Decision Tree

Definition

A Decision Tree is a graphical (tree-shaped) representation of conditional logic, showing conditions as branching nodes and outcomes/actions as leaf nodes — a visual alternative to a decision table for representing the same complex conditional logic.

Structure

• Root node — starting condition
• Branches — represent possible outcomes of a condition (Yes/No or multiple values)
• Internal nodes — further conditions to evaluate
• Leaf nodes — final actions/decisions

Example: Loan Approval Decision Tree

                    Good Credit Score?
                    /              \
                  Yes               No
                  /                   \
        Stable Income?          Stable Income?
         /        \               /        \
       Yes         No           Yes         No
        │           │            │           │
    Approve   Approve with   Approve with  Reject
     Loan      Conditions     Conditions    Loan

Decision Table vs. Decision Tree

Decision Table	Decision Tree
Tabular/compact format	Graphical/visual format
Better for many conditions (systematic)	Better for visualizing sequential logic flow
Harder to read at a glance for non-technical stakeholders	Easier for non-technical stakeholders to follow visually
Easy to check completeness (all combinations)	Can miss combinations if not drawn carefully
Good for verifying business rule logic	Good for presenting/communicating decision logic

Advantages

• Intuitive, easy to follow visually
• Good communication tool with non-technical stakeholders
• Clearly shows the sequence in which conditions are evaluated

Disadvantages

• Can become large and unwieldy with many conditions/branches
• Harder to verify systematic completeness compared to a decision table

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Exam tip: Almost always asked as a compare Decision Table vs Decision Tree question, or asked to draw one for a given scenario — practice both forms for the same business rule (e.g., loan approval, grading system).