Identify if code has dead code using AI

Below is a free classifier to identify if code has dead code. Just input your text, and our AI will predict if the code contains dead code - in just seconds.

if code has dead code identifier

API Access


import nyckel

credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("if-code-has-dead-code", "your_text_here", credentials)
            

fetch('https://www.nyckel.com/v1/functions/if-code-has-dead-code/invoke', {
    method: 'POST',
    headers: {
        'Authorization': 'Bearer ' + 'YOUR_BEARER_TOKEN',
        'Content-Type': 'application/json',
    },
    body: JSON.stringify(
        {"data": "your_text_here"}
    )
})
.then(response => response.json())
.then(data => console.log(data));
            

curl -X POST \
    -H "Content-Type: application/json" \
    -H "Authorization: Bearer YOUR_BEARER_TOKEN" \
    -d '{"data": "your_text_here"}' \
    https://www.nyckel.com/v1/functions/if-code-has-dead-code/invoke
            

How this classifier works

To start, input the text that you'd like analyzed. Our AI tool will then predict if the code contains dead code.

This pretrained text model uses a Nyckel-created dataset and has 2 labels, including Does Not Have Dead Code and Has Dead Code.

We'll also show a confidence score (the higher the number, the more confident the AI model is around if the code contains dead code).

Whether you're just curious or building if code has dead code detection into your application, we hope our classifier proves helpful.

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Need to identify if code has dead code at scale?

Get API or Zapier access to this classifier for free. It's perfect for:



  • Code Quality Assessment: This function can be integrated into continuous integration and deployment (CI/CD) pipelines to automatically assess the quality of the code. By identifying dead code, developers can ensure that the codebase remains clean and maintainable.

  • Legacy Code Refactoring: Software teams can use this function to identify and remove dead code from legacy systems. This improves the overall performance and readability of the system while easing future upgrades and maintenance.

  • Technical Debt Management: Organizations can incorporate this text classification function into their technical debt management strategy. By regularly detecting and addressing dead code, teams can proactively reduce technical debt and improve software sustainability.

  • Code Review Automation: Integrating this tool into code review processes can help automate the detection of dead code. It assists reviewers in focusing on the more relevant aspects of the code while ensuring that unnecessary code is flagged for removal.

  • Security Audits: This function can be utilized during security assessments to identify areas of code that may pose security risks due to being redundant or obsolete. Removing dead code can help minimize attack surfaces and enhance overall application security.

  • Documentation Improvement: By identifying dead code, teams can better align their code documentation with the actual functioning codebase. This ensures that documentation remains accurate and relevant, which is crucial for onboarding new developers or handovers.

  • Performance Optimization: Teams can leverage this function to enhance application performance by removing dead code that unnecessarily increases the code size or execution path. Streamlining the codebase contributes to faster execution times and improved user experiences.

Want this classifier for your business?

In just minutes you can automate a manual process or validate your proof-of-concept.

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