";

const UserInfo = () => (
  AKAvatar identify="Juntao Qiu" picture="/juntao.qiu.avatar.png" />
);

A easy textual content seek for Avatar received’t work on this case. You’ll want
to detect the alias and apply the transformation utilizing the right
identify.

One other instance arises when coping with Tooltip imports. If the file
already imports Tooltip however makes use of an alias, the codemod should detect that
alias and apply the adjustments accordingly. You’ll be able to’t assume that the
part named Tooltip is at all times the one you’re searching for.

Within the characteristic toggle instance, somebody may use
if(featureToggle('feature-new-product-list')), or assign the results of
the toggle operate to a variable earlier than utilizing it:

const shouldEnableNewFeature = featureToggle('feature-new-product-list');

if (shouldEnableNewFeature) {
  //...
}

They may even use the toggle with different circumstances or apply logical
negation, making the logic extra complicated:

const shouldEnableNewFeature = featureToggle('feature-new-product-list');

if (!shouldEnableNewFeature && someOtherLogic) {
  //...
}

These variations make it tough to foresee each edge case,
growing the danger of unintentionally breaking one thing. Relying solely
on the instances you may anticipate just isn’t sufficient. You want thorough testing
to keep away from breaking unintended components of the code.

Leveraging Supply Graphs and Take a look at-Pushed Codemods

To deal with these complexities, codemods needs to be used alongside different
strategies. As an example, a number of years in the past, I participated in a design
system parts rewrite challenge at Atlassian. We addressed this concern by
first looking the supply graph, which contained nearly all of inner
part utilization. This allowed us to grasp how parts have been used,
whether or not they have been imported beneath totally different names, or whether or not sure
public props have been steadily used. After this search section, we wrote our
check instances upfront, making certain 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 working the script to deal with particular instances manually. Normally,
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 may 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
assessment of the outcomes.

Nonetheless, in case your codebase has standardization instruments in place, corresponding to a
linter that enforces a specific coding fashion, you may leverage these
instruments to scale back edge instances. By implementing 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,
corresponding 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 permits you to 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 elimination instance mentioned earlier. Within the code snippet
now we have a toggle known 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 end result = featureToggle("feature-convert-new")
  ? convertNew("Hey, world")
  : convertOld("Hey, world");

console.log(end result);

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

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

const end result = convertNew("Hey, world");

console.log(end result);

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.

In fact, you would write one large codemod to deal with the whole lot in a
single cross and check it collectively. Nonetheless, 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 large transformation down into smaller codemods and
compose them. The benefit of this strategy is that every transformation
might 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 change to take away a selected characteristic toggle.
One other transformation to scrub up unused imports.
A change to take away unused operate declarations.

By composing these, you may 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:

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

Determine 6: Compose transforms into a brand new rework

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

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

The `createTransformer` Perform

The implementation of the createTransformer operate is comparatively
easy. It acts as a higher-order operate that takes an inventory of
smaller rework features, iterates by the listing 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";

kind 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 may construct up a group of reusable, smaller
transforms, which might tremendously ease the method of dealing with difficult edge
instances. This strategy 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 a number of reusable transforms outlined, like including feedback
in the beginning of features, eradicating deprecated props, or creating aliases
when a package deal is already imported above.

Every of those smaller transforms might be examined and used independently
or mixed for extra complicated transformations, which hastens subsequent
conversions considerably. Because of this, our refinement work turned 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 may 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 check
protection, you are able to do this confidently and safely.

Codemods in Different Languages

Whereas the examples we’ve explored thus far concentrate on JavaScript and JSX
utilizing jscodeshift, codemods may also be utilized to different languages. For
occasion, JavaParser gives the same
mechanism in Java, utilizing AST manipulation to refactor Java code.

Utilizing JavaParser in a Java Codebase

JavaParser might be helpful for making breaking API adjustments or refactoring
massive Java codebases in a structured, automated method.

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 Function Enabled");
    }

    void oldFeature() {
        System.out.println("Previous Function");
    }
}

We are able to outline a customer to search out if statements checking for
FeatureToggle.isEnabled, after which substitute 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 {
    @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 for if statements
that decision FeatureToggle.isEnabled() and replaces your entire
if assertion with the true department.

You can even outline guests to search out unused strategies and take away
them:

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

    // Accumulate all known 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 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("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 known as strategies within the calledMethods
set and checks every methodology declaration. If a technique isn’t known as and isn’t
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’ll be able to chain these guests collectively and apply them to your codebase
like so:

public class FeatureToggleRemoverWithCleanup {
    public static void important(String[] args) {
        attempt {
            String filePath = "src/check/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.

OpenRewrite

One other standard possibility for Java initiatives is OpenRewrite. It makes use of a unique format of the
supply code tree known as Lossless Semantic Bushes (LSTs), which
present extra detailed info in comparison with conventional AST (Summary
Syntax Tree) approaches utilized by instruments like JavaParser or jscodeshift.
Whereas AST focuses on the syntactic construction, LSTs seize each syntax and
semantic which means, enabling extra correct and complicated
transformations.

OpenRewrite additionally has a strong ecosystem of open-source refactoring
recipes for duties corresponding to framework migrations, safety fixes, and
sustaining stylistic consistency. This built-in library of recipes can
save builders vital time by permitting them to use standardized
transformations throughout massive codebases without having to write down customized
scripts.

For builders who want personalized transformations, OpenRewrite permits
you to create and distribute your personal recipes, making it a extremely versatile
and extensible software. It’s extensively used within the Java group and is
progressively increasing into different languages, due to its superior
capabilities and community-driven strategy.

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 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 write down customized codemods from scratch.

Different Instruments for Codemods

Whereas jscodeshift and OpenRewrite are highly effective instruments, there are
different choices price contemplating, relying in your wants and the ecosystem
you are working in.

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, check, and deploy a codemod to any repository
related to Hypermod. It might run the codemod and generate a pull
request with the proposed adjustments, permitting you to assessment 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. For those who want a selected codemod for a
widespread refactoring process or migration, you may seek for present
codemods. Alternatively, you may publish codemods you’ve created to assist
others within the developer group.

For those who’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.

Conclusion

Codemods are highly effective instruments that permit builders to automate code
transformations, making it simpler to handle API adjustments, refactor legacy
code, and preserve consistency throughout massive codebases with minimal handbook
intervention. By utilizing instruments like jscodeshift, Hypermod, or
OpenRewrite, builders can streamline the whole lot from minor syntax
adjustments to main part rewrites, enhancing total code high quality and
maintainability.

Nonetheless, whereas codemods supply vital advantages, they aren’t
with out challenges. One of many key considerations is dealing with edge instances,
notably when the codebase is various or publicly shared. Variations
in coding kinds, import aliases, or surprising patterns can result in
points that codemods could not deal with mechanically. These edge instances
require cautious planning, thorough testing, and, in some cases, handbook
intervention to make sure accuracy.

To maximise the effectiveness of codemods, it’s essential to interrupt
complicated transformations into smaller, testable steps and to make use of code
standardization instruments the place attainable. Codemods might be extremely efficient,
however their success relies on considerate design and understanding the
limitations they might face in additional various or complicated codebases.

Breaking Modifications in APIs

So, what precisely is the codemod we’re speaking about right here?

What’s a Codemod?

The method sometimes entails three important steps:

Parsing the code into an AST, the place every a part of the code is
represented as a tree construction.
Modifying the tree by making use of a metamorphosis, corresponding to renaming a
operate or altering parameters.
Rewriting the modified tree again into the supply code.

If we visualize the method, it could look one thing like this:

Determine 1: The three steps of a typical codemod course of

Use jscodeshift in JavaScript Codebases

You need to use jscodeshift to establish and substitute deprecated API calls
with up to date variations throughout a complete challenge.

Let’s break down a typical workflow for composing a codemod
manually.

Clear a Stale Function Toggle

As an example, contemplate the next code:

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

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

const information = { identify: 'Product' };

Understanding the AST

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

With jscodeshift, you may 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 corresponding unfavorable 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
known 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:

Discover all cases of featureToggle.
Confirm that the argument handed is 'feature-new-product-list'.
Substitute 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 check is featureToggle('feature-new-product-list')
  root
    .discover(j.ConditionalExpression, {
      check: {
        callee: { identify: "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 check 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 simple it’s to create a helpful
transformation and apply it to a big codebase, considerably lowering
handbook effort.

$ jscodeshift -t transform-name src/

Codemods Enhance Code High quality and Maintainability

Refactoring an Avatar Element

Determine 3: A avatar part 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 ;
};

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 (
    
      
    
  );
};

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.
Examine 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.
Substitute the unique Avatar node with the brand new Tooltip.

To start, we’ll discover all cases of Avatar (I’ll omit a number of the
checks, however you need 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 test 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);
    }
  });

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

Fixing Frequent Pitfalls of Codemods

import { Avatar as AKAvatar } from "@design-system/avatar";

const UserInfo = () => (
  AKAvatar identify="Juntao Qiu" picture="/juntao.qiu.avatar.png" />
);

A easy textual content seek for Avatar received’t work on this case. You’ll want
to detect the alias and apply the transformation utilizing the right
identify.

Within the characteristic toggle instance, somebody may use
if(featureToggle('feature-new-product-list')), or assign the results of
the toggle operate to a variable earlier than utilizing it:

const shouldEnableNewFeature = featureToggle('feature-new-product-list');

if (shouldEnableNewFeature) {
  //...
}

They may even use the toggle with different circumstances or apply logical
negation, making the logic extra complicated:

const shouldEnableNewFeature = featureToggle('feature-new-product-list');

if (!shouldEnableNewFeature && someOtherLogic) {
  //...
}

Leveraging Supply Graphs and Take a look at-Pushed Codemods

Using Current Code Standardization Instruments

Codemod Composition

Let’s revisit the characteristic toggle elimination instance mentioned earlier. Within the code snippet
now we have a toggle known 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 end result = featureToggle("feature-convert-new")
  ? convertNew("Hey, world")
  : convertOld("Hey, world");

console.log(end result);

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

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

const end result = convertNew("Hey, world");

console.log(end result);

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.

Breaking It Down

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

A change to take away a selected characteristic toggle.
One other transformation to scrub up unused imports.
A change to take away unused operate declarations.

By composing these, you may 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:

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

Determine 6: Compose transforms into a brand new rework

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

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

The `createTransformer` Perform

import { API, Assortment, FileInfo, JSCodeshift, Choices } from "jscodeshift";

kind 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 };

const shouldEnableNewFeature = featureToggle('feature-convert-new');

if (!shouldEnableNewFeature && someOtherLogic) {
  //...
}

Turns into this:

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

Codemods in Different Languages

Utilizing JavaParser in a Java Codebase

JavaParser might be helpful for making breaking API adjustments or refactoring
massive Java codebases in a structured, automated method.

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 Function Enabled");
    }

    void oldFeature() {
        System.out.println("Previous Function");
    }
}

// Customer to take away characteristic 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);
            }
        }
    }
}

You can even outline guests to search out unused strategies and take away
them:

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

    // Accumulate all known 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 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("important")) {
            methodsToRemove.add(n);
        }
    }

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

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 important(String[] args) {
        attempt {
            String filePath = "src/check/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.

OpenRewrite

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 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 write down customized codemods from scratch.

Different Instruments for Codemods

Whereas jscodeshift and OpenRewrite are highly effective instruments, there are
different choices price contemplating, relying in your wants and the ecosystem
you are working in.

Hypermod

Codemod.com

Conclusion

Autonomous coding brokers: A Codex instance