In systems analysis and design, what should a system design aid primarily help with? Choose the most appropriate primary purpose.

Introduction / Context:
System design aids (such as modeling notations and CASE tools) exist to clarify how a system should work before coding starts. Their primary role is to illuminate the problem space by analyzing both data (what is stored and exchanged) and activities/processes (what the system does).

Given Data / Assumptions:

• We are focusing on the primary purpose of a design aid, not every possible secondary benefit.
• Documentation and programming support can be side benefits but are not the central reason these aids exist.
• Automatic code generation is outside the minimal goal and is not universally available or reliable.

Concept / Approach:
The cornerstone of good system design is correct understanding of processes and data structures. Techniques like data flow diagrams, entity-relationship models, and use-case models provide a dual view: activities transform inputs to outputs, while data models define persistent structures. A tool or notation that helps analyze both dimensions best serves designers and stakeholders.

Step-by-Step Solution:
1) Identify the core needs of design: understand processes + understand data.2) Recognize that documentation is an artifact of analysis, not its core goal.3) Recognize that programming support may help later but depends on language/tech stack; it is not universal.4) Therefore, the primary purpose is comprehensive analysis of data and activities.

Verification / Alternative check:
When system models are accurate, teams can choose technology stacks and coding strategies confidently. Conversely, perfect documentation or code stubs do not fix incorrect analysis.

Why Other Options Are Wrong:
Documentation-only is too narrow. Programming-only support misses early-stage needs. Auto code generation is not a core requirement and may not fit every architecture. “None” ignores the established purpose of design aids.

Common Pitfalls:
Overemphasizing tool output (pretty diagrams, generated code) while underinvesting in the quality of the underlying analysis.

Final Answer:
Help analyze both data and activities (processes) comprehensively.