Comprehensive and Detailed Explanation From Exact Extract:

Pega’s class inheritance and data modeling principles, as taught in Pega Academy’sData Modeling Missionand thePega Certified Lead System Architect Study Guide, advocate for a hierarchical class structure to manage common and specialized attributes efficiently. This approach leverages Pega’s pattern and directed inheritance to promote reuse and maintainability.

Option A (Incorrect): Creating a single class and dynamically adding or removing attributes is not a Pega best practice. Dynamic attribute management is complex, error-prone, and not natively supported in Pega’s class structure. Italso complicates rule resolution and maintenance, as noted in theData Modelingguidelines.

Option B (Incorrect): Defining all possible attributes in a single class leads to a bloated class structure with unused properties for certain policy types, reducing maintainability and clarity. Pega discourages monolithic class designs for scenarios with specialized attributes, per theClass Designmodule.

Option C (Correct): Creating a base class (e.g., Insurance-Policy) for common attributes (policy number, policyholder name, premium amount) and derived classes (e.g., Insurance-Policy-Car, Insurance-Policy-Home, Insurance-Policy-Life) for unique attributes is the optimal approach. This leverages Pega’s class inheritance (pattern and directed) to reuse common attributes while allowing specialization, aligning with Pega’sData Modeling Missionand best practices for modular design.

Option D (Incorrect): Creating separate classes for each policy type and defining common attributes in a new class is unclear and inefficient. It suggests duplicating common attributes across classes or misusing a non-inherited class, both of which violate Pega’s inheritance principles and increase maintenance overhead.