Mapping Unique Scenarios Against Specific Conditions and Actions to Ensure Functional Completeness
While the scenario breakdown in Section 6.1 often begins with narrative decomposition and produces initial decision tables, Decision Matrix Analysis takes this rigor one step further. It systematically maps every unique, meaningful combination of conditions (states, inputs, business rules, environmental factors) against the precise actions or outcomes the system must produce. The result is a compact, exhaustive, and auditable representation of decision logic that guarantees functional completeness — meaning no realistic scenario is left unspecified, no contradictory outcomes exist, and every path has a defined, correct response.
A well-constructed decision matrix (also called a decision table in its classic form) has four main zones:
- Conditions (columns) — independent factors that influence the outcome
- Rules (rows) — each row represents one unique combination of condition values
- Actions / Outcomes (lower section) — what the system does or what state it reaches for that rule
- Annotations (optional extra columns) — traceability to use case steps, priority, test focus, or business justification
The power of this technique lies in forcing explicit consideration of all combinations (even the rare or edge ones), quickly revealing gaps, ambiguities, or inconsistencies that narrative text often hides.
In Visual Paradigm’s AI-Powered Use Case Modeling Studio, after generating an initial decision table from the use case flows (Section 6.1), you can invoke “Analyze Decision Matrix” or “Complete Decision Coverage”. The AI:
- Identifies additional conditions implied by preconditions, guards, business rules, or cross-referencing other use cases
- Fills in missing combinations that were not explicitly mentioned in the narrative
- Flags impossible combinations, contradictions, or rules with identical outcomes (candidates for merging)
- Suggests compacting the table by eliminating redundant rules
- Highlights high-risk or high-frequency scenarios for prioritization
You refine by adding domain-specific conditions, adjusting values, splitting overly coarse rules, and documenting rationale.
Practical Examples
Example 1: GourmetReserve – Use Case: Book a Table (Advanced Decision Matrix)
Conditions considered:
- Authenticated?
- Tables available for requested time & size?
- Party size ≥ 8?
- Peak hours (Fri/Sat 7–9 pm)?
- Gold Loyalty status?
- Valid promo code entered?
- Payment succeeds? (only relevant when deposit required)
Refined & Completed Decision Matrix (excerpt – showing selected critical combinations):
| Rule | Auth? | Tables Avail? | Party ≥8? | Peak? | Gold? | Valid Promo? | Payment OK? | Outcome / System Action | Priority | Trace |
|---|---|---|---|---|---|---|---|---|---|---|
| R1 | Y | Y | N | — | — | — | — | Confirmed – no deposit required | High | Main |
| R2 | Y | Y | Y | N | Y | — | — | Confirmed – deposit waived (loyalty) | High | Main |
| R3 | Y | Y | Y | Y | N | N | Y | Confirmed – 10% deposit collected | High | Main |
| R4 | Y | Y | Y | Y | N | Y | Y | Confirmed – discounted deposit (promo applied first) | Medium | Alt 4a |
| R5 | Y | Y | Y | Y | N | N | N | Error: “Payment declined. Retry or cancel booking.” | High | Exc 4b |
| R6 | Y | N | — | — | — | — | — | No tables → Offer waitlist OR closest alternatives | High | Alt 3a |
| R7 | Y | Y | Y | Y | N | — | Y | Confirmed – but pending manager approval (party ≥12) | Medium | New |
| R8 | N | — | — | — | — | — | — | Redirect to login / create account | High | Pre |
Key insight from matrix:
- Rule R7 was missing in the original narrative → added after realizing large parties have extra governance.
- Impossible combinations (e.g., payment outcome when no deposit required) are marked “—” and excluded.
Example 2: SecureATM – Withdraw Cash (High-risk security focus)
Decision Matrix (security & limit logic):
| Rule | Authenticated? | Within Daily Limit? | Sufficient Funds? | Sufficient Cash? | High-Value (> $1,000)? | Biometric Passed? | Outcome / Action Performed |
|---|---|---|---|---|---|---|---|
| 1 | Y | Y | Y | Y | N | — | Dispense → Update balance → Log transaction |
| 2 | Y | Y | Y | Y | Y | Y | Dispense → Update balance → Enhanced fraud log |
| 3 | Y | Y | Y | Y | Y | N | Retain card → Fraud alert → End session |
| 4 | Y | N | — | — | — | — | “Exceeds daily limit” → Return to main menu |
| 5 | Y | Y | N | — | — | — | “Insufficient funds” → Show balance → Suggest lower amount |
| 6 | Y | Y | Y | N | — | — | “Temporarily unavailable” → Alert operations team |
Example 3: CorpLearn – Final Assessment Submission
Focused Decision Matrix (pass/fail + compliance):
| Rule | Modules Complete? | Time Remaining? | Compliance Ack? | Privacy Q Correct? | Score ≥80%? | Retakes Left? | Outcome |
|---|---|---|---|---|---|---|---|
| 1 | Y | Y | Y | Y | Y | — | Passed → Issue certificate → Update record |
| 2 | Y | Y | Y | N | Y | — | Failed – privacy violation → No certificate |
| 3 | Y | Y | Y | Y | N | Y | Failed → Retake offered (2 attempts remaining) |
| 4 | Y | Y | Y | Y | N | N | Failed → No further attempts → Mark incomplete |
| 5 | Y | N | — | — | — | — | Time expired → Auto-submit → Score calculated |
| 6 | N | — | — | — | — | — | Cannot start – prerequisites not met |
Benefits of Thorough Decision Matrix Analysis
- Exhaustiveness — Guarantees every realistic combination has a defined outcome.
- Early defect detection — Contradictions (e.g., same conditions → different actions) become immediately visible.
- Conciseness — Redundant or impossible rules are eliminated, making logic easier to review.
- Direct test foundation — Each rule maps cleanly to one or more test cases (Module 7).
- Audit & compliance value — Provides clear evidence of considered edge cases and business rules.
By completing a rigorous decision matrix analysis, you transform potentially vague or incomplete narrative requirements into a mathematically complete specification of system behavior. This step is one of the strongest ways to ensure functional correctness before coding begins — and the AI accelerates the initial structure while your domain expertise ensures business accuracy and completeness.