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perf(GraphDiameterAnalyzer): array-based BFS eliminates per-source allocations - #111
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…tion Replace per-vertex HashMap-based BFS (via GraphUtils.bfsDistances) with a single pre-built int[][] adjacency list and reusable int[] distance/queue arrays across all BFS passes. This eliminates: - V HashMap<String,Integer> allocations (one per source vertex) - V^2 String hashing operations inside BFS - V^2 Integer autoboxing operations - V LinkedList<String> queue allocations The same optimisation pattern is already used in NodeCentralityAnalyzer and PageRankAnalyzer. For a 1000-node component this reduces GC pressure from ~1000 HashMap + LinkedList allocations to 0 per-source allocations.
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Problem
GraphDiameterAnalyzer.analyze()callsGraphUtils.bfsDistances()once per vertex in the largest component. Each call allocates a newHashMap<String, Integer>andLinkedList<String>, and performs String hashing + Integer autoboxing inside the BFS loop.For a component of V vertices and E edges, this means:
Fix
Pre-build an
int[][]adjacency list once from the graph, then reuseint[] distandint[] queuearrays across all V BFS passes — zero per-source allocations.This is the same optimisation pattern already used in
NodeCentralityAnalyzer.computeBetweennessAndCloseness()andPageRankAnalyzer.compute().Impact
For a 1000-node component: eliminates ~1000 HashMap + LinkedList creations and ~1M autoboxing operations per analysis run. The algorithmic complexity remains O(V·(V+E)) but with dramatically lower constant factors and GC pressure.