How can a DFD be decomposed into a primitive?

Decomposing a Data Flow Diagram (DFD) into a primitive level involves breaking down higher-level processes into more detailed and specific sub-processes while maintaining clarity about data flow. The correct choice highlights structured English, decision trees, and decision tables as effective tools for this purpose.

Structured English allows for writing clear and unambiguous descriptions of processes, enabling you to specify the details of each process in the DFD. Decision trees help in visualizing the various pathways and decisions within a process, making it easier to identify all the processes that need to be represented at a primitive level. Additionally, decision tables systematically display conditions and actions that can be evaluated, supporting the decomposition of complex processes into simpler components.

In contrast, other options do not effectively support the decomposition of DFDs into primitives. For example, context tables primarily provide an overview of the relationships between processes and external entities, rather than detailing individual process steps. Data mining techniques focus on extracting insights from large datasets rather than breaking down diagrammatic representations in a structured manner. Flowcharting or diagramming can illustrate processes, but they do not inherently provide a set framework like structured English or decision tools for decomposing DFDs into primitives effectively.