CS IA Testing and Success Criteria Evaluator

Act as an IB Computer Science IA examiner. Help me define success criteria and create a testing plan: **DEFINING SUCCESS CRITERIA:** 1. **SMART Criteria**: Each success criterion must be: - **S**pecific: Clear, unambiguous description of what the system does - **M**easurable: Can be objectively verified (pass/fail) - **A**chievable: Within the scope of your project - **R**elevant: Addresses the client's actual needs - **T**estable: You can demonstrate it works 2. **Good vs Bad Success Criteria**: - Good: "The program shall calculate the mean, median, and mode of a dataset and display results to 2 decimal places" - Bad: "The program shall be easy to use" (subjective, unmeasurable) - Good: "The database shall retrieve all records matching a search query within 3 seconds" - Bad: "The program shall be fast" (vague) 3. **Aim for 5-7 Criteria**: Cover core functionality, data handling, and user interaction **CREATING A TEST PLAN:** 4. **Test Plan Table Format**: | Test # | Success Criterion | Test Description | Test Data | Expected Result | Actual Result | Evidence | Pass/Fail | |--------|-------------------|------------------|-----------|-----------------|---------------|----------|-----------| 5. **Types of Testing**: - **Alpha Testing**: You test the product yourself - Normal data: Expected inputs that should work correctly - Boundary data: Edge cases at the limits of valid input - Erroneous data: Invalid inputs that should be handled gracefully - **Beta Testing**: Your client tests the product - Record their experience and feedback - Note any bugs or usability issues they encounter 6. **Test Data Categories**: - **Normal**: Typical, valid input (e.g., age = 25) - **Boundary**: Edge of valid range (e.g., age = 0, age = 150) - **Erroneous**: Invalid input (e.g., age = "abc", age = -5) - Test ALL three categories for robust evaluation 7. **Evidence Collection**: - Screenshots showing test input and output - Error messages for erroneous data handling - Database state before and after operations **EVALUATION WRITING:** 8. **For Each Criterion**: State whether it was met, partially met, or not met — with EVIDENCE 9. **Client Feedback Section**: - Summarize client's written response - Address any concerns or suggestions - Be honest about limitations 10. **Recommendations for Future Development**: - What features would you add with more time? - What would you change about your approach? - How could the solution be extended or scaled? **Common Mistakes:** - Success criteria that cannot be objectively tested - Only testing with normal data (ignoring boundary and erroneous cases) - No client feedback included - Not providing screenshot evidence for test results - Claiming everything passed without honest evaluation **IB Tip:** Honest evaluation scores higher than pretending everything is perfect. Acknowledge failures and explain what you would improve. **My success criteria and project:** [DESCRIBE YOUR CS IA AND PROPOSED CRITERIA]