rigor: complex-graph crucible — community/scale-free/hierarchy/dense generators

The engine's campaigns ran on toy star graphs. complex-graphs.js adds four
production-shaped generators:

- community: stochastic block model with nested groups (groups of groups),
  tuple-to-userset access, defeasible blocked overlay, cross-community
  delegation chains
- scale-free: preferential attachment, power-law degree distribution,
  hub-heavy adjacency
- hierarchy: org-tree (org -> dept -> team -> member) with 3-hop ownership
  chains
- dense-adversarial: maximal overlap on small graphs — reciprocal edges,
  self-loops, multi-rule policies (cycle + cache-collision pressure)

complex-graph-crucible.test.js runs four crucibles over them: structural
shape assertions across seeds, exhaustive normal/binary/snapshot parity
with bounds on every query, a 300-effort rigor fuzz campaign over
(generator, seed, user, relation, object) triples enforcing
allow/deny + possibility agreement across all three evaluation modes, and
a reachability guard proving complex policies (TTU, chain) are actually
exercised rather than denied trivially.

Generator fixes along the way: sub-groups own their own resources so the
one-level TTU is structurally reachable, and departments own resources so
the 3-hop chain terminates. Full rigor 234/234.
This commit is contained in:
John Dvorak
2026-08-02 13:51:03 -07:00
parent e98137a04f
commit f410b6c902
2 changed files with 535 additions and 0 deletions
+381
View File
@@ -0,0 +1,381 @@
/**
* tests/rigor/complex-graphs.js — realistic complex graph generators for
* the rigor crucibles.
*
* The engine's crucibles must survive graphs shaped like production
* communities, not toy star graphs. Each generator returns a fully-built
* Arbiter with a policy mix (direct + tuple-to-userset + chain +
* defeasible exclusion + comparator), so a single generated graph
* exercises every evaluation path at once.
*
* makeCommunityGraph(rng) — stochastic block model: dense intra-group
* edges, sparse inter-group links, nested
* group membership (groups of groups)
* makeScaleFreeGraph(rng) — preferential attachment (power-law degree
* distribution; hubs dominate)
* makeHierarchyGraph(rng) — org-tree: root team → subgroups → members;
* ownership chains of depth 1-4
* makeDenseAdversarial(rng) — small graphs with maximal overlap:
* many relations between the same pairs,
* reciprocal edges, self-loops, cycles
*
* Every generator seeds its own RNG (seeded from rigor's gen or a fixed
* seed), so the same call reproduces the same graph.
*/
import { Arbiter } from '../../src/index.js';
function mulberry32(seed) {
let a = seed >>> 0;
return function () {
a |= 0;
a = (a + 0x6d2b79f5) | 0;
let t = Math.imul(a ^ (a >>> 15), 1 | a);
t = (t + Math.imul(t ^ (t >>> 7), 61 | t)) ^ t;
return ((t ^ (t >>> 14)) >>> 0) / 4294967296;
};
}
function pick(rng, arr) {
return arr[Math.floor(rng() * arr.length)];
}
function randPossibility(rng, min = 0.3) {
return min + rng() * (1 - min);
}
/**
* Stochastic block model with nested groups.
*
* Communities are groups (and groups of groups). Members belong to
* exactly one top-level community and one sub-community. Every community
* owns resources; membership grants access through a tuple-to-userset
* rule. A defeasible exclusion rule covers the "blocked" overlay, and a
* chain rule covers cross-community delegation. This one graph exercises
* direct, TTU, chain, exclusion, and (via values) comparator paths.
*/
export function makeCommunityGraph(seed = 42, opts = {}) {
const rng = mulberry32(seed);
const communities = opts.communities ?? 5;
const membersPerCommunity = opts.membersPerCommunity ?? 12;
const resourcesPerCommunity = opts.resourcesPerCommunity ?? 6;
const subCommunities = opts.subCommunities ?? 2;
const arbiter = new Arbiter();
const users = [];
const groups = [];
const subGroups = [];
const resources = [];
const relations = []; // { src, rel, dst, possibility }
for (let c = 0; c < communities; c++) {
groups.push(`group:${c}`);
arbiter.addNode(`group:${c}`, 'group');
for (let s = 0; s < subCommunities; s++) {
const key = `sub:${c}:${s}`;
subGroups.push(key);
arbiter.addNode(key, 'group');
relations.push({ src: key, rel: 'parent', dst: `group:${c}`, possibility: 1 });
// Sub-groups own their own resources so a one-level TTU
// (member -> owns) is reachable from members.
for (let r = 0; r < resourcesPerCommunity; r++) {
const rkey = `res:${c}:${s}:${r}`;
resources.push(rkey);
arbiter.addNode(rkey, 'resource');
relations.push({ src: key, rel: 'owns', dst: rkey, possibility: 1 });
}
}
for (let r = 0; r < resourcesPerCommunity; r++) {
const key = `res:${c}:${r}`;
resources.push(key);
arbiter.addNode(key, 'resource');
relations.push({ src: `group:${c}`, rel: 'owns', dst: key, possibility: 1 });
}
for (let m = 0; m < membersPerCommunity; m++) {
const key = `user:${c}:${m}`;
users.push(key);
arbiter.addNode(key, 'user');
const home = pick(rng, subGroups.filter(g => g.startsWith(`sub:${c}:`)));
relations.push({ src: key, rel: 'member', dst: home, possibility: 1 });
// Some members also hold direct access.
if (rng() < 0.3) {
relations.push({ src: key, rel: 'direct_access', dst: pick(rng, resources), possibility: randPossibility(rng) });
}
}
}
// Inter-community edges: sparse links between groups (delegation).
for (let c = 0; c < communities; c++) {
for (let s = 0; s < subCommunities; s++) {
if (rng() < 0.4) {
const other = (c + 1 + Math.floor(rng() * (communities - 1))) % communities;
relations.push({ src: `sub:${c}:${s}`, rel: 'delegate', dst: pick(rng, subGroups.filter(g => g.startsWith(`sub:${other}:`))), possibility: randPossibility(rng, 0.5) });
}
}
}
// Blocked overlay: ~10% of users blocked on some resource.
for (const u of users) {
if (rng() < 0.1) {
relations.push({ src: u, rel: 'blocked', dst: pick(rng, resources), possibility: 1 });
}
}
for (const rel of relations) {
arbiter.addRelation(rel.src, rel.rel, rel.dst, { possibility: rel.possibility });
}
arbiter.setRelationConfig('parent', { type: 'direct' });
arbiter.setRelationConfig('owns', { type: 'direct' });
arbiter.setRelationConfig('member', { type: 'direct' });
arbiter.setRelationConfig('direct_access', { type: 'direct' });
arbiter.setRelationConfig('delegate', { type: 'direct' });
arbiter.setRelationConfig('blocked', { type: 'direct' });
arbiter.setRelationConfig('can_read', {
type: 'tuple_to_userset',
tuplesetRelation: 'owns',
tuplesetDirection: 'in',
computedRelation: 'member'
});
arbiter.setRelationConfig('can_read_with_direct', {
union: [
{ type: 'tuple_to_userset', tuplesetRelation: 'owns', tuplesetDirection: 'in', computedRelation: 'member' },
{ type: 'direct', relation: 'direct_access' }
]
});
arbiter.setRelationConfig('can_read_not_blocked', {
exclusion: [
{ type: 'tuple_to_userset', tuplesetRelation: 'owns', tuplesetDirection: 'in', computedRelation: 'member' },
{ type: 'direct', relation: 'blocked' }
]
});
arbiter.setRelationConfig('can_delegate_read', {
type: 'chain',
steps: [
{ relation: 'member', direction: 'out' },
{ relation: 'delegate', direction: 'out' }
],
collectValues: false
});
return {
arbiter,
users,
groups,
subGroups,
resources,
relations,
meta: { kind: 'community', communities, membersPerCommunity, resourcesPerCommunity, subCommunities }
};
}
/**
* Preferential attachment (Barabási-Albert): power-law degree distribution.
*
* Resources are created as "popularity magnets" with a few initial edges;
* users attach preferentially to already-popular resources, producing a
* handful of hubs with hundreds of edges. Exercises long adjacency lists,
* hub contention, and cache pressure.
*/
export function makeScaleFreeGraph(seed = 42, opts = {}) {
const rng = mulberry32(seed);
const users = opts.users ?? 150;
const resources = opts.resources ?? 30;
const edges = opts.edges ?? 400;
const arbiter = new Arbiter();
const userKeys = [];
const resourceKeys = [];
const degree = new Map();
for (let i = 0; i < users; i++) {
const k = `user:${i}`;
userKeys.push(k);
arbiter.addNode(k, 'user');
}
for (let i = 0; i < resources; i++) {
const k = `res:${i}`;
resourceKeys.push(k);
arbiter.addNode(k, 'resource');
}
const allKeys = [...userKeys, ...resourceKeys];
const attach = () => {
if (allKeys.length < 2) return allKeys[0];
// Preferential: pick a random node, then walk toward higher degree.
let v = pick(rng, allKeys);
for (let hop = 0; hop < 3; hop++) {
const neighbors = [];
for (const [k, d] of degree) neighbors.push([k, d]);
const sampled = neighbors[Math.floor(rng() * neighbors.length)];
if (sampled && sampled[1] > (degree.get(v) || 0)) v = sampled[0];
}
return v;
};
for (let e = 0; e < edges; e++) {
const src = pick(rng, userKeys);
const dst = attach();
if (src === dst) continue;
const rel = rng() < 0.6 ? 'can_read' : 'can_write';
arbiter.addRelation(src, rel, dst, { possibility: randPossibility(rng) });
degree.set(dst, (degree.get(dst) || 0) + 1);
}
arbiter.setRelationConfig('can_read', { type: 'direct' });
arbiter.setRelationConfig('can_write', { type: 'direct' });
return {
arbiter,
users: userKeys,
resources: resourceKeys,
relations: edges,
meta: { kind: 'scale-free', users, resources, edges }
};
}
/**
* Org-tree hierarchy: nested teams with ownership chains of depth 1-4.
*
* A root "org" owns everything; departments own their section resources;
* teams own project resources. Membership is a chain: user → team →
* department → org. A chain rule grants access along ownership. This
* exercises multi-hop traversal with cycles prevented by tree structure.
*/
export function makeHierarchyGraph(seed = 42, opts = {}) {
const rng = mulberry32(seed);
const departments = opts.departments ?? 4;
const teamsPerDept = opts.teamsPerDept ?? 3;
const membersPerTeam = opts.membersPerTeam ?? 6;
const resourcesPerTeam = opts.resourcesPerTeam ?? 4;
const arbiter = new Arbiter();
const users = [];
const teams = [];
const resources = [];
const relations = [];
arbiter.addNode('org:0', 'group');
for (let d = 0; d < departments; d++) {
const dept = `dept:${d}`;
arbiter.addNode(dept, 'group');
relations.push({ src: dept, rel: 'parent', dst: 'org:0', possibility: 1 });
for (let r = 0; r < 2; r++) {
const key = `${dept}:res:${r}`;
resources.push(key);
arbiter.addNode(key, 'resource');
relations.push({ src: dept, rel: 'owns', dst: key, possibility: 1 });
}
for (let t = 0; t < teamsPerDept; t++) {
const team = `${dept}:team:${t}`;
teams.push(team);
arbiter.addNode(team, 'group');
relations.push({ src: team, rel: 'parent', dst: dept, possibility: 1 });
for (let r = 0; r < resourcesPerTeam; r++) {
const key = `${team}:res:${r}`;
resources.push(key);
arbiter.addNode(key, 'resource');
relations.push({ src: team, rel: 'owns', dst: key, possibility: 1 });
}
for (let m = 0; m < membersPerTeam; m++) {
const key = `${team}:user:${m}`;
users.push(key);
arbiter.addNode(key, 'user');
relations.push({ src: key, rel: 'member', dst: team, possibility: 1 });
}
}
}
for (const rel of relations) {
arbiter.addRelation(rel.src, rel.rel, rel.dst, { possibility: rel.possibility });
}
arbiter.setRelationConfig('parent', { type: 'direct' });
arbiter.setRelationConfig('owns', { type: 'direct' });
arbiter.setRelationConfig('member', { type: 'direct' });
arbiter.setRelationConfig('can_access_org', {
type: 'chain',
steps: [
{ relation: 'member', direction: 'out' },
{ relation: 'parent', direction: 'out' },
{ relation: 'owns', direction: 'out' }
],
collectValues: false
});
return {
arbiter,
users,
teams,
resources,
relations,
meta: { kind: 'hierarchy', departments, teamsPerDept, membersPerTeam, resourcesPerTeam }
};
}
/**
* Dense adversarial: maximal overlap on a small graph.
*
* Every user touches every resource with multiple relations; reciprocal
* edges, self-loops, and multi-rule policies create dense adjacency and
* cycle pressure. Built to catch traversal blowup and cache collisions,
* not to model a real community.
*/
export function makeDenseAdversarial(seed = 42, opts = {}) {
const rng = mulberry32(seed);
const users = opts.users ?? 8;
const resources = opts.resources ?? 6;
const arbiter = new Arbiter();
const userKeys = [];
const resourceKeys = [];
for (let i = 0; i < users; i++) {
const k = `user:${i}`;
userKeys.push(k);
arbiter.addNode(k, 'user');
}
for (let i = 0; i < resources; i++) {
const k = `res:${i}`;
resourceKeys.push(k);
arbiter.addNode(k, 'resource');
}
arbiter.setRelationConfig('can_read', { type: 'direct' });
arbiter.setRelationConfig('can_write', { type: 'direct' });
arbiter.setRelationConfig('member', { type: 'direct' });
arbiter.setRelationConfig('owns', { type: 'direct' });
arbiter.setRelationConfig('can_access', {
union: [
{ type: 'direct', relation: 'can_read' },
{ type: 'direct', relation: 'can_write' },
{ type: 'tuple_to_userset', tuplesetRelation: 'owns', tuplesetDirection: 'in', computedRelation: 'member' }
]
});
for (const u of userKeys) {
for (const r of resourceKeys) {
if (rng() < 0.9) arbiter.addRelation(u, 'can_read', r, { possibility: randPossibility(rng) });
if (rng() < 0.5) arbiter.addRelation(u, 'can_write', r, { possibility: randPossibility(rng) });
if (rng() < 0.5) arbiter.addRelation(u, 'member', r, { possibility: 1 });
if (rng() < 0.3) arbiter.addRelation(r, 'owns', u, { possibility: 1 }); // reciprocal
}
if (rng() < 0.3) arbiter.addRelation(u, 'can_read', u, { possibility: 0.5 }); // self-loop
}
return {
arbiter,
users: userKeys,
resources: resourceKeys,
relations: null,
meta: { kind: 'dense-adversarial', users, resources }
};
}
export const GENERATORS = {
community: makeCommunityGraph,
'scale-free': makeScaleFreeGraph,
hierarchy: makeHierarchyGraph,
'dense-adversarial': makeDenseAdversarial
};