Decision Tree And Decision Table
Decision Tree and Decision Table are rule models that assist in visualizing and understanding decision logic, typically employed for capturing business rules. While both serve similar purposes, they differ in their structure, complexity handling, and ease of interpretation. Here's how each works:
Decision Tree:
Structure: A decision tree resembles a tree structure with branches representing choices leading to outcomes, often visualized either horizontally or vertically. Decision points can be represented by diamond shapes or text, while the outcomes (the leaves) are represented in boxes.
Complexity: Best suited for binary decisions, for instance, yes or no scenarios.
Usage: Easier to interpret visually and, therefore, often preferred for stakeholder reviews. Decision trees can help identify redundant or unnecessary steps within a decision-making process.
Test Case Foundation: Each path from the root to a leaf in a decision tree can serve as a test case scenario.
Decision Table:
Structure: Tabular in nature, decision tables have four sections - Condition Stub, Conditions, Action Stub, and Actions. The upper rows represent decision points, while the lower rows represent the outcomes.
Complexity: Effective for handling more complex scenarios involving multiple choices and conditions. Helps to make sure all combinations of conditions and their corresponding outcomes are considered.
Usage: Especially useful when the decision logic is complicated and a comprehensive evaluation of all possible scenarios is required.
Test Case Foundation: Each column in a decision table represents a business rule and can form the basis for a test case.
Common Use Cases:
Business Rules Modeling: Ideal for capturing complex business rules and conditions.
Elicitation and Analysis: Useful during the requirements gathering phase when branching "if-then-else" logic is identified.
Redundancy Elimination: Decision trees can be used to simplify complex decision logic by identifying redundancies.
Relationship to Requirements:
Both models can stand alone as a direct representation of business rules, which can be implemented either in the process or during development.
These models can also identify additional requirements or constraints necessary for supporting particular business rules or specific outcomes.
Understanding when to use a decision tree versus a decision table depends on the specific needs of the project, the complexity of the decision logic, and the stakeholders’ preference for visual representation. Both are invaluable tools for business analysts, especially in clarifying requirements and setting a foundation for test cases.