Migrate all repos into monorepo context folders
Bahn: aisupport, Analyse-O2C-C2S, awesome-bahn-mcp-servers, beam-mcp,
Confluence_Bot, db-planet-mcp-server, O2C-Harness, project-audit,
Projekt-KIQ-HP, teamlandkarte-mcp
Dhive: Jury-Voting
Privat: CV, NoteGraph (NOTE: NoteGraph needs complete redo after consolidation)
Shared: AI-Orchestrator, OrgMyLife, power_skills_and_more
Shared/references: symphony (read-only)
Bahn repos remain available as independent remotes - this monorepo
pulls them in via subtree, the originals are untouched.
This commit is contained in:
@@ -0,0 +1,338 @@
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import { describe, it, expect } from 'vitest';
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import fc from 'fast-check';
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import { selectRelevant } from './relevance-selection';
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import { generateTandemData } from './tandem-generator';
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import type { Experience, Skill, Project, Person, Tandem } from '../schemas/types';
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// --- Arbitraries ---
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const kebabCaseId = fc
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.array(
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fc.stringMatching(/^[a-z0-9]{1,8}$/),
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{ minLength: 1, maxLength: 4 }
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)
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.map(parts => parts.join('-'));
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const isoDate = fc
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.record({
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year: fc.integer({ min: 1990, max: 2030 }),
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month: fc.integer({ min: 1, max: 12 }),
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})
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.map(({ year, month }) => `${year}-${String(month).padStart(2, '0')}`);
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const skillCategory = fc.constantFrom(
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'programming-language' as const,
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'framework' as const,
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'methodology' as const,
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'soft-skill' as const,
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'domain' as const
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);
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const skillLevel = fc.constantFrom(
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'beginner' as const,
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'intermediate' as const,
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'advanced' as const,
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'expert' as const
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);
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/** Generates a Skill entity */
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const skillArb = fc.record({
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id: kebabCaseId,
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created: isoDate,
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modified: isoDate,
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name: fc.string({ minLength: 1, maxLength: 20 }).filter(s => s.trim().length > 0),
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category: skillCategory,
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level: skillLevel,
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}).map(f => ({
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id: f.id,
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type: 'skill' as const,
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created: f.created,
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modified: f.modified,
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name: f.name,
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category: f.category,
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level: f.level,
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}));
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/** Generates an Experience entity */
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const experienceArb = fc.record({
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id: kebabCaseId,
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created: isoDate,
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modified: isoDate,
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title: fc.string({ minLength: 1, maxLength: 30 }).filter(s => s.trim().length > 0),
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organization: kebabCaseId,
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start: isoDate,
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description: fc.string({ minLength: 0, maxLength: 50 }),
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skillsUsed: fc.array(fc.string({ minLength: 1, maxLength: 15 }).filter(s => s.trim().length > 0), { minLength: 0, maxLength: 5 }),
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}).map(f => ({
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id: f.id,
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type: 'experience' as const,
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created: f.created,
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modified: f.modified,
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title: f.title,
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organization: f.organization,
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start: f.start,
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end: null,
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description: f.description,
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skillsUsed: f.skillsUsed,
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}));
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/** Generates a Project entity */
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const projectArb = fc.record({
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id: kebabCaseId,
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created: isoDate,
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modified: isoDate,
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name: fc.string({ minLength: 1, maxLength: 30 }).filter(s => s.trim().length > 0),
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organization: kebabCaseId,
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start: isoDate,
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description: fc.string({ minLength: 0, maxLength: 50 }),
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skillsUsed: fc.array(fc.string({ minLength: 1, maxLength: 15 }).filter(s => s.trim().length > 0), { minLength: 0, maxLength: 5 }),
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}).map(f => ({
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id: f.id,
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type: 'project' as const,
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created: f.created,
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modified: f.modified,
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name: f.name,
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organization: f.organization,
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start: f.start,
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description: f.description,
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skillsUsed: f.skillsUsed,
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}));
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/** Generates a Person entity */
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const personArb = fc.record({
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id: kebabCaseId,
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created: isoDate,
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modified: isoDate,
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firstName: fc.string({ minLength: 1, maxLength: 15 }).filter(s => s.trim().length > 0),
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lastName: fc.string({ minLength: 1, maxLength: 15 }).filter(s => s.trim().length > 0),
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summary: fc.string({ minLength: 0, maxLength: 50 }),
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}).map(f => ({
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id: f.id,
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type: 'person' as const,
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created: f.created,
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modified: f.modified,
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name: { first: f.firstName, last: f.lastName, display: `${f.firstName} ${f.lastName}` },
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summary: f.summary || undefined,
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skills: [] as string[],
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experiences: [] as string[],
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}));
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/** Generates a Tandem entity referencing two partner IDs */
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const tandemArb = (partner1Id: string, partner2Id: string) => fc.record({
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id: kebabCaseId,
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created: isoDate,
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modified: isoDate,
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sharedVision: fc.string({ minLength: 1, maxLength: 50 }).filter(s => s.trim().length > 0),
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complementarySkills: fc.string({ minLength: 1, maxLength: 50 }).filter(s => s.trim().length > 0),
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collaborationModel: fc.string({ minLength: 1, maxLength: 50 }).filter(s => s.trim().length > 0),
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combinedNarrative: fc.string({ minLength: 0, maxLength: 50 }),
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jointCompetencies: fc.array(fc.string({ minLength: 1, maxLength: 20 }).filter(s => s.trim().length > 0), { minLength: 0, maxLength: 3 }),
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}).map(f => ({
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id: f.id,
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type: 'tandem' as const,
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created: f.created,
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modified: f.modified,
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partners: [partner1Id, partner2Id] as [string, string],
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sharedVision: f.sharedVision,
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complementarySkills: f.complementarySkills,
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collaborationModel: f.collaborationModel,
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combinedNarrative: f.combinedNarrative || undefined,
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jointCompetencies: f.jointCompetencies.length > 0 ? f.jointCompetencies : undefined,
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}));
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// --- Property 9: CV relevance selection ordering ---
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describe('Property 9: CV relevance selection ordering', () => {
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it('matching items have score > 0 and appear before score-0 items in the output', () => {
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fc.assert(
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fc.property(
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fc.array(fc.string({ minLength: 1, maxLength: 15 }).filter(s => s.trim().length > 0), { minLength: 1, maxLength: 5 }),
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fc.array(experienceArb, { minLength: 0, maxLength: 5 }),
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fc.array(skillArb, { minLength: 0, maxLength: 5 }),
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fc.array(projectArb, { minLength: 0, maxLength: 5 }),
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(requirements, experiences, skills, projects) => {
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const results = selectRelevant(requirements, experiences, skills, projects);
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// All items with matchedRequirements.length > 0 must have score > 0
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for (const r of results) {
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if (r.matchedRequirements.length > 0) {
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expect(r.score).toBeGreaterThan(0);
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}
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}
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// Items are sorted: all score > 0 items appear before score === 0 items
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let seenZero = false;
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for (const r of results) {
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if (r.score === 0) {
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seenZero = true;
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} else if (seenZero) {
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// A non-zero score item appeared after a zero-score item — ordering violated
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expect(seenZero && r.score > 0).toBe(false);
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}
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}
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// Results are sorted by score descending
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for (let i = 1; i < results.length; i++) {
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expect(results[i - 1].score).toBeGreaterThanOrEqual(results[i].score);
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}
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}
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),
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{ numRuns: 100 }
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);
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});
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/**
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* Validates: Requirements 5.1, 5.2
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*/
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});
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// --- Property 10: Tandem application document set (exactly 3 docs) ---
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describe('Property 10: Tandem application document set', () => {
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it('generateTandemData produces data with exactly 2 partner profiles referencing both partners', () => {
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fc.assert(
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fc.property(
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personArb,
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personArb,
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fc.array(experienceArb, { minLength: 0, maxLength: 3 }),
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fc.array(experienceArb, { minLength: 0, maxLength: 3 }),
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fc.array(skillArb, { minLength: 0, maxLength: 3 }),
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fc.array(skillArb, { minLength: 0, maxLength: 3 }),
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(partner1, partner2, exp1, exp2, skills1, skills2) => {
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// Ensure distinct partner IDs
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const p1 = { ...partner1, id: partner1.id + '-p1' };
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const p2 = { ...partner2, id: partner2.id + '-p2' };
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const tandem: Tandem = {
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id: 'tandem-test',
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type: 'tandem',
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created: '2025-01-01',
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modified: '2025-01-01',
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partners: [p1.id, p2.id],
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sharedVision: 'Shared vision text',
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complementarySkills: 'Complementary skills text',
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collaborationModel: 'Collaboration model text',
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};
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const result = generateTandemData(
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tandem,
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p1 as Person,
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p2 as Person,
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exp1,
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exp2,
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skills1,
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skills2
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);
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// Exactly 2 partner profiles in the output
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expect(result.partnerProfiles).toHaveLength(2);
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// The tandem CV references both partners
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expect(result.partners).toContain(p1.id);
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expect(result.partners).toContain(p2.id);
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// Each partner profile corresponds to one of the partners
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const profileIds = result.partnerProfiles.map(p => p.personId);
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expect(profileIds).toContain(p1.id);
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expect(profileIds).toContain(p2.id);
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// The tandem data contains shared information from both profiles
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expect(result.sharedVision).toBeTruthy();
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expect(result.complementarySkills).toBeTruthy();
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expect(result.collaborationModel).toBeTruthy();
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}
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),
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{ numRuns: 100 }
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);
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});
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/**
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* Validates: Requirements 5.3, 5.4
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*/
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});
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// --- Property 11: CV output validity and traceability ---
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describe('Property 11: CV output validity and traceability', () => {
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it('all data in TandemDocumentData traces back to input entities', () => {
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fc.assert(
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fc.property(
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personArb,
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personArb,
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fc.array(experienceArb, { minLength: 1, maxLength: 4 }),
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fc.array(experienceArb, { minLength: 1, maxLength: 4 }),
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fc.array(skillArb, { minLength: 1, maxLength: 4 }),
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fc.array(skillArb, { minLength: 1, maxLength: 4 }),
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(partner1, partner2, exp1, exp2, skills1, skills2) => {
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const p1 = { ...partner1, id: partner1.id + '-p1' };
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const p2 = { ...partner2, id: partner2.id + '-p2' };
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const tandem: Tandem = {
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id: 'tandem-trace',
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type: 'tandem',
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created: '2025-01-01',
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modified: '2025-01-01',
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partners: [p1.id, p2.id],
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sharedVision: 'Vision',
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complementarySkills: 'Skills complement',
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collaborationModel: 'Model',
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combinedNarrative: 'Narrative',
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jointCompetencies: ['competency-1', 'competency-2'],
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};
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const result = generateTandemData(
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tandem,
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p1 as Person,
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p2 as Person,
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exp1,
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exp2,
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skills1,
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skills2
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);
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// All skill names in partner profiles must come from input skills
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const allInputSkillNames = [...skills1, ...skills2].map(s => s.name);
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for (const profile of result.partnerProfiles) {
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for (const skillName of profile.topSkills) {
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expect(allInputSkillNames).toContain(skillName);
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}
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}
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// All experience titles in partner profiles must come from input experiences
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const allInputExpTitles = [...exp1, ...exp2].map(e => e.title);
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for (const profile of result.partnerProfiles) {
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for (const exp of profile.topExperiences) {
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expect(allInputExpTitles).toContain(exp.title);
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}
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}
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// All organization references in experiences must come from input experiences
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const allInputOrgs = [...exp1, ...exp2].map(e => e.organization);
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for (const profile of result.partnerProfiles) {
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for (const exp of profile.topExperiences) {
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expect(allInputOrgs).toContain(exp.organization);
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}
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}
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// Display names must come from input persons
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const inputDisplayNames = [p1.name.display, p2.name.display];
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for (const profile of result.partnerProfiles) {
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expect(inputDisplayNames).toContain(profile.displayName);
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}
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// Tandem-level data must trace back to the tandem entity
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expect(result.sharedVision).toBe(tandem.sharedVision);
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expect(result.complementarySkills).toBe(tandem.complementarySkills);
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expect(result.collaborationModel).toBe(tandem.collaborationModel);
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expect(result.combinedNarrative).toBe(tandem.combinedNarrative);
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expect(result.jointCompetencies).toEqual(tandem.jointCompetencies);
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}
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),
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{ numRuns: 100 }
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);
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});
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/**
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* Validates: Requirements 5.5, 5.6
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*/
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});
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