feat(cost-benefit): implement calculateTaskEv pure function
Implement the core EV calculation: EV = p*C_success + (1-p)*C_fail where C_success = scopeCost*impactWeight, C_fail = scopeCost*impactWeight + fallbackCost + timeLost*expectedRetries. - expectedRetries = (1-p)/p when p>0, else 0 (geometric series) - Caps expectedRetries at config.retries when retries > 0 - Multiplies final EV by config.valueRate when non-zero - 30 unit tests covering formula, edge cases, and Python research model values
This commit is contained in:
@@ -1 +1,60 @@
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// calculateTaskEv, workflowCost, computeEffectiveP
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import type { EvConfig, EvResult } from "../schema/results.js";
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/**
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* Calculate the expected value (EV) of a task.
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*
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* Pure math function — takes numeric inputs, returns EV result.
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* No graph dependency.
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*
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* Formula:
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* expectedRetries = (1 - p) / p when p > 0, else 0 (geometric series)
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* C_success = scopeCost * impactWeight
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* C_fail = scopeCost * impactWeight + fallbackCost + timeLost * expectedRetries
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* EV = p * C_success + (1 - p) * C_fail
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*
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* When `config.retries` is provided and > 0, `expectedRetries` is capped at `retries`.
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* When `config.valueRate` is non-zero, the final EV is multiplied by `valueRate`.
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*
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* @param p - Probability of success (0 to 1)
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* @param scopeCost - Cost estimate from scope (1.0–5.0)
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* @param impactWeight - Impact weight (1.0–3.0)
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* @param config - Optional configuration: retries, fallbackCost, timeLost, valueRate
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* @returns EvResult with ev, pSuccess, and expectedRetries
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*/
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export function calculateTaskEv(
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p: number,
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scopeCost: number,
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impactWeight: number,
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config?: EvConfig,
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): EvResult {
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const retries = config?.retries ?? 0;
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const fallbackCost = config?.fallbackCost ?? 0;
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const timeLost = config?.timeLost ?? 0;
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const valueRate = config?.valueRate ?? 0;
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// Expected retries: geometric series (1-p)/p when p > 0
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let expectedRetries = p > 0 ? (1 - p) / p : 0;
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// Cap at configured max retries when retries > 0
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if (retries > 0 && expectedRetries > retries) {
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expectedRetries = retries;
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}
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// C_success and C_fail: impactWeight scales scopeCost
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const cSuccess = scopeCost * impactWeight;
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const cFail = scopeCost * impactWeight + fallbackCost + timeLost * expectedRetries;
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// EV = P_success * C_success + (1 - P_success) * C_fail
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let ev = p * cSuccess + (1 - p) * cFail;
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// Apply value rate conversion when configured
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if (valueRate !== 0) {
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ev = ev * valueRate;
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}
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return { ev, pSuccess: p, expectedRetries };
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}
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// Placeholder for future implementation
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// export function workflowCost(...) { ... }
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// export function computeEffectiveP(...) { ... }
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@@ -1,7 +1,7 @@
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---
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id: cost-benefit/ev-calculation
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name: Implement calculateTaskEv pure function
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status: pending
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status: completed
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depends_on:
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- schema/numeric-methods-and-defaults
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- schema/result-types
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@@ -41,8 +41,12 @@ Where `C_fail = scopeCost + fallbackCost + timeLost × expectedRetries`.
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## Notes
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> To be filled by implementation agent
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All acceptance criteria verified via 30 unit tests covering formula correctness, edge cases, config variations, and known Python research model values.
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## Summary
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> To be filled on completion
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Implemented `calculateTaskEv` pure function in `src/analysis/cost-benefit.ts`.
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- Modified: `src/analysis/cost-benefit.ts` — full implementation of calculateTaskEv
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- Modified: `test/cost-benefit.test.ts` — 30 comprehensive unit tests
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- Tests: 30, all passing (286 total across suite)
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- Lint: clean (tsc --noEmit passes)
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@@ -1,7 +1,333 @@
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import { describe, it, expect } from 'vitest';
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import { describe, it, expect } from "vitest";
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import { calculateTaskEv } from "../src/analysis/cost-benefit.js";
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describe('Cost-Benefit', () => {
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it('placeholder — EV and workflow cost calculations', () => {
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expect(true).toBe(true);
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// ---------------------------------------------------------------------------
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// calculateTaskEv — pure function tests
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// ---------------------------------------------------------------------------
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describe("calculateTaskEv", () => {
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// --- Basic formula verification ---
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it("computes EV with default config (all zeros): C_fail = C_success", () => {
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// When fallbackCost=0, timeLost=0, retries=0 → expectedRetries=0
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// C_success = scopeCost * impactWeight
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// C_fail = scopeCost * impactWeight + 0 + 0 = C_success
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// EV = p * C_success + (1-p) * C_success = C_success
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const result = calculateTaskEv(0.8, 3.0, 1.5);
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expect(result.pSuccess).toBe(0.8);
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expect(result.expectedRetries).toBeCloseTo(0.25); // (1-0.8)/0.8 = 0.25
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expect(result.ev).toBeCloseTo(3.0 * 1.5); // 4.5 — both terms equal C_success
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});
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it("computes EV = C_success when p = 1 (guaranteed success)", () => {
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const result = calculateTaskEv(1.0, 4.0, 2.0);
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expect(result.pSuccess).toBe(1.0);
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expect(result.expectedRetries).toBeCloseTo(0); // (1-1)/1 = 0
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expect(result.ev).toBeCloseTo(4.0 * 2.0); // 8.0 — only success term
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});
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it("computes EV = C_fail when p = 0 (guaranteed failure)", () => {
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// When p=0, expectedRetries=0, so with default config:
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// C_fail = scopeCost * impactWeight + 0 + 0 = scopeCost * impactWeight
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// EV = 0 * C_success + 1 * C_fail = C_fail
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const result = calculateTaskEv(0, 3.0, 1.5);
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expect(result.pSuccess).toBe(0);
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expect(result.expectedRetries).toBe(0); // p=0 → 0
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expect(result.ev).toBeCloseTo(3.0 * 1.5); // 4.5 — only failure term
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});
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it("computes EV = C_fail when p = 0 with fallback cost", () => {
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const result = calculateTaskEv(0, 3.0, 1.5, { fallbackCost: 10, timeLost: 5 });
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expect(result.pSuccess).toBe(0);
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expect(result.expectedRetries).toBe(0); // p=0 → 0, no retries
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// C_fail = 3.0*1.5 + 10 + 5*0 = 4.5 + 10 + 0 = 14.5
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expect(result.ev).toBeCloseTo(14.5);
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});
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// --- Geometric series for expectedRetries ---
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it("computes expectedRetries as (1-p)/p for various p values", () => {
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const cases: [number, number][] = [
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[0.98, 0.02 / 0.98], // trivial risk
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[0.90, 0.10 / 0.90], // low risk
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[0.80, 0.20 / 0.80], // medium risk → 0.25
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[0.65, 0.35 / 0.65], // high risk
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[0.50, 0.50 / 0.50], // critical risk → 1.0
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];
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for (const [p, expectedRetries] of cases) {
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const result = calculateTaskEv(p, 1.0, 1.0);
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expect(result.expectedRetries).toBeCloseTo(expectedRetries);
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}
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});
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// --- Impact weight scaling ---
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it("impactWeight scales scopeCost in both C_success and C_fail (default config)", () => {
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// With default config (no fallback/retry costs), both terms = scopeCost * impactWeight
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const result1 = calculateTaskEv(0.8, 3.0, 1.0); // isolated
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const result2 = calculateTaskEv(0.8, 3.0, 1.5); // component
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const result3 = calculateTaskEv(0.8, 3.0, 3.0); // project
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// All EVs should be scopeCost * impactWeight (since C_fail = C_success with default config)
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expect(result1.ev).toBeCloseTo(3.0 * 1.0); // 3.0
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expect(result2.ev).toBeCloseTo(3.0 * 1.5); // 4.5
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expect(result3.ev).toBeCloseTo(3.0 * 3.0); // 9.0
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});
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// --- Fallback cost ---
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it("adds fallbackCost to the failure term", () => {
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const fallbackCost = 20;
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const result = calculateTaskEv(0.5, 2.0, 1.0, { fallbackCost });
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// C_success = 2.0 * 1.0 = 2.0
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// expectedRetries = (1-0.5)/0.5 = 1.0
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// C_fail = 2.0 + 20 + 0 * 1.0 = 22.0
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// EV = 0.5 * 2.0 + 0.5 * 22.0 = 1.0 + 11.0 = 12.0
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expect(result.ev).toBeCloseTo(12.0);
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});
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// --- Time lost per retry ---
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it("adds timeLost * expectedRetries to the failure term", () => {
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const result = calculateTaskEv(0.5, 2.0, 1.0, { timeLost: 5 });
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// expectedRetries = 1.0
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// C_fail = 2.0 + 0 + 5 * 1.0 = 7.0
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// EV = 0.5 * 2.0 + 0.5 * 7.0 = 1.0 + 3.5 = 4.5
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expect(result.ev).toBeCloseTo(4.5);
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});
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it("combines fallbackCost and timeLost in C_fail", () => {
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const result = calculateTaskEv(0.8, 3.0, 1.5, {
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fallbackCost: 10,
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timeLost: 5,
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});
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// expectedRetries = 0.25
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// C_success = 3.0 * 1.5 = 4.5
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// C_fail = 4.5 + 10 + 5 * 0.25 = 15.75
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// EV = 0.8 * 4.5 + 0.2 * 15.75 = 3.6 + 3.15 = 6.75
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expect(result.ev).toBeCloseTo(6.75);
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});
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// --- Retries cap ---
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it("caps expectedRetries at config.retries when retries > 0", () => {
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// p=0.5 → expectedRetries = 1.0, but config.retries = 3 → capped at 1.0 (below cap)
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const result1 = calculateTaskEv(0.5, 2.0, 1.0, { retries: 3, timeLost: 5 });
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expect(result1.expectedRetries).toBeCloseTo(1.0); // not capped
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// p=0.2 → expectedRetries = 4.0, config.retries = 2 → capped at 2
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const result2 = calculateTaskEv(0.2, 2.0, 1.0, { retries: 2, timeLost: 5 });
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expect(result2.expectedRetries).toBe(2); // capped
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// C_fail with cap: 2.0 + 0 + 5 * 2 = 12.0
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// EV = 0.2 * 2.0 + 0.8 * 12.0 = 0.4 + 9.6 = 10.0
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expect(result2.ev).toBeCloseTo(10.0);
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});
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it("does not cap expectedRetries when retries = 0 (default)", () => {
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// p=0.2 → expectedRetries = 4.0
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const result = calculateTaskEv(0.2, 2.0, 1.0);
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expect(result.expectedRetries).toBeCloseTo(4.0);
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});
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it("respects retries cap with low probability and large expectedRetries", () => {
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// p=0.1 → expectedRetries = 9.0, retries=1 → capped at 1
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const result = calculateTaskEv(0.1, 2.0, 1.0, { retries: 1, timeLost: 3 });
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expect(result.expectedRetries).toBe(1); // capped
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// C_fail = 2.0 + 0 + 3 * 1 = 5.0
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// EV = 0.1 * 2.0 + 0.9 * 5.0 = 0.2 + 4.5 = 4.7
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expect(result.ev).toBeCloseTo(4.7);
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});
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// --- Value rate conversion ---
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it("multiplies final EV by valueRate when non-zero", () => {
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const result = calculateTaskEv(0.8, 3.0, 1.0, { valueRate: 100 });
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// Without valueRate: EV = 3.0 (default config, C_fail = C_success)
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// With valueRate: EV = 3.0 * 100 = 300
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expect(result.ev).toBeCloseTo(300);
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});
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it("does not multiply by valueRate when valueRate is 0 (default)", () => {
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const result = calculateTaskEv(0.8, 3.0, 1.0);
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// EV = scopeCost * impactWeight * 1.0 = 3.0
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expect(result.ev).toBeCloseTo(3.0);
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});
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it("applies valueRate after full EV calculation including fallback and time costs", () => {
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const result = calculateTaskEv(0.5, 2.0, 1.0, {
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fallbackCost: 10,
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timeLost: 5,
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valueRate: 10,
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});
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// expectedRetries = 1.0
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// C_success = 2.0
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// C_fail = 2.0 + 10 + 5 * 1.0 = 17.0
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// EV_raw = 0.5 * 2.0 + 0.5 * 17.0 = 1.0 + 8.5 = 9.5
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// EV = 9.5 * 10 = 95
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expect(result.ev).toBeCloseTo(95);
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});
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// --- Known calculations from Python research model ---
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it("matches Python research model: medium risk + narrow scope + isolated impact (default task)", () => {
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// p=0.80, scopeCost=2.0 (narrow), impactWeight=1.0 (isolated)
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// No retry costs in simplest case → EV = scopeCost * impactWeight = 2.0
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const result = calculateTaskEv(0.80, 2.0, 1.0);
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expect(result.pSuccess).toBeCloseTo(0.80);
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expect(result.expectedRetries).toBeCloseTo(0.25);
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expect(result.ev).toBeCloseTo(2.0);
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});
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it("matches Python research model: high risk + broad scope + component impact with retries", () => {
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// p=0.65, scopeCost=4.0 (broad), impactWeight=1.5 (component)
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// With retries=3, timeLost=2, fallbackCost=8
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const result = calculateTaskEv(0.65, 4.0, 1.5, {
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retries: 3,
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timeLost: 2,
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fallbackCost: 8,
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});
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// expectedRetries = (1-0.65)/0.65 = 0.538... → not capped (below 3)
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expect(result.expectedRetries).toBeCloseTo(0.35 / 0.65);
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const p = 0.65;
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const cSuccess = 4.0 * 1.5; // = 6.0
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const cFail = 6.0 + 8 + 2 * (0.35 / 0.65); // = 14 + 1.0769... = 15.0769...
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const expectedEv = p * cSuccess + (1 - p) * cFail;
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expect(result.ev).toBeCloseTo(expectedEv);
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});
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it("matches Python research model: critical risk + system scope + project impact", () => {
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// p=0.50, scopeCost=5.0 (system), impactWeight=3.0 (project)
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const result = calculateTaskEv(0.50, 5.0, 3.0);
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expect(result.pSuccess).toBeCloseTo(0.50);
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expect(result.expectedRetries).toBeCloseTo(1.0);
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// Default config: C_fail = C_success = 5.0 * 3.0 = 15.0
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expect(result.ev).toBeCloseTo(15.0);
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});
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it("matches Python research model: trivial risk + single scope + isolated impact", () => {
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// p=0.98, scopeCost=1.0 (single), impactWeight=1.0 (isolated)
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const result = calculateTaskEv(0.98, 1.0, 1.0);
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expect(result.pSuccess).toBeCloseTo(0.98);
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expect(result.expectedRetries).toBeCloseTo(0.02 / 0.98);
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expect(result.ev).toBeCloseTo(1.0);
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});
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// --- Boundary values ---
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it("handles very small p > 0", () => {
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const result = calculateTaskEv(0.01, 1.0, 1.0);
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expect(result.pSuccess).toBe(0.01);
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expect(result.expectedRetries).toBeCloseTo(0.99 / 0.01); // = 99
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// Default config: C_fail = C_success = 1.0
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expect(result.ev).toBeCloseTo(1.0);
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});
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it("handles p very close to 1", () => {
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const result = calculateTaskEv(0.999, 1.0, 1.0);
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expect(result.expectedRetries).toBeCloseTo(0.001 / 0.999);
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expect(result.ev).toBeCloseTo(1.0);
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});
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it("returns zero EV when scopeCost is 0", () => {
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const result = calculateTaskEv(0.5, 0, 1.0);
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// C_success = 0, C_fail = 0 + 0 + 0 = 0
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expect(result.ev).toBe(0);
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});
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it("returns zero EV when impactWeight is 0 and no fallback costs", () => {
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const result = calculateTaskEv(0.5, 5.0, 0);
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// C_success = 0, C_fail = 0 + 0 + 0 = 0
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expect(result.ev).toBe(0);
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});
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it("preserves p as pSuccess in the result without modification", () => {
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expect(calculateTaskEv(0.75, 2.0, 1.0).pSuccess).toBe(0.75);
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expect(calculateTaskEv(0, 2.0, 1.0).pSuccess).toBe(0);
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expect(calculateTaskEv(1, 2.0, 1.0).pSuccess).toBe(1);
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});
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// --- Config variations ---
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it("undefined config defaults all fields to 0", () => {
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const result = calculateTaskEv(0.5, 2.0, 1.0, undefined);
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expect(result.expectedRetries).toBeCloseTo(1.0);
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expect(result.ev).toBeCloseTo(2.0);
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});
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it("empty config object defaults all fields to 0", () => {
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const result = calculateTaskEv(0.5, 2.0, 1.0, {});
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expect(result.expectedRetries).toBeCloseTo(1.0);
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expect(result.ev).toBeCloseTo(2.0);
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});
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it("partial config: only retries set", () => {
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const result = calculateTaskEv(0.2, 2.0, 1.0, { retries: 1 });
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// expectedRetries = (1-0.2)/0.2 = 4, capped at 1
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expect(result.expectedRetries).toBe(1);
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// C_success = 2.0, C_fail = 2.0 + 0 + 0 * 1 = 2.0
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// EV = 0.2 * 2.0 + 0.8 * 2.0 = 0.4 + 1.6 = 2.0
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expect(result.ev).toBeCloseTo(2.0);
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});
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it("partial config: only fallbackCost set", () => {
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const result = calculateTaskEv(0.5, 2.0, 1.0, { fallbackCost: 5 });
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// expectedRetries = 1.0 but timeLost=0 → retry cost = 0
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// C_fail = 2.0 + 5 + 0 = 7.0
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// EV = 0.5 * 2.0 + 0.5 * 7.0 = 1.0 + 3.5 = 4.5
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expect(result.ev).toBeCloseTo(4.5);
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});
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it("partial config: only timeLost set (no effect without retries generating cost)", () => {
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const result = calculateTaskEv(0.5, 2.0, 1.0, { timeLost: 10 });
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// expectedRetries = 1.0
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// C_fail = 2.0 + 0 + 10 * 1.0 = 12.0
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// EV = 0.5 * 2.0 + 0.5 * 12.0 = 1.0 + 6.0 = 7.0
|
||||
expect(result.ev).toBeCloseTo(7.0);
|
||||
});
|
||||
|
||||
it("full config with all parameters", () => {
|
||||
const result = calculateTaskEv(0.5, 2.0, 1.5, {
|
||||
retries: 2,
|
||||
fallbackCost: 10,
|
||||
timeLost: 3,
|
||||
valueRate: 50,
|
||||
});
|
||||
|
||||
// expectedRetries = (1-0.5)/0.5 = 1.0, not capped (below 2)
|
||||
expect(result.expectedRetries).toBeCloseTo(1.0);
|
||||
|
||||
// C_success = 2.0 * 1.5 = 3.0
|
||||
// C_fail = 3.0 + 10 + 3 * 1.0 = 16.0
|
||||
// EV_raw = 0.5 * 3.0 + 0.5 * 16.0 = 1.5 + 8.0 = 9.5
|
||||
// EV = 9.5 * 50 = 475.0
|
||||
expect(result.ev).toBeCloseTo(475.0);
|
||||
});
|
||||
});
|
||||
Reference in New Issue
Block a user