Software Engineering basics - Difference between completeness checks and realism checks
1. Completeness Check
Definition:
A completeness check ensures that all required data fields are filled in and that no mandatory information is missing.
Purpose:
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To verify that the dataset or form has all necessary information for processing.
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Prevents incomplete records from entering the system.
Examples:
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A registration form must have name, email, and password filled.
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An invoice must include invoice number, date, and amount.
Key Point:
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Focuses on presence of required data.
2. Realism Check
Definition:
A realism check ensures that the data values are believable and make sense in the real world.
Purpose:
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To detect implausible or unlikely data that might be technically valid but logically incorrect.
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Helps maintain data quality.
Examples:
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Age entered as 250 years → unrealistic.
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Salary entered as $0 for a full-time employee → unrealistic.
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Date of birth in the future → unrealistic.
Key Point:
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Focuses on plausibility and practical sense of data values.
3. Key Differences Table
| Feature | Completeness Check | Realism Check |
|---|---|---|
| Purpose | Ensure all required data is present | Ensure data values are plausible |
| Focus | Presence of mandatory fields | Believability of entered values |
| Example | Name, address, and email must be entered | Age < 120, salary > 0 |
| When Used | During data entry | During data entry or validation |
Summary
Completeness check = Is any required data missing?
Realism check = Does the data make sense in the real world?
