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Constructing Customized Tooling with LLMs

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May 30, 2025
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Instruments that deal with diagrams as code, corresponding to PlantUML, are invaluable for speaking
advanced system conduct. Their text-based format simplifies versioning, automation, and
evolving architectural diagrams alongside code. In my work explaining distributed
techniques, PlantUML’s sequence diagrams are notably helpful for capturing interactions
exactly.

Nonetheless, I usually wished for an extension to stroll via these diagrams step-by-step,
revealing interactions sequentially relatively than displaying the complete advanced stream at
as soon as—like a slideshow for execution paths. This want displays a typical developer
situation: wanting customized extensions or inner instruments for their very own wants.

But, extending established instruments like PlantUML usually includes important preliminary
setup—parsing hooks, construct scripts, viewer code, packaging—sufficient “plumbing” to
deter speedy prototyping. The preliminary funding required to start can suppress good
concepts.

That is the place Giant Language Fashions (LLMs) show helpful. They’ll deal with boilerplate
duties, liberating builders to concentrate on design and core logic. This text particulars how I
used an LLM to construct PlantUMLSteps, a small extension including step-wise
playback to PlantUML sequence diagrams. The objective is not simply the software itself, however
illustrating the method how syntax design, parsing, SVG technology, construct automation,
and an HTML viewer have been iteratively developed via a dialog with an LLM,
turning tedious duties into manageable steps.

Diagram as code – A PlantUML primer

Earlier than diving into the event course of, let’s briefly introduce PlantUML
for many who may be unfamiliar. PlantUML is an open-source software that enables
you to create UML diagrams from a easy text-based description language. It
helps
numerous diagram varieties together with sequence, class, exercise, part, and state
diagrams.

The ability of PlantUML lies in its potential to model management diagrams
as plain textual content, combine with documentation techniques, and automate diagram
technology inside growth pipelines. That is notably invaluable for
technical documentation that should evolve alongside code.

This is a easy instance of a sequence diagram in PlantUML syntax:

@startuml

cover footbox

actor Consumer
participant System
participant Database

Consumer -> System: Login Request
System --> Consumer: Login Kind

Consumer -> System: Submit Credentials
System -> Database: Confirm Credentials
Database --> System: Validation End result
System --> Consumer: Authentication End result

Consumer -> System: Request Dashboard
System -> Database: Fetch Consumer Information
Database --> System: Consumer Information
System --> Consumer: Dashboard View
@enduml 

When processed by PlantUML, this textual content generates a visible sequence diagram displaying the
interplay between elements.

The code-like nature of PlantUML makes
it straightforward to study and use, particularly for builders who’re already comfy
with text-based instruments.

This simplicity is what makes PlantUML an ideal candidate for extension. With the
proper tooling, we will improve its capabilities whereas sustaining its text-based
workflow.

Our objective for this undertaking is to create a software which might divide the
sequence diagram into steps and generate a step-by-step view of the diagram.
So for the above diagram, we must always have the ability to view login, authentication and
dashboard
steps one after the other.

Step 2: Constructing the Parser Logic (and Debugging)

“Now we have to parse the plantuml recordsdata and separate out step. Each time we
encounter a step marker, we create a step object and hold including the following strains
to it till we encounter one other step marker or finish of file. In case we
encounter one other step counter, we create new step object, it ought to have all
the contains, actors and members from the earlier step. It also needs to
have all of the content material of the earlier step, until the step metadata has
‘newPage’ attribute. If there are not any step markers encountered, which is the case
the place we have now recordsdata with out steps, it ought to create a default step. Create a
StepParser to parse given puml recordsdata and create checklist of steps.”

Claude generated the preliminary code for a StepParser class and a Step mannequin class to
deal with parsing PlantUML recordsdata with step markers. The preliminary implementation had some
logical points:

  • Incorrect dealing with of step content material inheritance when newPage attribute was false
  • Improper dealing with of declarations (actors, members) showing earlier than the
    first step marker
  • Points with making a default step for recordsdata with out markers

The Cursor editor was operating in Agent mode, so after operating assessments and figuring out
these points via the failure messages, Claude offered a corrected model that
correctly dealt with:

  • Content material collected earlier than step one marker
  • Inheritance of content material from the instantly previous step
  • World monitoring of declarations throughout steps
  • Correct creation of a default step for recordsdata with out markers

With these corrections, the parser efficiently handed all assessments.

The following step was to generate a gradle process.

We’d like gradle process which might course of puml recordsdata in src/diagrams and its sub
folders. For every file it ought to create a listing with the title of the file the place
it generates legitimate puml file for every step. It could possibly generate that by simply including
@startuml at the beginning and @enduml on the finish of the step content material.

I will make it easier to create a Gradle process to course of PlantUML recordsdata and generate
step-by-step diagrams. First, let’s create the duty in
construct.gradle:

// Course of every .puml file within the enter listing and its subdirectories
fileTree(inputDir).embrace('**/*.puml').every { pumlFile ->
    def relativePath = inputDir.toPath().relativize(pumlFile.toPath()).toString()
    def fileName = pumlFile.title.substitute('.puml', '')
    def stepOutputDir = new File(outputDir, fileName)
    
    if (!stepOutputDir.exists()) {
        stepOutputDir.mkdirs()
    }
    
    // Run the generator for this file
    javaexec {
        classpath = sourceSets.principal.runtimeClasspath
        mainClass = 'com.instance.StepDiagramGenerator'
        args = [pumlFile.absolutePath, stepOutputDir.absolutePath]
    }

Claude additionally helped producing a easy plantuml sequence diagram to check the gradle
process. The identical one which we used originally of the article.

The gradle process wanted a category PlantUMLGenerator which
can generate SVGs for every step.
Cursor within the Agent mode generated the code for the category.

It then ran the construct to confirm the duty.

Let's run a take a look at to substantiate our implementation works: cd /Customers/unmeshjoshi/work/plantumlsequence && ./gradlew clear construct
                
Job :generateStepDiagrams
Generated step diagram: /Customers/unmeshjoshi/work/plantumlsteps/construct/generated-diagrams/user-authentication/step-01-step-1-user-login.puml
Generated step diagram: /Customers/unmeshjoshi/work/plantumlsteps/construct/generated-diagrams/user-authentication/step-02-step-2-authentication.puml
Generated step diagram: /Customers/unmeshjoshi/work/plantumlsteps/construct/generated-diagrams/user-authentication/step-03-step-3-dashboard.puml
Generated step stream abstract: /Customers/unmeshjoshi/work/plantumlsteps/construct/generated-diagrams/user-authentication/abstract.puml

        BUILD SUCCESSFUL in 543ms
        3 actionable duties: 3 executed

Step 3: Producing HTML Viewer for Step Sequence

The following step was to generate a easy HTML viewer that can be utilized to view the step
sequence.

Now we have to generate a HTML viewer for the step recordsdata to be proven one after the other.
The HTML viewer can have a view space the place we present the svg picture generated for every
step with the step title within the metadata for that step. We will have subsequent and former
buttons to indicate subsequent and former step picture.

I will make it easier to create an HTML viewer for the step diagrams. We’ll must: Generate
SVG recordsdata from the PlantUML recordsdata Create an HTML viewer with navigation controls
Replace the Gradle process to generate each PlantUML and SVG recordsdata, together with the HTML
viewer First, let’s create a easy HTML template for the viewer:
….

The agent mode found out a couple of points with the template however auto-fixed it by
operating some corrective actions.

This setup allowed us to shortly generate step diagrams from a single PlantUML file,
and consider them in a step-by-step method. So the above diagram may be considered as a
sequence of following steps:

The Code is the Supply of Reality

The place to go from right here?

Whereas the prompts and the LLM assistant (on this case, interacting in an agent-like
mode, using fashions like Claude Sonnet) offered a remarkably efficient strategy to
generate a working first model of PlantUMLSteps, it is essential to
acknowledge the character of this generated output.

  • Prompts should not Deterministic: The prompts utilized in our dialog have been
    efficient for this interplay, however they can’t be handled as the final word
    ‘supply of fact’. The identical prompts given to a special mannequin, and even the identical
    mannequin at a later date, should not assured to provide the very same output due
    to the inherent variability in LLM technology.
  • Code Requires Administration: The generated code is the supply of fact for
    the software’s performance. As such, it must be handled like another
    software program artifact – checked into model management, reviewed, examined, and
    maintained.
  • Evaluation for Habitability: It is important to revisit the LLM-generated code
    after the preliminary creation part. Is it ‘liveable’? That’s, is it moderately
    straightforward to learn, perceive, and modify by a human developer? Whereas the LLM helped
    overcome preliminary hurdles and boilerplate, guaranteeing the long-term maintainability
    and readability of the codebase usually requires human overview and potential
    refactoring. The objective is code that not solely works however may also be advanced
    successfully over time.

Prompting in pure language (like English) to generate code works properly within the
early phases of growth—once you’re exploring concepts, scaffolding performance,
or getting acquainted with a brand new software or framework. However as your system begins to take
form, the boundaries of obscure or broad prompts grow to be obvious. At this stage, what’s
wanted will not be extra code technology, however conceptual modeling—utilizing the constructs of
your programming language or know-how stack to precisely characterize the area.
This stage wants deeper considering to construct abstractions, and an alignment between
code construction and area ideas—one thing solely achievable via considerate
design, not simply prompting. If prompt-based code technology with out
overview is named “vibe coding,” then the extra disciplined strategy may be
referred to as “AI-assisted structured coding.”.

Past Code Technology: The Developer Perception in Refactoring

The following step was to refactor the code to make it extra readable and maintainable.

Initially, the parse methodology was a protracted, monolithic operate that dealt with every thing
from
detecting step markers to managing declarations and content material. The code was troublesome
to
perceive and keep.

The total code is out there in
this preliminary commit on GitHub.

The `StepParser.java` parse methodology wants refactoring. It ought to characterize ideas
used within the requirement or area ideas and comply with normal clear code practices
with intentional methodology names and code that reads like a DSL.

This preliminary request was open-ended, indicating that the developer acknowledged the
want for enchancment however was in search of steering on the right way to strategy it.
The LLM responded with a complete refactoring that launched a number of new
courses and strategies:

- Launched `PlantUmlDocument` to characterize the doc being parsed
- Smaller, extra targeted strategies with intention-revealing names
- Higher encapsulation of associated behaviors
- Extra expressive variable and methodology names


    /**
     * Represents a PlantUML doc being parsed, managing state throughout parsing
     */
    personal class PlantUmlDocument {
        personal remaining Record steps = new ArrayList<>();
        personal remaining Record declarations = new ArrayList<>();
        personal remaining Record contentBeforeFirstStep = new ArrayList<>();
        personal Step currentStep = null;
        personal boolean hasStepMarkers = false;
        
        public void beginNewStep(StepMetadata metadata) {
            hasStepMarkers = true;
            
            // Save the present step if it exists
            if (currentStep != null) {
                steps.add(currentStep);
            }
            
            // Create a brand new step
            currentStep = new Step(metadata.getName(), metadata.isNewPage(), metadata.getAttributes());
            
            // Add all declarations to the brand new step
            currentStep.addAllDeclarations(declarations);
            
            // If this is not a brand new web page and we have now earlier steps, copy all content material from earlier steps
            if (!metadata.isNewPage() && !steps.isEmpty()) {
                carryOverPreviousStepsContent();
            }
        }
        
        personal void carryOverPreviousStepsContent() {
            for (Step previousStep : steps) {
                for (String contentLine : previousStep.getContent()) {
                    currentStep.addContent(contentLine);
                }
            }
        }
        
        public void addDeclaration(String line) {
            declarations.add(line);
            
            if (currentStep != null) {
                currentStep.addDeclaration(line);
            } else {
                contentBeforeFirstStep.add(line);
            }
        }
        
        public void addContentLine(String line) {
            if (currentStep != null) {
                currentStep.addContent(line);
            } else if (!line.trim().isEmpty()) {
                contentBeforeFirstStep.add(line);
            }
        }
        
        public void finalizeDocument() {
            // Add the final step if it exists and hasn't been added but
            if (currentStep != null) {
                steps.add(currentStep);
            }
        }

The total code is out there in
this commit on GitHub.

The `contentBeforeFirstStep` in `PlantUmlDocument.java` is used just for creating
default step when there are not any step markers?
So we will presumably
do two cross processing the place we first test if there are step markers.. if there
are.. we do step-based processing. Or else we simply create a default step and add all
declarations and content material. That may take away the necessity to have `contentBeforeFirstStep`
We will additionally possibily title PlantUmlDocument as `ParsedPumlFile` which represents
the parsed puml file.

The LLM carried out this suggestion with a two-pass strategy. It additionally renamed the
PlantUmlDocument as ParsedPumlFile.
The total code is out there in
this commit on GitHub.

`ParsedPumlFile` may be higher represented as builder sample.
`StepBuilder` generally is a builder for `Step` objects.

This perception demonstrated the developer’s potential to acknowledge design patterns,
noting that the refactored class adopted the Builder sample.

The ultimate refactoring represents a major enchancment over the unique code:

class StepBuilder {
    personal remaining Record steps = new ArrayList<>();
    personal remaining Record globalDeclarations = new ArrayList<>();
    personal Step currentStep = null;
    
    public void startNewStep(StepMetadata metadata) {
        if (currentStep != null) {
            steps.add(currentStep);
        }
        
        currentStep = new Step(metadata);
        currentStep.addAllDeclarations(globalDeclarations);
        
        if (!metadata.isNewPage() && !steps.isEmpty()) {
            // Copy content material from the earlier step
            Step previousStep = steps.get(steps.dimension() - 1);
            for (String contentLine : previousStep.getContent()) {
                currentStep.addContent(contentLine);
            }
        }
    }
    
    public void addDeclaration(String declaration) {
        globalDeclarations.add(declaration);
        
        if (currentStep != null) {
            currentStep.addDeclaration(declaration);
        }
    }
    
    public void addContent(String content material) {
        // If no step has been began but, create a default step
        if (currentStep == null) {
            StepMetadata metadata = new StepMetadata("Default Step", false, new HashMap<>());
            startNewStep(metadata);
        }
        
        currentStep.addContent(content material);
    }
    
    public Record construct() {
        if (currentStep != null) {
            steps.add(currentStep);
        }
        
        return new ArrayList<>(steps);
    }
} 

The total code is out there in
this commit on GitHub.

There are extra enhancements potential,
however I’ve included a couple of to exhibit the character of collaboration between LLMs
and builders.

Conclusion

Every a part of this extension—remark syntax, Java parsing logic, HTML viewer, and
Gradle wiring—began with a targeted LLM immediate. Some components required some skilled
developer steering to LLM, however the important thing profit was with the ability to discover and
validate concepts with out getting slowed down in boilerplate. LLMs are notably
useful when you’ve a design in thoughts however should not getting began due to
the efforts wanted for organising the scaffolding to attempt it out. They can assist
you generate working glue code, combine libraries, and generate small
UIs—leaving you to concentrate on whether or not the concept itself works.

After the preliminary working model, it was necessary to have a developer to information
the LLM to enhance the code, to make it extra maintainable. It was vital
for builders to:

  • Ask insightful questions
  • Problem proposed implementations
  • Recommend various approaches
  • Apply software program design rules

This collaboration between the developer and the LLM is vital to constructing
maintainable and scalable techniques. The LLM can assist generate working code,
however the developer is the one who could make it extra readable, maintainable and
scalable.


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Instruments that deal with diagrams as code, corresponding to PlantUML, are invaluable for speaking
advanced system conduct. Their text-based format simplifies versioning, automation, and
evolving architectural diagrams alongside code. In my work explaining distributed
techniques, PlantUML’s sequence diagrams are notably helpful for capturing interactions
exactly.

Nonetheless, I usually wished for an extension to stroll via these diagrams step-by-step,
revealing interactions sequentially relatively than displaying the complete advanced stream at
as soon as—like a slideshow for execution paths. This want displays a typical developer
situation: wanting customized extensions or inner instruments for their very own wants.

But, extending established instruments like PlantUML usually includes important preliminary
setup—parsing hooks, construct scripts, viewer code, packaging—sufficient “plumbing” to
deter speedy prototyping. The preliminary funding required to start can suppress good
concepts.

That is the place Giant Language Fashions (LLMs) show helpful. They’ll deal with boilerplate
duties, liberating builders to concentrate on design and core logic. This text particulars how I
used an LLM to construct PlantUMLSteps, a small extension including step-wise
playback to PlantUML sequence diagrams. The objective is not simply the software itself, however
illustrating the method how syntax design, parsing, SVG technology, construct automation,
and an HTML viewer have been iteratively developed via a dialog with an LLM,
turning tedious duties into manageable steps.

Diagram as code – A PlantUML primer

Earlier than diving into the event course of, let’s briefly introduce PlantUML
for many who may be unfamiliar. PlantUML is an open-source software that enables
you to create UML diagrams from a easy text-based description language. It
helps
numerous diagram varieties together with sequence, class, exercise, part, and state
diagrams.

The ability of PlantUML lies in its potential to model management diagrams
as plain textual content, combine with documentation techniques, and automate diagram
technology inside growth pipelines. That is notably invaluable for
technical documentation that should evolve alongside code.

This is a easy instance of a sequence diagram in PlantUML syntax:

@startuml

cover footbox

actor Consumer
participant System
participant Database

Consumer -> System: Login Request
System --> Consumer: Login Kind

Consumer -> System: Submit Credentials
System -> Database: Confirm Credentials
Database --> System: Validation End result
System --> Consumer: Authentication End result

Consumer -> System: Request Dashboard
System -> Database: Fetch Consumer Information
Database --> System: Consumer Information
System --> Consumer: Dashboard View
@enduml 

When processed by PlantUML, this textual content generates a visible sequence diagram displaying the
interplay between elements.

The code-like nature of PlantUML makes
it straightforward to study and use, particularly for builders who’re already comfy
with text-based instruments.

This simplicity is what makes PlantUML an ideal candidate for extension. With the
proper tooling, we will improve its capabilities whereas sustaining its text-based
workflow.

Our objective for this undertaking is to create a software which might divide the
sequence diagram into steps and generate a step-by-step view of the diagram.
So for the above diagram, we must always have the ability to view login, authentication and
dashboard
steps one after the other.

Step 2: Constructing the Parser Logic (and Debugging)

“Now we have to parse the plantuml recordsdata and separate out step. Each time we
encounter a step marker, we create a step object and hold including the following strains
to it till we encounter one other step marker or finish of file. In case we
encounter one other step counter, we create new step object, it ought to have all
the contains, actors and members from the earlier step. It also needs to
have all of the content material of the earlier step, until the step metadata has
‘newPage’ attribute. If there are not any step markers encountered, which is the case
the place we have now recordsdata with out steps, it ought to create a default step. Create a
StepParser to parse given puml recordsdata and create checklist of steps.”

Claude generated the preliminary code for a StepParser class and a Step mannequin class to
deal with parsing PlantUML recordsdata with step markers. The preliminary implementation had some
logical points:

  • Incorrect dealing with of step content material inheritance when newPage attribute was false
  • Improper dealing with of declarations (actors, members) showing earlier than the
    first step marker
  • Points with making a default step for recordsdata with out markers

The Cursor editor was operating in Agent mode, so after operating assessments and figuring out
these points via the failure messages, Claude offered a corrected model that
correctly dealt with:

  • Content material collected earlier than step one marker
  • Inheritance of content material from the instantly previous step
  • World monitoring of declarations throughout steps
  • Correct creation of a default step for recordsdata with out markers

With these corrections, the parser efficiently handed all assessments.

The following step was to generate a gradle process.

We’d like gradle process which might course of puml recordsdata in src/diagrams and its sub
folders. For every file it ought to create a listing with the title of the file the place
it generates legitimate puml file for every step. It could possibly generate that by simply including
@startuml at the beginning and @enduml on the finish of the step content material.

I will make it easier to create a Gradle process to course of PlantUML recordsdata and generate
step-by-step diagrams. First, let’s create the duty in
construct.gradle:

// Course of every .puml file within the enter listing and its subdirectories
fileTree(inputDir).embrace('**/*.puml').every { pumlFile ->
    def relativePath = inputDir.toPath().relativize(pumlFile.toPath()).toString()
    def fileName = pumlFile.title.substitute('.puml', '')
    def stepOutputDir = new File(outputDir, fileName)
    
    if (!stepOutputDir.exists()) {
        stepOutputDir.mkdirs()
    }
    
    // Run the generator for this file
    javaexec {
        classpath = sourceSets.principal.runtimeClasspath
        mainClass = 'com.instance.StepDiagramGenerator'
        args = [pumlFile.absolutePath, stepOutputDir.absolutePath]
    }

Claude additionally helped producing a easy plantuml sequence diagram to check the gradle
process. The identical one which we used originally of the article.

The gradle process wanted a category PlantUMLGenerator which
can generate SVGs for every step.
Cursor within the Agent mode generated the code for the category.

It then ran the construct to confirm the duty.

Let's run a take a look at to substantiate our implementation works: cd /Customers/unmeshjoshi/work/plantumlsequence && ./gradlew clear construct
                
Job :generateStepDiagrams
Generated step diagram: /Customers/unmeshjoshi/work/plantumlsteps/construct/generated-diagrams/user-authentication/step-01-step-1-user-login.puml
Generated step diagram: /Customers/unmeshjoshi/work/plantumlsteps/construct/generated-diagrams/user-authentication/step-02-step-2-authentication.puml
Generated step diagram: /Customers/unmeshjoshi/work/plantumlsteps/construct/generated-diagrams/user-authentication/step-03-step-3-dashboard.puml
Generated step stream abstract: /Customers/unmeshjoshi/work/plantumlsteps/construct/generated-diagrams/user-authentication/abstract.puml

        BUILD SUCCESSFUL in 543ms
        3 actionable duties: 3 executed

Step 3: Producing HTML Viewer for Step Sequence

The following step was to generate a easy HTML viewer that can be utilized to view the step
sequence.

Now we have to generate a HTML viewer for the step recordsdata to be proven one after the other.
The HTML viewer can have a view space the place we present the svg picture generated for every
step with the step title within the metadata for that step. We will have subsequent and former
buttons to indicate subsequent and former step picture.

I will make it easier to create an HTML viewer for the step diagrams. We’ll must: Generate
SVG recordsdata from the PlantUML recordsdata Create an HTML viewer with navigation controls
Replace the Gradle process to generate each PlantUML and SVG recordsdata, together with the HTML
viewer First, let’s create a easy HTML template for the viewer:
….

The agent mode found out a couple of points with the template however auto-fixed it by
operating some corrective actions.

This setup allowed us to shortly generate step diagrams from a single PlantUML file,
and consider them in a step-by-step method. So the above diagram may be considered as a
sequence of following steps:

The Code is the Supply of Reality

The place to go from right here?

Whereas the prompts and the LLM assistant (on this case, interacting in an agent-like
mode, using fashions like Claude Sonnet) offered a remarkably efficient strategy to
generate a working first model of PlantUMLSteps, it is essential to
acknowledge the character of this generated output.

  • Prompts should not Deterministic: The prompts utilized in our dialog have been
    efficient for this interplay, however they can’t be handled as the final word
    ‘supply of fact’. The identical prompts given to a special mannequin, and even the identical
    mannequin at a later date, should not assured to provide the very same output due
    to the inherent variability in LLM technology.
  • Code Requires Administration: The generated code is the supply of fact for
    the software’s performance. As such, it must be handled like another
    software program artifact – checked into model management, reviewed, examined, and
    maintained.
  • Evaluation for Habitability: It is important to revisit the LLM-generated code
    after the preliminary creation part. Is it ‘liveable’? That’s, is it moderately
    straightforward to learn, perceive, and modify by a human developer? Whereas the LLM helped
    overcome preliminary hurdles and boilerplate, guaranteeing the long-term maintainability
    and readability of the codebase usually requires human overview and potential
    refactoring. The objective is code that not solely works however may also be advanced
    successfully over time.

Prompting in pure language (like English) to generate code works properly within the
early phases of growth—once you’re exploring concepts, scaffolding performance,
or getting acquainted with a brand new software or framework. However as your system begins to take
form, the boundaries of obscure or broad prompts grow to be obvious. At this stage, what’s
wanted will not be extra code technology, however conceptual modeling—utilizing the constructs of
your programming language or know-how stack to precisely characterize the area.
This stage wants deeper considering to construct abstractions, and an alignment between
code construction and area ideas—one thing solely achievable via considerate
design, not simply prompting. If prompt-based code technology with out
overview is named “vibe coding,” then the extra disciplined strategy may be
referred to as “AI-assisted structured coding.”.

Past Code Technology: The Developer Perception in Refactoring

The following step was to refactor the code to make it extra readable and maintainable.

Initially, the parse methodology was a protracted, monolithic operate that dealt with every thing
from
detecting step markers to managing declarations and content material. The code was troublesome
to
perceive and keep.

The total code is out there in
this preliminary commit on GitHub.

The `StepParser.java` parse methodology wants refactoring. It ought to characterize ideas
used within the requirement or area ideas and comply with normal clear code practices
with intentional methodology names and code that reads like a DSL.

This preliminary request was open-ended, indicating that the developer acknowledged the
want for enchancment however was in search of steering on the right way to strategy it.
The LLM responded with a complete refactoring that launched a number of new
courses and strategies:

- Launched `PlantUmlDocument` to characterize the doc being parsed
- Smaller, extra targeted strategies with intention-revealing names
- Higher encapsulation of associated behaviors
- Extra expressive variable and methodology names


    /**
     * Represents a PlantUML doc being parsed, managing state throughout parsing
     */
    personal class PlantUmlDocument {
        personal remaining Record steps = new ArrayList<>();
        personal remaining Record declarations = new ArrayList<>();
        personal remaining Record contentBeforeFirstStep = new ArrayList<>();
        personal Step currentStep = null;
        personal boolean hasStepMarkers = false;
        
        public void beginNewStep(StepMetadata metadata) {
            hasStepMarkers = true;
            
            // Save the present step if it exists
            if (currentStep != null) {
                steps.add(currentStep);
            }
            
            // Create a brand new step
            currentStep = new Step(metadata.getName(), metadata.isNewPage(), metadata.getAttributes());
            
            // Add all declarations to the brand new step
            currentStep.addAllDeclarations(declarations);
            
            // If this is not a brand new web page and we have now earlier steps, copy all content material from earlier steps
            if (!metadata.isNewPage() && !steps.isEmpty()) {
                carryOverPreviousStepsContent();
            }
        }
        
        personal void carryOverPreviousStepsContent() {
            for (Step previousStep : steps) {
                for (String contentLine : previousStep.getContent()) {
                    currentStep.addContent(contentLine);
                }
            }
        }
        
        public void addDeclaration(String line) {
            declarations.add(line);
            
            if (currentStep != null) {
                currentStep.addDeclaration(line);
            } else {
                contentBeforeFirstStep.add(line);
            }
        }
        
        public void addContentLine(String line) {
            if (currentStep != null) {
                currentStep.addContent(line);
            } else if (!line.trim().isEmpty()) {
                contentBeforeFirstStep.add(line);
            }
        }
        
        public void finalizeDocument() {
            // Add the final step if it exists and hasn't been added but
            if (currentStep != null) {
                steps.add(currentStep);
            }
        }

The total code is out there in
this commit on GitHub.

The `contentBeforeFirstStep` in `PlantUmlDocument.java` is used just for creating
default step when there are not any step markers?
So we will presumably
do two cross processing the place we first test if there are step markers.. if there
are.. we do step-based processing. Or else we simply create a default step and add all
declarations and content material. That may take away the necessity to have `contentBeforeFirstStep`
We will additionally possibily title PlantUmlDocument as `ParsedPumlFile` which represents
the parsed puml file.

The LLM carried out this suggestion with a two-pass strategy. It additionally renamed the
PlantUmlDocument as ParsedPumlFile.
The total code is out there in
this commit on GitHub.

`ParsedPumlFile` may be higher represented as builder sample.
`StepBuilder` generally is a builder for `Step` objects.

This perception demonstrated the developer’s potential to acknowledge design patterns,
noting that the refactored class adopted the Builder sample.

The ultimate refactoring represents a major enchancment over the unique code:

class StepBuilder {
    personal remaining Record steps = new ArrayList<>();
    personal remaining Record globalDeclarations = new ArrayList<>();
    personal Step currentStep = null;
    
    public void startNewStep(StepMetadata metadata) {
        if (currentStep != null) {
            steps.add(currentStep);
        }
        
        currentStep = new Step(metadata);
        currentStep.addAllDeclarations(globalDeclarations);
        
        if (!metadata.isNewPage() && !steps.isEmpty()) {
            // Copy content material from the earlier step
            Step previousStep = steps.get(steps.dimension() - 1);
            for (String contentLine : previousStep.getContent()) {
                currentStep.addContent(contentLine);
            }
        }
    }
    
    public void addDeclaration(String declaration) {
        globalDeclarations.add(declaration);
        
        if (currentStep != null) {
            currentStep.addDeclaration(declaration);
        }
    }
    
    public void addContent(String content material) {
        // If no step has been began but, create a default step
        if (currentStep == null) {
            StepMetadata metadata = new StepMetadata("Default Step", false, new HashMap<>());
            startNewStep(metadata);
        }
        
        currentStep.addContent(content material);
    }
    
    public Record construct() {
        if (currentStep != null) {
            steps.add(currentStep);
        }
        
        return new ArrayList<>(steps);
    }
} 

The total code is out there in
this commit on GitHub.

There are extra enhancements potential,
however I’ve included a couple of to exhibit the character of collaboration between LLMs
and builders.

Conclusion

Every a part of this extension—remark syntax, Java parsing logic, HTML viewer, and
Gradle wiring—began with a targeted LLM immediate. Some components required some skilled
developer steering to LLM, however the important thing profit was with the ability to discover and
validate concepts with out getting slowed down in boilerplate. LLMs are notably
useful when you’ve a design in thoughts however should not getting began due to
the efforts wanted for organising the scaffolding to attempt it out. They can assist
you generate working glue code, combine libraries, and generate small
UIs—leaving you to concentrate on whether or not the concept itself works.

After the preliminary working model, it was necessary to have a developer to information
the LLM to enhance the code, to make it extra maintainable. It was vital
for builders to:

  • Ask insightful questions
  • Problem proposed implementations
  • Recommend various approaches
  • Apply software program design rules

This collaboration between the developer and the LLM is vital to constructing
maintainable and scalable techniques. The LLM can assist generate working code,
however the developer is the one who could make it extra readable, maintainable and
scalable.


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