BFS Traversal
BFS traversal is a graph search method that explores connections level by level, starting from a chosen node.
BFS starts at one node and first visits all the nodes one step away, then all the nodes two steps away, and so on. Because it expands outward evenly, it’s often used when you want the “closest” path in terms of number of steps.
In exchange-rate systems, a graph can represent assets and the trusted rates between them. BFS traversal can help find a reasonable path to connect two assets when a direct market is missing.
Why It Matters
BFS traversal is a practical tool for building cross-asset conversions because it helps find short paths that reduce compounding error.
When is BFS better than other graph searches?
BFS is a good fit when each edge is treated as “one step” and you care about using as few steps as possible. It also works well when you want predictable exploration that doesn’t depend on complex weighting. If you need to prefer certain edges based on quality scores or costs, other algorithms may be more appropriate.
How does BFS reduce errors in cross-rate calculations?
Every extra step in a conversion path can add noise and increase the chance of using a weak market. By preferring fewer hops, BFS-style paths can reduce the amount of chaining needed. That doesn’t guarantee accuracy, but it can be a sensible default when combined with strong data quality rules.
Real-World Example
To derive TOKEN/EUR, a system might not have a direct TOKEN/EUR market. BFS finds a short path like TOKEN/USDT → USDT/EUR and uses that to compute the cross rate.
BFS Traversal and Exchange Rates API
When exchange rates are built from a network of linked markets, traversal methods matter. CoinAPI’s Exchange Rates API uses graph concepts to connect assets and generate cross-asset rates.