4. Detailed Use Case Specification

By now you have a refined, professional-grade Use Case Diagram that clearly shows actors, core goals, shared functionality («include»), and conditional extensions («extend»). This high-level view answers “Who does what, and in what variants?” — but it does not yet explain how each goal is achieved step by step.

Module 4 shifts the focus from structure to behavioral detail. Here you write the full textual use case specification — the detailed narrative that describes exactly what happens when an actor pursues a goal. This is the most critical bridge between requirements and implementation: developers, testers, UX designers, and stakeholders all rely on these specifications to understand expected system behavior, edge cases, preconditions, postconditions, and alternative paths.

A well-written use case specification typically includes the following structured sections:

• Use Case Name and ID
• Primary Actor
• Secondary Actors (if any)
• Preconditions (what must be true before the use case can start)
• Postconditions (what must be true after successful completion)
• Main Success Scenario (the happy path — numbered steps)
• Alternative Flows (variations that still lead to success)
• Exception Flows (error conditions and how the system recovers or fails gracefully)
• Extension Points (where «extend» use cases insert behavior)
• Business Rules / Non-functional Notes (if relevant)
• Priority & Frequency

In traditional projects, writing these specifications is one of the most time-consuming activities — often resulting in inconsistent style, missing edge cases, or outdated documents. Visual Paradigm’s AI-Powered Use Case Modeling Studio transforms this effort by generating comprehensive, multi-section specifications automatically from:

• The use case name
• Its relationships («include», «extend»)
• The problem context and scope
• Actor goals identified earlier

The AI produces a complete draft in seconds, written in clear, structured, numbered prose. You then refine it collaboratively in the integrated markdown-style editor — adding domain-specific rules, adjusting tone, or inserting precise business logic — while the tool keeps everything traceable to the diagram.

Practical Examples of AI-Generated + Refined Specifications (Excerpts)

Example 1: GourmetReserve – Use Case: Book a Table

AI-Generated Draft (partial):

• Use Case: Book a Table
• Primary Actor: Diner
• Preconditions: Diner is authenticated; at least one restaurant is registered in the system
• Postconditions: A table reservation is confirmed; a deposit (if required) is processed; confirmation and reminder notifications are scheduled
• Main Success Scenario
  1. Diner searches for available tables by location, date, time, and party size.
  2. System displays matching restaurants and open slots.
  3. Diner selects a restaurant, time slot, and party size.
  4. System includes Process Payment (required deposit).
  5. Diner confirms booking details.
  6. System creates reservation record and sends confirmation.
• Alternative Flows 3a. If no tables available → System offers waitlist option (extends via Handle Waitlist).
• Exception Flows 4a. Payment fails → System displays error and returns to payment retry or cancel.

Typical Refinement You Add: Insert business rule at step 4: “Deposit is 10% of estimated bill for parties > 8 or peak hours (Fri/Sat 7–9 pm).”

Example 2: SecureATM – Use Case: Withdraw Cash

AI-Generated Structure (excerpt):

• Preconditions: User has inserted valid card or authenticated via mobile; sufficient funds available
• Main Success Scenario
  1. System includes Authenticate User.
  2. User selects “Withdraw Cash”.
  3. System includes Validate Transaction Limits.
  4. User enters amount.
  5. System dispenses cash and updates balance.
  6. System offers receipt (extends via Print Receipt).
• Exception Flows 4a. Amount exceeds daily limit → System displays message and returns to amount entry. 5a. Insufficient funds → System shows error and suggests lower amount. 5b. Cash cassette empty → System displays “Temporarily unavailable” and alerts operations team.

Example 3: CorpLearn – Use Case: Take Final Assessment

AI-Generated + Refined Highlights:

• Main Success Scenario
  1. Learner selects “Start Assessment” from course page.
  2. System presents timed questions (multiple choice, short answer).
  3. Learner submits answers.
  4. System includes Record Learning Progress.
  5. If score ≥ 80% → System extends with Issue Certificate.
• Exception Flows 3a. Time expires → System auto-submits current answers. 5a. Score < 80% → System offers retake option (if allowed by course policy) or marks course incomplete.

Why This Step Remains Essential (Even with AI)

The AI excels at producing consistent, well-structured drafts quickly — but it cannot know your organization’s specific policies, regulatory constraints, pricing logic, error-recovery preferences, or subtle user experience decisions. You — the requirements engineer or product owner — remain the decision-maker:

• You validate that every exception flow covers real-world risks.
• You ensure postconditions align with compliance or audit needs.
• You refine wording so developers and testers interpret intent correctly.

By the end of Module 4, each major use case will have a detailed, readable, and traceable specification that serves as:

• The single source of truth for development
• The foundation for generating Activity & Sequence Diagrams (Module 5)
• The direct input for automated test case creation (Module 7)

You’ve now moved from a bird’s-eye view of functionality to a step-by-step blueprint of system behavior — and thanks to AI assistance, you’ve done so in a fraction of the traditional time while retaining full control over quality and accuracy.