February 12, 2025

As a library developer, you might create a well-liked utility that lots of of
1000’s of builders depend on each day, equivalent to lodash or React. Over time,
utilization patterns would possibly 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 modifications 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 modifications, refactor legacy codebases, and preserve code hygiene with
minimal handbook effort.

On this article, we’ll discover what codemods are and the instruments you’ll be able to
use to create them, equivalent to jscodeshift, hypermod.io, and codemod.com. We’ll stroll by means of real-world examples,
from cleansing up function toggles to refactoring element hierarchies.
You’ll additionally discover ways to break down advanced transformations into smaller,
testable items—a apply referred to as codemod composition—to make sure
flexibility and maintainability.

By the tip, you’ll see how codemods can change into a significant 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 state of affairs 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 modifications, a primary find-and-replace within the IDE would possibly work. In
extra advanced instances, you would possibly resort to utilizing instruments like sed
or awk. Nonetheless, when your library is broadly adopted, the
scope of such modifications turns into tougher to handle. You’ll be able to’t make sure how
extensively the modification will affect your customers, and the very last thing
you need is to interrupt present performance that doesn’t want
updating.

A standard method 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 would not scale nicely, particularly for main shifts.
Think about React’s transition from class elements to operate elements
with hooks—a paradigm shift that took years for big codebases to completely
undertake. By the point groups managed emigrate, extra breaking modifications 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 modifications threat eroding belief.
They might hesitate to improve or begin exploring extra secure alternate options,
which perpetuating the cycle.

However what in case you might assist customers handle these modifications mechanically?
What in case you might launch a software alongside your replace that refactors
their code for them—renaming capabilities, 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 clean the trail for model
bumps. For instance, React gives 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
modifications throughout codebases. Initially developed at Fb, codemods helped
engineers handle refactoring duties for big initiatives like React. As
Fb scaled, sustaining the codebase and updating APIs turned
more and more tough, prompting the event of codemods.

Manually updating 1000’s of information throughout completely different repositories was
inefficient and error-prone, so the idea of codemods—automated scripts
that remodel code—was launched to sort out this drawback.

The method sometimes entails three important steps:

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

By utilizing this method, codemods make sure that modifications are utilized
constantly throughout each file in a codebase, decreasing the prospect of human
error. Codemods also can deal with advanced refactoring eventualities, equivalent to
modifications to deeply nested buildings 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
computerized transformations isn’t new. That’s how your IDE works whenever you
run refactorings like Extract Function, Rename Variable, or Inline Function.
Primarily, your IDE parses the supply code into ASTs and applies
predefined transformations to the tree, saving the outcome again into your
information.

For contemporary IDEs, many issues occur underneath the hood to make sure modifications
are utilized accurately and effectively, equivalent to figuring out the scope of
the change and resolving conflicts like variable title collisions. Some
refactorings even immediate you to enter parameters, equivalent to when utilizing
Change Function Declaration, the place you’ll be able to modify the
order of parameters or default values earlier than finalizing the change.

Use jscodeshift in JavaScript Codebases

Let’s have 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 remodel the tree into
different codecs (that is how TypeScript works). Moreover, there are
instruments that assist apply codemods to whole repositories mechanically.

Some of the fashionable 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 should 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 Characteristic Toggle

Let’s begin with a easy but sensible instance to show 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.

For example, think about the next code:

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

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

const knowledge =  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 identical 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 appears 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 sorts 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
accommodates nodes like Identifier (for variables), StringLiteral (for the
toggle title), and extra summary nodes like CallExpression and
ConditionalExpression.

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

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

For a activity with clear enter and output, I favor writing checks first,
then implementing the codemod. I begin by defining a unfavourable case to
guarantee we don’t unintentionally change issues we wish to depart untouched,
adopted by an actual case that performs the precise conversion. I start with
a easy state of affairs, implement it, then add a variation (like checking if
featureToggle is known as inside an if assertion), implement that case, and
guarantee all checks go.

This method aligns nicely with Take a look at-Pushed Improvement (TDD), even
in case you don’t apply TDD usually. Realizing precisely what the
transformation’s inputs and outputs are earlier than coding improves security and
effectivity, particularly when tweaking codemods.

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

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

defineInlineTest(
  remodel,
  ,
  `
  const knowledge = featureToggle('feature-new-product-list') ?  title: 'Product'  : undefined;
  `,
  `
  const knowledge =  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 check’s intent.
Now, operating the check with a traditional 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 knowledge = featureToggle('feature-search-result-refinement') ?  title: 'Product'  : undefined;
  `,
  `
  const knowledge = 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 are able to 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 check is featureToggle('feature-new-product-list')
  root
    .discover(j.ConditionalExpression, 
      check: 
        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 check calls
    featureToggle('feature-new-product-list').
  • Replaces all the conditional expression with the resultant (i.e.,
    title: '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 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 sturdy in real-world eventualities.

As soon as the codemod is prepared, you’ll be able to try it out on a goal codebase,
such because the one you are engaged on. jscodeshift gives a command-line
software 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 practical checks nonetheless
go and that nothing breaks—even in case you’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 will be time-consuming and error-prone.

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

Refactoring an Avatar Part

Now, let’s have a look at a extra advanced instance. Suppose you’re working with
a design system that features an Avatar element tightly coupled with a
Tooltip. At any time when a consumer passes a title prop into the Avatar, it
mechanically 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 = ( title, picture : AvatarProps) => 
  if (title) 
    return (
      <Tooltip content material=title>
        <CircleImage picture=picture />
      </Tooltip>
    );
  

  return <CircleImage picture=picture />;
;

The aim is to decouple the Tooltip from the Avatar element,
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 <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 lots of of Avatar usages unfold
throughout the codebase. Manually refactoring every occasion can be extremely
inefficient, so we are able to use a codemod to automate this course of.

Utilizing instruments like AST Explorer, we are able to
examine the element and see which nodes characterize the Avatar utilization
we’re focusing on. An Avatar element with each title 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.
  • Examine 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 toddler 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 among the
checks, however you need to write comparability checks first).

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

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

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

Subsequent, we verify 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
element as a toddler. Lastly, we name replaceWith to
substitute the present path.

Right here’s a preview of the way it appears 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 outcome:

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. Nonetheless, that is not the entire
image. Within the subsequent part, I’ll make clear among the challenges
and the way we are able to deal with these less-than-ideal features.

Fixing Frequent Pitfalls of Codemods

As a seasoned developer, you understand the “glad path” is simply a small half
of the complete image. There are quite a few eventualities to contemplate when writing
a metamorphosis script to deal with code mechanically.

Builders write code in quite a lot of types. For instance, somebody
would possibly import the Avatar element however give it a special title as a result of
they may have one other Avatar element from a special package deal:

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

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

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

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 modifications accordingly. You’ll be able to’t assume that the
element named Tooltip is at all times the one you’re in search of.

Within the feature toggle example, somebody would possibly 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 could even use the toggle with different situations or apply logical
negation, making the logic extra advanced:

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’ll be able to anticipate is just not sufficient. You want thorough testing
to keep away from breaking unintended elements 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. For example, a couple of years in the past, I participated in a design
system elements rewrite challenge at Atlassian. We addressed this difficulty by
first looking the supply graph, which contained the vast majority of inner
element 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 regularly used. After this search section, we wrote our
check instances upfront, guaranteeing we coated the vast majority 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. Normally,
there have been solely a handful of such cases, so this method nonetheless proved
helpful for upgrading variations.

Using Present 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
overview of the outcomes.

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

For example, you can use linting guidelines to limit sure patterns,
equivalent 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 advanced 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 advanced
modifications extra possible.

Codemod Composition

Let’s revisit the function toggle elimination 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("Whats up, world")
  : convertOld("Whats up, world");

console.log(outcome);

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

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

const outcome = convertNew("Whats up, world");

console.log(outcome);

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

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

In fact, you can write one massive codemod to deal with every part in a
single go and check it collectively. Nonetheless, a extra maintainable method is
to deal with codemod logic like product code: break the duty into smaller,
impartial items—identical to how you’ll 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 method is that every transformation
will be examined individually, masking completely different instances with out interference.
Furthermore, it means that you can reuse and compose them for various
functions.

For 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 not used.

Determine 6: Compose transforms into a brand new remodel

You can even extract extra codemods as wanted, combining them in
numerous orders relying on the specified final 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
easy. It acts as a higher-order operate that takes an inventory of
smaller remodel capabilities, iterates by means of the record to use them to
the basis 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((remodel) => remodel(j, root));
    return root.toSource(choices.printOptions ;

export  createTransformer ;

For instance, you can 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 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
at first of capabilities, eradicating deprecated props, or creating aliases
when a package deal is already imported above.

Every of those smaller transforms will be examined and used independently
or mixed for extra advanced transformations, which hastens subsequent
conversions considerably. In consequence, our refinement work turned 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 advanced, composed ones. For
occasion, you would possibly re-implement a remodel to enhance efficiency—like
decreasing 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 to this point deal with JavaScript and JSX
utilizing jscodeshift, codemods will also be utilized to different languages. For
occasion, JavaParser provides an identical
mechanism in Java, utilizing AST manipulation to refactor Java code.

Utilizing JavaParser in a Java Codebase

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

Assume 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("Outdated Characteristic");
    

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—much like how we dealt with the function toggle codemod in
JavaScript.

// Customer to take away function 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.substitute(thenBlock);
            
        
    

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

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

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

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

    // Gather strategies to take away if not 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("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 way isn’t referred to as and isn’t
important, it provides it to the record of strategies to take away. As soon as all strategies are
processed, it removes any unused strategies from the AST.

Composing Java Guests

You’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 straightforward to compose them.

OpenRewrite

One other fashionable possibility for Java initiatives is OpenRewrite. It makes use of a special format of the
supply code tree referred to 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 that means, enabling extra correct and complicated
transformations.

OpenRewrite additionally has a sturdy ecosystem of open-source refactoring
recipes for duties equivalent 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 giant codebases with no need to write down customized
scripts.

For builders who want custom-made transformations, OpenRewrite permits
you to create and distribute your individual recipes, making it a extremely versatile
and extensible software. It’s broadly used within the Java group and is
regularly increasing into different languages, due to its superior
capabilities and community-driven method.

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 at all times
    seize the nuances of how the code behaves semantically.

Moreover, OpenRewrite provides 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 value contemplating, relying in your wants and the ecosystem
you are working in.

Hypermod

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

You’ll be able to compose, check, and deploy a codemod to any repository
related to Hypermod. It might probably run the codemod and generate a pull
request with the proposed modifications, permitting you to overview 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. In case you want a selected codemod for a
widespread refactoring activity 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 group.

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

Conclusion

Codemods are highly effective instruments that permit builders to automate code
transformations, making it simpler to handle API modifications, refactor legacy
code, and preserve consistency throughout giant codebases with minimal handbook
intervention. By utilizing instruments like jscodeshift, Hypermod, or
OpenRewrite, builders can streamline every part from minor syntax
modifications to main element rewrites, enhancing general 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,
significantly when the codebase is various or publicly shared. Variations
in coding types, 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
advanced transformations into smaller, testable steps and to make use of code
standardization instruments the place doable. Codemods will be extremely efficient,
however their success relies on considerate design and understanding the
limitations they might face in additional diversified or advanced codebases.