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:

  • To verify that the dataset or form has all necessary information for processing.

  • Prevents incomplete records from entering the system.

Examples:

  • A registration form must have name, email, and password filled.

  • An invoice must include invoice number, date, and amount.

Key Point:

  • 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:

  • To detect implausible or unlikely data that might be technically valid but logically incorrect.

  • Helps maintain data quality.

Examples:

  • Age entered as 250 years → unrealistic.

  • Salary entered as $0 for a full-time employee → unrealistic.

  • Date of birth in the future → unrealistic.

Key Point:

  • 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?