Janady13/missionmatch / internal/modules/staffing/optimizer_test.go

Source identity

Field	Recorded value
Source type	GitHub source
Original record	Janady13/missionmatch / internal/modules/staffing/optimizer_test.go
Date	Not specified in source
Repository	Janady13/missionmatch
Revision	720d47fae476b0d38477ae4401697d372b1ea2bc
Branch	feature/opportunity-to-outcome
Path or archive member	internal/modules/staffing/optimizer_test.go
Original SHA-256	edc03f424693b3c8394aa6a62e9295c501b417d9b7fcba33edfd5350fb9c85ba
Git blob SHA	877d080c4689593f573d3da38b3d39f0e17f7366
Reading-copy SHA-256	edc03f424693b3c8394aa6a62e9295c501b417d9b7fcba33edfd5350fb9c85ba

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Original record	Branch or archive	Revision / identifier	Original location
Janady13/missionmatch / internal/modules/staffing/optimizer_test.go	feature/opportunity-to-outcome	720d47fae476b0d38477ae4401697d372b1ea2bc	Open original
Janady13/missionmatch / internal/modules/staffing/optimizer_test.go	per-tenant-routing	9bde0f9a74b89d01980fa658e5253acda7528d0c	Open original
Janady13/missionmatch / internal/modules/staffing/optimizer_test.go	collision-deconfliction	4ee5a09972608ed89f8377c6665542d5f450f0a6	Open original
Janady13/missionmatch / internal/modules/staffing/optimizer_test.go	ws6-retrieval	6c56e29231ec05735927fa265c97d517499dfeaf	Open original
Janady13/missionmatch / internal/modules/staffing/optimizer_test.go	m5-price-to-win	41000ad30fff4129fdaf5ec84e15ba14c27d4890	Open original
Janady13/missionmatch / internal/modules/staffing/optimizer_test.go	ws1-ontology-sync	b596f449a32a1016fbd403c36505cc00a1ac9ee6	Open original
Janady13/missionmatch / internal/modules/staffing/optimizer_test.go	master	1e9249840a4302ec82e123b9c9cb6f75badea3e4	Open original
Janady13/missionmatch / internal/modules/staffing/optimizer_test.go	ws8-teaching-loop	c823f0fb6bb2aba0f39001eb6de96f4000d9321f	Open original
Janady13/missionmatch / internal/modules/staffing/optimizer_test.go	w3-ai-staffing-recommendations	43d56387270ef4da4cabd794d97ca6a49909bc7d	Open original
Janady13/missionmatch / internal/modules/staffing/optimizer_test.go	mag-substrate	b82c7100a492dec67dfd1eda6b3f53def859be35	Open original
Janady13/missionmatch / internal/modules/staffing/optimizer_test.go	ws3-clearance	4b8e7ce594c068621867f9c9deed0ec64ae6c553	Open original
Janady13/missionmatch / internal/modules/staffing/optimizer_test.go	phase2-eval-fairness	d361af254701975fe239927656ababb56374655e	Open original
Janady13/missionmatch / internal/modules/staffing/optimizer_test.go	time-to-fill-survival	b66e1e505863d4f17741a4b9ede73509e45bd6c6	Open original
Janady13/missionmatch / internal/modules/staffing/optimizer_test.go	graphrag-foundation	b0ddeb9f633fd138d09309d1a17b7d13bc3a67f7	Open original
Janady13/missionmatch / internal/modules/staffing/optimizer_test.go	deploy-and-ops	bdacd9d0b4d5998d25fc74bf4007f4c3ec538c7a	Open original
Janady13/missionmatch / internal/modules/staffing/optimizer_test.go	ws9-bench-ingestion	f585a9ef32fa554663ce1fba9a414a54b6e49cf0	Open original
Janady13/missionmatch / internal/modules/staffing/optimizer_test.go	ws2-alias-relationship	e4dada4601c6eb101830f9d223a9655dfa120616	Open original
Janady13/missionmatch / internal/modules/staffing/optimizer_test.go	presentation-readiness	eb574acaa29d71ce4d0f852572e87c275c79fdb7	Open original
Janady13/missionmatch / internal/modules/staffing/optimizer_test.go	vendor-intelligence	fe9796a19c261951d3f2565206c0c1b5ac294465	Open original
Janady13/missionmatch / internal/modules/staffing/optimizer_test.go	ws7-federal-signal	6a9f6ce9cfb13345ffb47770d4960e7c2d9c17c2	Open original
Janady13/missionmatch / internal/modules/staffing/optimizer_test.go	ai-brain-live	aac32fc49c878cc5bca099459307611562d0bac1	Open original
Janady13/missionmatch / internal/modules/staffing/optimizer_test.go	phase2-connectors	e038d4c687aec16f8bd9bc4d907eea14d91f8704	Open original
Janady13/missionmatch / internal/modules/staffing/optimizer_test.go	feature/aioe-upgrade	2178e7298d0e5d9af83afa12402fd587f0ba6ed8	Open original
Janady13/missionmatch / internal/modules/staffing/optimizer_test.go	capture-readiness	bae6af7cb2997e819174a9e9cfff5e16067a1975	Open original

Recovered source transcript

Download complete source text ↓154 lines · 5.3 KB

package staffing

import (
	"context"
	"errors"
	"testing"
)

func solve(t *testing.T, in PortfolioInput) PortfolioSolution {
	t.Helper()
	sol, err := SolvePortfolio(context.Background(), in, 1_000_000, 100_000)
	if err != nil {
		t.Fatalf("solve: %v", err)
	}
	return sol
}

func TestSolveEmpty(t *testing.T) {
	if sol := solve(t, PortfolioInput{}); len(sol.Assignments) != 0 || sol.TotalValue != 0 {
		t.Fatalf("empty problem must yield an empty allocation, got %+v", sol)
	}
	// candidates but no edges -> empty (everyone is a source).
	if sol := solve(t, PortfolioInput{NumCandidates: 3, Slots: []int{1, 1}}); len(sol.Assignments) != 0 {
		t.Fatalf("no edges means no assignment, got %+v", sol)
	}
}

func TestSolveSingle(t *testing.T) {
	sol := solve(t, PortfolioInput{
		NumCandidates: 1,
		Slots:         []int{1},
		Edges:         []AssignEdge{{0, 0, 100}},
	})
	if len(sol.Assignments) != 1 || sol.TotalValue != 100 {
		t.Fatalf("single profitable pair must be assigned, got %+v", sol)
	}
}

// TestSolveTrueOptimumNotGreedy is the proof that this is a real optimizer and not a greedy heuristic.
// Greedy gives c0 its best requirement r0 (10), leaving c1 only r1 (1), total 11. The true optimum routes
// c0 to r1 (8) and c1 to r0 (9), total 17. The successive shortest path solve must find 17.
func TestSolveTrueOptimumNotGreedy(t *testing.T) {
	sol := solve(t, PortfolioInput{
		NumCandidates: 2,
		Slots:         []int{1, 1},
		Edges: []AssignEdge{
			{0, 0, 10}, {0, 1, 8},
			{1, 0, 9}, {1, 1, 1},
		},
	})
	if sol.TotalValue != 17 {
		t.Fatalf("max profit must be 17 (greedy would give 11), got %d", sol.TotalValue)
	}
	got := map[int]int{}
	for _, a := range sol.Assignments {
		got[a.CandidateIdx] = a.RequirementIdx
	}
	if got[0] != 1 || got[1] != 0 {
		t.Fatalf("optimal allocation must be c0->r1 and c1->r0, got %+v", got)
	}
}

func TestSolveUnfilledSlotsAreImplicitSource(t *testing.T) {
	// One candidate, two single slot requirements they both fit; the candidate takes the higher value one,
	// the other slot is left unfilled (a source in the domain).
	sol := solve(t, PortfolioInput{
		NumCandidates: 1,
		Slots:         []int{1, 1},
		Edges:         []AssignEdge{{0, 0, 50}, {0, 1, 90}},
	})
	if len(sol.Assignments) != 1 || sol.Assignments[0].RequirementIdx != 1 || sol.TotalValue != 90 {
		t.Fatalf("the candidate must take the higher value slot, leaving the other unfilled, got %+v", sol)
	}
}

func TestSolveRespectsSlotCapacity(t *testing.T) {
	// One requirement with two slots, three qualified candidates -> exactly two assigned (the two highest).
	sol := solve(t, PortfolioInput{
		NumCandidates: 3,
		Slots:         []int{2},
		Edges:         []AssignEdge{{0, 0, 70}, {1, 0, 95}, {2, 0, 80}},
	})
	if len(sol.Assignments) != 2 {
		t.Fatalf("a two slot requirement must take exactly two candidates, got %d", len(sol.Assignments))
	}
	if sol.TotalValue != 175 { // 95 + 80
		t.Fatalf("the two highest value candidates must fill the slots, total 175, got %d", sol.TotalValue)
	}
}

func TestSolveDeterministic(t *testing.T) {
	in := PortfolioInput{
		NumCandidates: 4,
		Slots:         []int{1, 1, 1},
		Edges: []AssignEdge{
			{0, 0, 50}, {0, 1, 50}, {1, 0, 50}, {1, 1, 50},
			{2, 1, 50}, {2, 2, 50}, {3, 0, 50}, {3, 2, 50},
		},
	}
	first := solve(t, in)
	for i := 0; i < 20; i++ {
		again := solve(t, in)
		if again.TotalValue != first.TotalValue || len(again.Assignments) != len(first.Assignments) {
			t.Fatalf("non deterministic total: %+v vs %+v", first, again)
		}
		for k := range again.Assignments {
			if again.Assignments[k] != first.Assignments[k] {
				t.Fatalf("non deterministic allocation at %d: %+v vs %+v", k, first.Assignments, again.Assignments)
			}
		}
	}
}

func TestSolveProblemTooLarge(t *testing.T) {
	in := PortfolioInput{NumCandidates: 2, Slots: []int{1}, Edges: []AssignEdge{{0, 0, 1}, {1, 0, 1}}}
	if _, err := SolvePortfolio(context.Background(), in, 1, 100); !errors.Is(err, ErrProblemTooLarge) {
		t.Fatalf("an edge count over the cap must be refused, got %v", err)
	}
	if _, err := SolvePortfolio(context.Background(), in, 100, 2); !errors.Is(err, ErrProblemTooLarge) {
		t.Fatalf("a node count over the cap must be refused, got %v", err)
	}
}

func TestSolveBudgetExceeded(t *testing.T) {
	ctx, cancel := context.WithCancel(context.Background())
	cancel() // already cancelled: the solve must refuse rather than run
	in := PortfolioInput{NumCandidates: 1, Slots: []int{1}, Edges: []AssignEdge{{0, 0, 100}}}
	if _, err := SolvePortfolio(ctx, in, 1000, 1000); !errors.Is(err, ErrSolveBudget) {
		t.Fatalf("a cancelled context must surface ErrSolveBudget, got %v", err)
	}
}

func TestCounterfactualsKnown(t *testing.T) {
	in := PortfolioInput{
		NumCandidates: 2,
		Slots:         []int{1, 1},
		Edges: []AssignEdge{
			{0, 0, 10}, {0, 1, 8},
			{1, 0, 9}, {1, 1, 1},
		},
	}
	sol := solve(t, in) // c0->r1 (8), c1->r0 (9)
	cf := Counterfactuals(in, sol)
	// c0 assigned to r1 (8); next best requirement is r0 (10); delta = 8 - 10 = -2 (giving c0 r1 instead of
	// its own best protected the portfolio).
	if cf[0].CandidateNextReqIdx != 0 || cf[0].CandidateValueDelta != -2 {
		t.Fatalf("c0 counterfactual wrong: %+v", cf[0])
	}
	// requirement r1's next best candidate (other than c0) is c1 at value 1; assigned value 8; delta 7.
	if cf[0].RequirementNextCandIdx != 1 || cf[0].RequirementValueDelta != 7 {
		t.Fatalf("r1 next best candidate counterfactual wrong: %+v", cf[0])
	}
}

Mathematical records from this source

func TestCounterfactualsKnown(t *testing.T) · c0 assigned to r1 (8); next best requirement is r0 (10); delta

This relation defines c0 assigned to r1 (8); next best requirement is r0 (10); delta in the source section “func TestCounterfactualsKnown(t *testing.T) · c0 assigned to r1 (8);…