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WGU Foundations-of-Computer-Science Exam Syllabus Topics:

SectionObjectives
Topic 1: Operating Systems & Architecture- OS Fundamentals
  • 1. Process states and scheduling basics
    • 2. Memory management concepts
      - System Architecture
      • 1. Hardware vs software abstraction
        • 2. Von Neumann architecture basics
          Topic 2: Data & Security Basics- Data Handling
          • 1. Data profiling concepts
            • 2. Basic database concepts overview
              - Security Fundamentals
              • 1. Encryption basics (at rest vs in transit)
                • 2. Basic cybersecurity threats and mitigation
                  Topic 3: Computer Science Fundamentals- Core CS Concepts
                  • 1. Algorithm efficiency and Big-O basics
                    • 2. Computational thinking and problem solving
                      • 3. Basic programming logic and algorithms
                        - Data Structures Introduction
                        • 1. Basic sorting and searching concepts
                          • 2. Arrays and lists
                            Topic 4: Programming Foundations- Language Concepts Overview
                            • 1. Compiled vs interpreted languages
                              • 2. Programming paradigms overview
                                - Programming Concepts
                                • 1. Control flow (if/else, loops)
                                  • 2. Variables, data types, expressions
                                    • 3. Basic pseudocode interpretation

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                                      WGU Foundations of Computer Science Sample Questions (Q42-Q47):

                                      NEW QUESTION # 42
                                      What is traversal in the context of trees and graphs?

                                      Answer: B

                                      Explanation:
                                      In data structures and algorithms,traversalrefers to systematicallyvisiting nodesin a tree or graph in order to process them. "Visiting" typically means performing some operation at each node, such as reading its value, marking it as seen, computing a property, or collecting it into an output structure. Traversal is foundational because many algorithms-search, path finding, connectivity checks, topological analysis, and evaluation of expressions-are built on traversal patterns.
                                      Intrees, traversal has classic forms: preorder, inorder, and postorder depth-first traversals, as well as breadth- first traversal (level-order). Each defines a rule for the order in which nodes are visited relative to their children. Ingraphs, traversal must additionally handle the possibility of cycles and multiple paths; textbooks therefore emphasize maintaining a "visited" set to avoid infinite loops. The two principal graph traversal strategies areDepth-First Search (DFS)andBreadth-First Search (BFS). DFS explores along a path as far as possible before backtracking, while BFS explores layer by layer outward from a start node.
                                      Options A, B, and C do not define traversal. Changing values may happen during traversal, but it is not what traversal means. Removing all nodes is deletion, not traversal. Connecting all nodes is not a standard traversal concept. The correct definition is the process of visiting all nodes (typically reachable from a starting node, or all nodes in the structure if fully connected).


                                      NEW QUESTION # 43
                                      What is the time complexity of a binary search algorithm?