WGU C949 DATA STRUCTURES AND ALGORITHMS OBJECTIVE ASSESSMENT ACTUAL EXAM 2025/2026 COMPLETE QUESTIONS BANK AND CORRECT DETAILED ANSWERS WITH RATIONALES || 100% GUARANTEED PASS <NEWEST VERSION>

WGU C949 DATA STRUCTURES AND ALGORITHMS OBJECTIVE ASSESSMENT ACTUAL EXAM 2025/2026 COMPLETE QUESTIONS BANK AND CORRECT DETAILED ANSWERS WITH RATIONALES || 100% GUARANTEED PASS &lt;NEWEST VERSION&gt; 1. Algorithm- ANSWER A set of instructions followed step by step to solve a problem 2. What are the 6 Characteristics of an Algorithm? - ANSWER Unambiguity Finiteness -finite number of steps, defined endpoint or output Well-defined inputs Effectiveness & Feasibility - doable and practicable. Language independence Well-defined outputs 3. What are the 8 Factors of an Algorithm? - ANSWER Modularity Correctness Maintainability Functionality Robustness User-friendly Simplicity Extensibility 4. What is a straightforward type of algorithm that exhaustively tries all possible solutions? - ANSWER Brute Force Algorithm 5. What algorithm method breaks a problem into smaller, similar subproblems and applies itself recursively? - ANSWER Recursive Algorithm 6. Which type of algorithm is used to transform data into a secure, unreadable form using cryptographic techniques? - ANSWER Encryption Algorithm 7. Which type of algorithm explores potential solutions by undoing choices when they lead to an incorrect outcome? - ANSWER Backtracking Algorithm 8. Which type of algorithm is designed to find a specific target within a dataset? - ANSWER Searching Algorithm 9. Which type of algorithm aims to arrange elements in a specific order? - ANSWER Sorting Algorithm 10. Which type of algorithm converts data into a fixed-size hash value for rapid access in hash tables? - ANSWER Hashing Algorithm 11. Which algorithm breaks a complex problem into smaller subproblems and combines their solutions? - ANSWER Divide and Conquer Algorithm 12. Which type of algorithm makes locally optimal choices at each step in the hope of finding a global optimum? - ANSWER Greedy Algorithm 13. Which type of algorithm stores and reuses intermediate results to enhance efficiency in solving complex problems? - ANSWER Dynamic Programming Algorithm 14. Which type of algorithm utilizes randomness in its steps to achieve a solution? - ANSWER Randomized Algorith 15. Ld(x) - ANSWER adds x at last element 16. L(x) - ANSWER removes the x element 17. Le(x) - ANSWER removes the x value 18. T(x) - ANSWER returns how many times x is in tuple 19. T(x) - ANSWER finds where x is located in the tuple 20. Se(set2) - ANSWER adds new set to current set 21. S(x) - ANSWER adds x to set 22. Se(x) - ANSWER finds x and removes from set 23. Binary Search Tree (BST) - Time Complexity - ANSWER MUST BE SORTED O(Log N) - O(N) 24. Graph - Vertex / Vertices - ANSWER Any node in the graph 25. Graph - Adjacency - ANSWER Any connection of the vertex 26. Graph - Edge - ANSWER The connection between vertices 27. Graph - Breadth Search - ANSWER TOP DOWN Approach 28. Graph - Depth Search - ANSWER TOP to FURTHEST LEFT Approach 29. Dijkstras's Algorithm - ANSWER Finds the shortest path from vertex to vertex. 30. Linear Search - ANSWER Sort Doesn't Matter O(N) 31. Binary Search - ANSWER DIVIDE AND CONQUER O(Log N) - O(N²)? 32. def find(lst, item, low, high, indent): """ Finds index of string in list of strings, else -1. Searches only the index range low to high Note: Upper/Lower case characters matter """ print(indent, 'find() range', low, high) range_size = (high - low) + 1 mid = (high + low) // 2 if item == lst[mid]: # Base case 1: Found at mid print(indent, 'Found person.') pos = mid elif range_size == 1: # Base case 2: Not found print(indent, 'Person not found.') pos = 0 else: # Recursive search: Search lower or upper half if item &lt; lst[mid]: # Search lower half print(indent, 'Searching lower half.') pos = find(lst, item, low, mid, indent + ' ') else: # Search upper half print(indent, 'Searching upper half.') pos = find(lst, item, mid+1, high, indent + ' ') print(indent, 'Returning pos = %d.' % pos) return pos attendees = [] d('Adams, Mary') d('Carver, Michael') d('Domer, Hugo') - ANSWER True 33. def find(lst, item, low, high, indent): """ Finds index of string in list of strings, else -1. Searches only the index range low to high Note: Upper/Lower case characters matter """ print(indent, 'find() range', low, high) range_size = (high - low) + 1 mid = (high + low) // 2 if item == lst[mid]: # Base case 1: Found at mid print(indent, 'Found person.') pos = mid elif range_size == 1: # Base case 2: Not found print(indent, 'Person not found.') pos = 0 else: # Recursive search: Search lower or upper half if item &lt; lst[mid]: # Search lower half print(indent, 'Searching lower half.') pos = find(lst, item, low, mid, indent + ' ') else: # Search upper half print(indent, 'Searching upper half.') pos = find(lst, item, mid+1, high, indent + ' ') print(indent, 'Returning pos = %d.' % pos) return pos attendees = [] d('Adams, Mary') d('Carver, Michael') d('Domer, Hugo') - ANSWER True 34. def find(lst, item, low, high, indent): """ Finds index of string in list of strings, else -1. Searches only the index range low to high Note: Upper/Lower case characters matter """ print(indent, 'find() range', low, high) range_size = (high - low) + 1 mid = (high + low) // 2 if item == lst[mid]: # Base case 1: Found at mid print(indent, 'Found person.') pos = mid elif range_size == 1: # Base case 2: Not found print(indent, 'Person not found.') pos = 0 else: # Recursive search: Search lower or upper half if item &lt; lst[mid]: # Search lower half print(indent, 'Searching lower half.') pos = find(lst, item, low, mid, indent + ' ') else: # Search upper half print(indent, 'Searching upper half.') pos = find(lst, item, mid+1, high, indent + ' ') print(indent, 'Returning pos = %d.' % pos) return pos attendees = [] d('Adams, Mary') d('Carver, Michael') d('Domer, Hugo') - ANSWER False 35. A recursive function with parameter n counts up from any negative number to 0. An appropriate base case would be n == 0. - ANSWER True 36. A recursive function can have two base cases, such as n == 0 returning 0, and n == 1, returning 1. - ANSWER True 37. n factorial (n!) is commonly implemented as a recursive function due to being easier to understand and executing faster than a loop implementation. - ANSWER False 38. In the code below, suppose str1 is a pointer or reference to a string. The code only executes in constant time if the assignment copies the pointer/reference, and not all the characters in the string. srt2 = str1 - ANSWER True 39. Certain hardware may execute division more slowly than multiplication, but both may still be constant time operations. - ANSWER True 40. The hardware running the code is the only thing that affects what is and what is not a constant time operation. - ANSWER False 41. Computational complexity analysis allows the efficiency of algorithms to be compared. - ANSWER True 42. Two different algorithms that produce the same result have the same computational complexity. - ANSWER False 43. Runtime and memory usage are the only two resources making up computational complexity. - ANSWER False