In database design and normalization, a dependency graph (also called a functional-dependency diagram) uses nodes and directed arcs to illustrate attributes and their dependency relationships across a database schema. Is this description accurate?

Introduction / Context:
Dependency graphs, often called functional-dependency (FD) diagrams, are visual tools used during logical database design and normalization. They show which attributes depend on which other attributes so designers can identify potential redundancy, update anomalies, and the need for decompositions into higher normal forms such as 3NF and BCNF.

Given Data / Assumptions:

• A database schema contains relations (tables) and attributes (columns).
• Functional dependencies describe rules such as A -> B, meaning attribute A functionally determines attribute B.
• Graphs use nodes to represent attributes or attribute sets and directed arcs to indicate determination.

Concept / Approach:
By modeling dependencies as a directed graph, designers can quickly see determinants, candidate keys, and transitive chains. This supports decisions about decomposition to eliminate partial and transitive dependencies, thereby reducing redundancy and anomalies.

Step-by-Step Solution:
List discovered functional dependencies from requirements or profiling.Create nodes for attributes or attribute groups (e.g., {OrderID}, {CustomerID}, {CustomerCity}).Draw directed arcs from each determinant to the attributes it determines.Identify keys as determinants that reach all other attributes in the relation.Use the diagram to plan decompositions that remove non-key determinants.

Verification / Alternative check:
Cross-check the graph with normalization rules; if non-key determinants exist, anomalies are likely. Confirm by testing sample inserts/updates for inconsistency risks.

Why Other Options Are Wrong:
It is not limited to hierarchical databases; it is primarily used with relational schemas. “Cannot be determined” is incorrect because the definition of the diagram does not require sample data.

Common Pitfalls:
Confusing foreign-key relationships with functional dependencies, or omitting composite determinants (e.g., A,B -> C) from the diagram.

Final Answer:
Correct