Which statement is true about memory optimization in a process model?

Which statement is true about memory optimization in a process model?

• A. Splitting into sub processes reduces memory usage by allowing only part of the process to run at a time.
• B. Increasing the number of process variables reduces memory usage.
• C. Storing large data chunks in process variables improves performance.
• D. Compressing text before storing in process variables is never beneficial.

Answer: (B)

Memory usage in a process model is tied to how much data you keep active in memory at once. If you store large data items directly in process variables, the in‑memory footprint grows quickly. Increasing the number of process variables can help reduce peak memory usage because you can split data into smaller pieces, keep only what you need in memory, and store the bulk of data externally while holding lightweight references or smaller chunks in variables. This on-demand or chunked approach minimizes the amount of data resident in memory at any moment. Other options tend to be less reliable. Splitting into sub-processes can help with organization and control flow, but memory reduction isn’t guaranteed and depends on the overall design. Storing large data chunks in process variables generally increases memory usage rather than reduces it. Compressing text before storing can be beneficial in many cases, especially for large text, so the claim that it’s never beneficial isn’t accurate.

Memory usage in a process model is tied to how much data you keep active in memory at once. If you store large data items directly in process variables, the in‑memory footprint grows quickly. Increasing the number of process variables can help reduce peak memory usage because you can split data into smaller pieces, keep only what you need in memory, and store the bulk of data externally while holding lightweight references or smaller chunks in variables. This on-demand or chunked approach minimizes the amount of data resident in memory at any moment.

Other options tend to be less reliable. Splitting into sub-processes can help with organization and control flow, but memory reduction isn’t guaranteed and depends on the overall design. Storing large data chunks in process variables generally increases memory usage rather than reduces it. Compressing text before storing can be beneficial in many cases, especially for large text, so the claim that it’s never beneficial isn’t accurate.