Implement Fuzzy Search for Duplicate Issue Detection

[dkargatzis]

Objective

Integrate a fuzzy search algorithm into the GitHub Action to detect and prevent the creation of duplicate issues based on similarities in their titles and descriptions.

Details

• Algorithm Choice: Utilize the Levenshtein distance or Jaccard Index to measure the similarity between the title and description of the new issue and existing issues in the repository.
• Threshold Setting: Define a similarity threshold to determine when an issue is considered a duplicate. Issues surpassing this threshold will not be created, and a reference to the existing similar issue will be provided instead.
• Implementation Considerations:
  • Ensure that the search algorithm does not significantly impact the execution time of the action.
  • Handle edge cases where the issue descriptions or titles are exceptionally long or contain special formatting.
• Quality Assurance: Include tests to validate the accuracy and efficiency of the fuzzy search implementation. Ensure that the feature does not interfere with the existing functionalities of the GitHub Action.

Benefits

• Reduced Redundancy: Minimize duplicate issues, making the issue tracker easier to manage and navigate.
• Enhanced Efficiency: Save time for developers and maintainers by automatically preventing duplicate issue submissions.
• Improved Issue Management: Streamline issue management processes by automatically identifying and referencing similar existing issues.

[warestack-dev]

This is a test comment to verify the commenting functionality.