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Arcaide

Explore code with multi-level call graphs

Details

External ID
48845142
Source
HN
Company
—
Product
Arcaide
Website domain
arcaide.foo
Launched
July 9, 2026
Cohort
—
Upvotes
25
Upvotes percentile
0.7592592592592593
Tags
—
Fetched at
Sept. 7, 2026, 9:26 p.m.
Updated at
Sept. 7, 2026, 9:26 p.m.

Description

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

Enrichment

Theme
AI agent frameworks and developer tools
Vertical
Horizontal
Function
Dev tools
Audience
Developer
AI stance
Not AI
Project type
Commercial product
Normalized one-liner
code exploration tool with call graphs
Manually corrected
False

Could you build this?

Partial Creating the visual node-graph interface is easily vibe-coded, but statically tracing multi-level call graphs accurately across diverse language constructs requires specialized static analysis.

What it would actually take: A production version needs an analysis backend using Tree-sitter or compiler frontends (such as Clang, Roslyn, or TypeScript compiler APIs) combined with a graph visualizer like React Flow or Cytoscape. The core difficulty lies in resolving dynamic dispatch, interfaces, higher-order functions, and inter-module dependencies without running the code. Building this requires expertise in compiler design, AST manipulation, and control-flow/call-graph algorithms.

Discussion

14 comments analyzed.

Competitors mentioned: Mermaid charts, Ilograph, Deepwiki.com

Concerns raised: Diagrams not editable, only LLM-generated from source code, Unclear filtering logic for which call graphs to include

Feature requests: Export graph for use/conversion elsewhere, Data flow tracing in addition to call graphs, Code access/API for the tool

Competitors

Other products that read as similar to this one — 51 launches clear the similarity bar, closest 8 shown.

Attention rank: #12 of 52 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 245 days after the earliest competitor.

Other launches for this product

Same idea, different domain

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