bridges
Generic Description
Find edges whose removal disconnects the graph.
Simple example:
CALL nexyron.bridges()
Structural diagnostic procedures find articulation points, bridges, cores, and other graph-shape features. They are useful for resilience, dependency risk, and graph cleaning.
Consumer-Level Explanation
Use bridges when find edges whose removal disconnects the graph is the graph-analysis or operational question you actually need to answer. Keep the call explicit because its YIELD columns, row grain, and required runtime state determine how the rest of the Cypher pipeline can safely compose it. These procedures identify structural risk or cohesion, but the result is only meaningful when the relationship type and direction match the real dependency being modeled.
Conceptual Explanation
bridges should be read as one named procedure contract in the broader Nexyron Cypher surface. The procedure call is not only a syntax hook: it defines what runtime state, projection, registry entry, or graph algorithm is being asked to operate, and it determines which output columns downstream YIELD, WITH, and RETURN stages can safely use.
More Detailed Explanation
Bridges are the relationship counterpart to articulation points
In practical queries, start by deciding the row grain you want after the call: one row per node, one row per path, one row per registry object, one row per artifact, or one row per summary. Then keep that grain explicit with YIELD and named projections. That is the difference between a useful planner-facing example and a vague call that downstream tooling cannot safely compose. For contract-driven procedures, the executable examples on these pages intentionally inspect procedure metadata unless the required named artifacts are created in the same example.
How It Differs From Nearby Algorithms
Bridges are the relationship counterpart to articulation points.
Advanced Example
This example yields named columns from bridges and returns a bounded result shape that downstream planner tooling can compose without guessing column names or row grain.
CALL nexyron.bridges() YIELD source, target
RETURN source, target
LIMIT 10
Real Use Cases
- critical-link detection
- network fragility analysis
- handoff-path diagnostics
- compare algorithm output with domain labels or time windows before operationalizing it
- feed graph-analytic scores into ranked reports, feature contracts, or investigation queues only after checking the modeling assumptions
Real Limitations And Tradeoffs
- says little about weighted importance beyond structural necessity
- algorithm output reflects the projected graph, not an abstract real-world network outside the data model
- nearby algorithms can answer different questions even when their output columns look similar