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Show HN: Automated CodeReview using AI and NLP(github.io)

34 points by autocodecritic 1 year ago | flag | hide | 14 comments

  • user1 1 year ago | next

    This is really interesting! I've been looking for a tool like this for my team.

    • author 1 year ago | next

      Thanks for the interest! Let me know if you have any questions.

      • author 1 year ago | next

        We've achieved an accuracy of around 80% in our tests, which is quite good for the complexity of the task. However, we're always working on improving it and making it more robust to different coding styles and languages.

      • user5 1 year ago | prev | next

        What programming languages do you support?

        • author 1 year ago | next

          We currently support Java, Python, and C#. However, our pipeline is designed to be language-agnostic, so it's relatively easy for us to add new languages.

    • user2 1 year ago | prev | next

      What kind of NLP techniques are you using for the code review?

      • author 1 year ago | next

        We're using a combination of word embeddings and sequence-to-sequence models for the code review. We're also using rule-based techniques for some specific cases.

      • user3 1 year ago | prev | next

        I'm not familiar with those techniques. Could you elaborate more on how they work and what the benefits are?

        • author 1 year ago | next

          Sure. Word embeddings allow us to represent words as vectors and capture their semantic relationships. Sequence-to-sequence models are neural networks that learn to map input sequences to output sequences, which is useful for translation and summarization tasks. In our case, we're using these models to learn patterns and relations between healthy and unhealthy code snippets.

  • user6 1 year ago | prev | next

    How do you deal with false positives and negatives?

    • author 1 year ago | next

      Great question. We've implemented a feedback mechanism where developers can confirm or reject the suggestions of the system. This helps us to learn from their expertise and improve our models.

  • user7 1 year ago | prev | next

    Have you considered open-sourcing your project?

    • author 1 year ago | next

      Yes, we've been thinking about it for some time now, and we're currently preparing our codebase to make it more accessible to the community. Stay tuned!