In an IDMS database, how is data integrity typically ensured during normal operations?

Introduction / Context:
Data integrity is a core responsibility of any database management system. In CA IDMS, which uses a network model with records and sets, the engine must ensure that relationships remain consistent and that failures do not leave the database in a corrupted state. Interviewers ask this question to see whether you understand basic IDMS mechanisms such as locking, journaling, and enforcement of set relationships that together protect data integrity.

Given Data / Assumptions:

• IDMS is running in a multi user environment where concurrent access is common.
• Updates to records and sets must be atomic and recoverable.
• IDMS provides built in features such as locks, journals, and automatic set maintenance.
• The question is about normal database mechanisms, not about ad hoc flat file copying.

Concept / Approach:
A robust DBMS uses several techniques to maintain data integrity. IDMS uses record and page level locking to control concurrent updates. It keeps journals that record changes for recovery and rollback. It also enforces set linkage rules so that when records are inserted or deleted, pointers are correctly maintained. Currency control ensures that programs know which record instances they are manipulating. The correct answer must bring these ideas together, describing an integrated mechanism for safeguarding integrity under normal load.

Step-by-Step Solution:
Step 1: Think about standard DBMS features that protect data integrity: locking, logging or journaling, and transactional control. Step 2: Map these to the IDMS context, where journaling captures changes and set relationships must stay valid. Step 3: Look for the option that explicitly mentions locking, journaling, and linkage rules working together. Step 4: Eliminate options that describe extremely inefficient or unrealistic methods such as copying all data after each transaction. Step 5: Also remove options that deny concurrency or place all responsibility on application code alone.

Verification / Alternative check:
As a cross check, ask whether the described method would scale in a large mainframe system. Copying entire databases after each transaction or forbidding concurrency is not realistic for large banks or government systems. In contrast, fine grained locking, journaling, and automatic pointer maintenance are well known techniques used by mature database systems like IDMS, which confirms the correct option.

Why Other Options Are Wrong:
Option b: Copying all data to flat files after every transaction would be extremely slow and is not how IDMS protects integrity.
Option c: Completely blocking concurrency defeats the purpose of a multi user database system and is not how IDMS is designed to operate.
Option d: While application programs must handle some validation, IDMS itself plays a central role in enforcing relationships and recoverability; it does not leave integrity entirely to applications.

Common Pitfalls:
A common pitfall is underestimating the importance of journaling and assuming that backups alone are enough. Backups help after major failures, but journals and locks protect data on every transaction. Another mistake is to think of IDMS as just a file handler, ignoring its advanced locking and recovery features. For interview answers, always emphasize coordinated mechanisms such as locking, journaling, and automated set maintenance when explaining how IDMS ensures data integrity.

Final Answer:
By using locking, journaling, currency control, and set linkage rules so that updates are consistent and recoverable.