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| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 | 11x 11x 19x 19x 11x 19x 11x 11x 5x 5x 5x 5x 1x 5x 11x 11x 5x 12x 12x 5x 5x 5x 12x 5x 5x 5x 7x 7x 7x 7x 5x 5x 5x 5x 12x 12x 12x 12x 12x 12x 5x 5x 5x 11x | import type { DependencyGraph, ModuleCluster } from './types';
import { calculateFragmentation, calculateEnhancedCohesion } from './metrics';
import {
classifyFile,
adjustFragmentationForClassification,
} from './classifier';
/**
* Group files by domain to detect module clusters
* @param graph - The dependency graph to analyze
* @param options - Optional configuration options
* @param options.useLogScale - Whether to use logarithmic scaling for calculations
* @returns Array of module clusters
*/
export function detectModuleClusters(
graph: DependencyGraph,
options?: { useLogScale?: boolean }
): ModuleCluster[] {
const domainMap = new Map<string, string[]>();
for (const [file, node] of graph.nodes.entries()) {
const primaryDomain = node.exports[0]?.inferredDomain || 'unknown';
if (!domainMap.has(primaryDomain)) {
domainMap.set(primaryDomain, []);
}
domainMap.get(primaryDomain)!.push(file);
}
const clusters: ModuleCluster[] = [];
const generateSuggestedStructure = (
files: string[],
tokens: number,
fragmentation: number
) => {
const targetFiles = Math.max(1, Math.ceil(tokens / 10000));
const plan: string[] = [];
Iif (fragmentation > 0.5) {
plan.push(
`Consolidate ${files.length} files scattered across multiple directories into ${targetFiles} core module(s)`
);
}
if (tokens > 20000) {
plan.push(
`Domain logic is very large (${Math.round(tokens / 1000)}k tokens). Ensure clear sub-domain boundaries.`
);
}
return { targetFiles, consolidationPlan: plan };
};
for (const [domain, files] of domainMap.entries()) {
if (files.length < 2 || domain === 'unknown') continue;
const totalTokens = files.reduce((sum, file) => {
const node = graph.nodes.get(file);
return sum + (node?.tokenCost || 0);
}, 0);
// Calculate shared import ratio for coupling discount
let sharedImportRatio = 0;
Eif (files.length >= 2) {
const allImportSets = files.map(
(f) => new Set(graph.nodes.get(f)?.imports || [])
);
let intersection = new Set(allImportSets[0]);
const union = new Set(allImportSets[0]);
for (let i = 1; i < allImportSets.length; i++) {
const nextSet = allImportSets[i];
intersection = new Set([...intersection].filter((x) => nextSet.has(x)));
for (const x of nextSet) union.add(x);
}
sharedImportRatio = union.size > 0 ? intersection.size / union.size : 0;
}
const rawFragmentation = calculateFragmentation(files, domain, {
...options,
sharedImportRatio,
});
// Average cohesion and adjusted fragmentation for the cluster
let totalCohesion = 0;
let totalAdjustedFragmentation = 0;
files.forEach((f) => {
const node = graph.nodes.get(f);
Eif (node) {
const cohesion = calculateEnhancedCohesion(node.exports);
totalCohesion += cohesion;
const classification = classifyFile(node, cohesion);
totalAdjustedFragmentation += adjustFragmentationForClassification(
rawFragmentation,
classification
);
}
});
const avgCohesion = totalCohesion / files.length;
const fragmentationScore = totalAdjustedFragmentation / files.length;
clusters.push({
domain,
files,
totalTokens,
fragmentationScore,
avgCohesion,
suggestedStructure: generateSuggestedStructure(
files,
totalTokens,
fragmentationScore
),
});
}
return clusters;
}
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