Show HN: AI that reads and explains complex code naturally, like a human

by codeenlighteneron 9/7/2021, 6:34:49 PM with 2 comments
  • by diskzeroon 9/7/2021, 6:53:20 PM

    This is really interesting. When I first looked at some of the examples, I initially dismissed it, but then I realized there was some additional work being done in addition to some of the more obvious interpretations..

    I ran some of my own code snippets and the results were pretty impressive. I was having a lot of fun before I got rate limited. Bummer!

    I am still not sure of the exact business case. It this for non-technical people to get a plain language explanation of the code? For junior developers? I would like to try larger chunks of code to see how the system performs.

  • by codeenlighteneron 9/7/2021, 6:38:32 PM

    Hi HN! I created this to help decipher complex game engine logic. Instead of a literal translation, what it does is get at the core ideas in the code.

    Programmers spend 30-90% of their time reading code. With Denigma, I hope to help programmers read unfamiliar code faster.

    By accident, my alpha tester group was mainly kernel and embedded developers. Surprisingly, it works well and fairly accurately on most code in obscure domains like kernel and embedded.

    When possible, it helps show what concepts are in the code. The AI model following was written to explain part of a kernel's boot process:

        - longmode - Indicates whether or not we are running in 64 bit mode
    - lv5 - Indicates whether or not we are running with L1V5 support enabled (if you're unsure what this means google "Intel VT-x" and "L1D cache")
    - pagemap - The address of our page table entry array (this is where all of our virtual addresses go)
    - x2apic - Indicates whether or not we are using an Intel X2APIC controller
    It likes to explain business logic.

    Here is part of an explanation of a C++ function, called "AttackSystem::update." The full code is next to "Focus on what's important." on the landing page, which uses two nested closures– quite complex.

        - Each attacker has an associated position and attack object which contains information about how much damage they have done to the victim so far (base_damages) as well as their cooldown timer (cooldown).
    - When an attacker's cooldown timer reaches zero they can no longer attack for another 8 frames.
    - If there are any victims then each one will be updated with their current health minus the amount of damage done by the attacker up until now (current).
    - This process repeats itself until either there are no more victims or there is only one left - when this happens then we know that our last victim was our enemy who attacked us!
    Of course, AI isn't a silver bullet. It needs sufficient context cues– such as variable names. The variable names don't need to be perfect, however– it can work with and infer the meaning of vague, single-word names in legacy code.

    I'm sure that if it can explain the code from the STIVALE2 boot protocol, it can explain simpler code!

    There's also a second landing page for product managers: https://denigma.app/for-product-manager

    Denigma isn't perfect. On code that occurs rarely in its dataset, its accuracy becomes questionable. Sometimes it takes 2-3 tries to get a good explanation. And it only understands some parts of the Linux kernel- and can't explain Verilog HDL at all. Over time with feedback, the model will get bigger and better.