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Roadmap

This document outlines the planned evolution of the d-Heap Priority Queue project.

Philosophy

Each milestone follows a deliberate sequence:

  1. Validate before expanding — Prove existing implementations work in real algorithms before adding new languages
  2. Fill ecosystem gaps — Prioritize languages where quality d-ary heap libraries don't exist
  3. Teach by example — Demonstrate why d-ary heaps matter through canonical use cases

Current Status

v2.2.0 — Core implementations complete for C++, Rust, Zig, and TypeScript.

v2.2.0 — Examples Infrastructure + TypeScript Dijkstra

Why start here?

Dijkstra's shortest path algorithm is the canonical reason d-ary heaps exist. It performs many more decrease_priority operations than pop operations on dense graphs. A 4-ary heap reduces decrease_priority from O(log₂n) to O(log₄n)—a measurable win.

Starting with TypeScript enables:

  • Fast iteration — No compilation step; instant feedback
  • NPM momentum — The TypeScript library is already published; users need a usage example
  • Visualization groundwork — A future React-based visualization can import this example directly

Deliverables

  • examples/ directory structure
  • examples/dijkstra/README.md — Algorithm explanation and complexity analysis
  • examples/dijkstra/graphs/small.json — Shared test graph (used by all languages)
  • examples/dijkstra/TypeScript/ — Working implementation
  • benchmarks/ directory scaffold (populated in v2.4.0)

v2.3.0 — Go Implementation

Why Go? Why now?

Research revealed the only existing Go d-ary heap library lacks decrease_priority and O(1) item lookup—the very features that make d-ary heaps useful for graph algorithms.

Adding Go after the TypeScript example (rather than before) means:

  • The example pattern exists — Dijkstra structure is already defined
  • Architecture is validated — go.work setup tested with a real use case
  • Different audience reached — Go developers ≠ TypeScript developers

Deliverables

  • Go/ — Full implementation with API parity
  • go.work — Workspace configuration for local development
  • examples/dijkstra/Go/ — Dijkstra implementation
  • Published on pkg.go.dev

v2.4.0 — Complete Dijkstra Examples

Why wait for the other languages?

By this point, both the example structure and a new language integration have been battle-tested. Completing the remaining examples becomes straightforward.

Same algorithm, same graph, five languages—ideal for:

  • Learning — Compare idiomatic patterns across languages
  • Benchmarking — Measure d=2 vs d=4 vs d=8 performance
  • Credibility — Proves the unified API works everywhere

Deliverables

  • examples/dijkstra/Cpp/
  • examples/dijkstra/Rust/
  • examples/dijkstra/Zig/
  • benchmarks/scripts/ — Benchmark runners for each language
  • benchmarks/results/ — Comparative data (d=2 vs d=4 vs d=8)
  • Updated README with complete examples matrix

Future Considerations

The following are under consideration but not yet scheduled:

Item Description
Julia implementation No d-ary heap exists in the Julia ecosystem—significant gap
React Flow visualization Interactive step-through of Dijkstra with animated heap operations
Additional examples Prim's MST, A* search, event-driven simulation
Performance benchmarks Formal benchmarks with reproducible methodology

Contributing

Interested in helping? Open an issue to discuss.

Feedback on this roadmap is welcome—open an issue titled [Roadmap] with your thoughts.