While learning Go concurrency, I wanted a fun project to apply it to. So I built a tool that analyzes walking binary trees, comparing them, and finding differences all in parallel. It also exposes live performance metrics so I can see how well everything runs under the hood.

• Spawns goroutines to walk and compare trees concurrently.

• Uses channels to pass values and diff messages between routines.

• Relies on sync.WaitGroup to coordinate task completion.

• Applies sync.Mutex to safely update shared performance counters.

• Runs a simple HTTP server to expose runtime metrics.

⚡ Pros:

• High Performance: Makes full use of Go's lightweight goroutines and scheduler.

• Smart Error Handling: Graceful exits with context cancellation & timeouts.

• Built in Observability: Exposes real-time metrics through an HTTP endpoint.

• Clean Concurrency: Uses channels and mutexes to avoid common race bugs.

📦 Cons:

• Verbosity in Walk: The time.Sleep calls in Walk are there for demonstration purposes (to see context cancellation more clearly), but in a real-world scenario, they would be removed to maximize performance.

If I was to continue developing this:

• Configurable Tree Generation: Allow users to specify tree size or structure more flexibly.
• Comparative Benchmarking: Implement different tree traversal algorithms (e.g., BFS, DFS) and benchmark their performance using the existing metrics system to compare their efficiency.
• Interactive Web UI: Instead of just a raw /metrics endpoint, build a simple web UI to display metrics in real-time within the browser using websockets or periodic AJAX requests.