Lecture Notes: Validation and Verification

Introduction

• Validation and Verification are distinct concepts important for exams.
  • Validation: Ensures sensible data entry.
  • Verification: Ensures data matches the original source.

Validation

Definition

• An automatic computer check at data entry.
• Ensures data is sensible and reasonable.
• Does NOT ensure data accuracy.

Importance

• Prevents program crashes due to abnormal data.
• Easier to prevent poor data at entry than to fix later.
• Assumes users may enter incorrect data; systems should be idiot-proof.

Examples

• Restaurant Booking System:

  • Missing contact info or booking details if no validation.

• Integer Input:

  • Expect whole numbers between 1 and 10.
  • Validation stops incorrect entries like '5.7' or '11'.

Limitations

• Cannot ensure data accuracy.
• Examples:
  • Gender entry 'M' or 'F' may still be incorrect.
  • Postcodes may follow format but be outdated.
  • Emails can match patterns but have typos.
  • Test scores may be technically valid but incorrect.

Validation Methods

1. Range Check: Ensures data falls within a specific range.

   • E.g., age or score validations.

2. Type Check: Checks data type (e.g., number vs text).

3. Length Check: Ensures enough characters are entered.

   • Common in password criteria.

4. Presence Check: Ensures a field is not left empty.

5. Check Digits: Extra digit ensuring number sequence correctness.

Verification

Definition

• Ensures data copied from one medium matches the original.

Differences from Validation

• Does not check data makes sense.
• Focuses on identical data transfer.

Methods of Verification

1. Double Entry: Enter data twice to confirm match.

   • Common in passwords and email confirmations.
   • Uncommon for lengthy texts like essays.

2. Visual Check: Manually compare the original and new data.

   • E.g., comparing written account numbers with online entries.

Conclusion

• Validation: Ensures sensible data entry to minimize future issues.
• Verification: Confirms accurate data transfer between mediums.
• Understanding both is critical for effective data management.