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Show HN: Arcaide – Explore code with multi-level call graphs

arcaide.foo

25 points by aqula a month ago · 15 comments · 2 min read

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One of the things I do when approaching a new codebase is to find the entry points and start exploring down the call paths. This gives a good overview of the different components in the code and how they're connected. I wanted to translate that to a visual experience, similar to how you would use call graphs, but there's a couple of problems with classical call graphs. One, call graphs represent flow at the function level, so the architectural context is lost. And call graphs tend to get very large and can grow exponentially with program size.

The approach I'm exploring is to construct "multi-level" call graphs. These are call graphs represented in the form of program structure showing control flow not just at the function level, but rolled up to higher level units such as classes and packages. This gives you the ability to zoom in and out and see your code at different levels of abstraction, à la C4 diagrams, allowing you to navigate large graphs by expanding the areas you care about and collapsing the rest.

The graph is then fed to an LLM for semantic analysis. This does two things, detects telemetry, trivial utilities to strip them out of the graph further condensing it, and identifies external interfaces and dependencies to enrich the graph. The result is a single graph which incorporates both structural and behavioral aspects. You can see package level dependencies, class composition and relationships, as well as external services, databases and user interactions. Think of it as a package diagram + class diagram + use case diagram combined into a single composite diagram.

Of course, ultimately source is king. There is no substitute for reading code to understand the details of what it is doing. But a map doesn't replace the terrain, it tells you where to walk. As we shift from hand coding each line to orchestrating agents that are generating all the code, maintaining the "big picture" becomes ever more important. We need better maps to help us navigate the terrain.

I would love to hear what you think though. Do check out some of the example diagrams in the link [1] and share your feedback. Also interested in your general thoughts on program comprehension!

[1] Link: https://arcaide.foo

ramon156 a month ago

I love this! It's relatively simplistic and would be a really fun tool to use during lectures.

billyp-rva a month ago

It's a bit like a (simplified) version of Ilograph[0]. Are these editable, or strictly LLM-generated?

[0] https://www.ilograph.com

  • aqulaOP a month ago

    They're generated from source code using a combination of static analysis + llm analysis. They're not editable per se, but you can update them when you edit your code.

    • xamde a month ago

      I think you found a very good prompt/technique to extract mostly the high level stuff without making the diagrams too complicated. And then elk.js seems to do the layout.

      Deepwiki.com also has some usable autogenerated architecture diagrams worth a look.

actionfromafar a month ago

I wish something like this could trace also data flow in a program.

darkro a month ago

This looks really cool! I’ve piddled with something like this using mermaid charts, but this takes it up a level. Do you offer access to the code behind the tool?

mtsNews a month ago

How does it decide which call graphs to include? In a typical project there can be many and these graphs seem to be a small subset.

  • aqulaOP a month ago

    It identifies telemetry, accessors, and other trivial code and strips them out of the graph. The idea is to retain architecturally relevant parts of the code.

xamde a month ago

Consider to let the user export the graph itself and convert/use it elsewhere.

otaviodev a month ago

How u make this??

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