Epic Skills Assessment Algorithmic Problem Solving Questions and Answers — Questions and Answers
Question 1: A developer needs to find if any duplicate patient IDs exist in a very large list containing millions of encounter records. They are considering two approaches: Approach A: Use a nested loop. For each ID in the list, iterate through the rest of the list to check for a match. Approach B: Iterate through the list once, adding each ID to a Hash Set. If an ID is already in the set when attempting to add it, a duplicate has been found. Which statement best describes the performance of these two approaches as the list size grows?
- Both approaches have roughly the same efficiency.
- Approach A will be significantly more efficient than Approach B.
- The efficiency difference is minor and depends on the number of duplicates.
- Approach B will be significantly more efficient than Approach A. (Correct answer)
Correct answer: Approach B will be significantly more efficient than Approach A.
Approach A uses a nested loop, resulting in a time complexity of O(n^2), which is inefficient for large datasets. Approach B iterates through the list only once, and Hash Set lookups/insertions have an average time complexity of O(1) (constant time). Therefore, the total time complexity for Approach B is O(n), which is vastly more performant for large lists. [27, 29, 30]
Question 2: A programmer writes a recursive function to process a hierarchy of organizational units. The function calls itself for each child unit of the current unit. What is the most likely consequence if the programmer forgets to include a base case to stop the recursion (e.g., checking if a unit has no children)?
- The function will execute correctly but may be slow.
- The function will likely result in a stack overflow error. (Correct answer)
- The function will process only the top-level unit.
- The function will return a null value automatically.
Correct answer: The function will likely result in a stack overflow error.
A recursive function must have a base case, which is a condition that stops the function from calling itself. Without a base case, the function will call itself indefinitely, with each call being added to the call stack until the stack runs out of memory, causing a stack overflow error and crashing the program. [9, 24]
Question 3: An application needs to manage a collection of unique medication codes for a hospital's formulary. The most frequent operations will be adding a new code and checking if a specific code already exists. Which data structure is best suited for these requirements?
- Hash Set (Correct answer)
- Array (or List)
- Stack
- Queue
Correct answer: Hash Set
A Hash Set is the ideal data structure because it enforces uniqueness of its elements and provides very fast (average O(1) constant-time) lookups and insertions. An array would require a slower O(n) linear scan to check for existence. Stacks and Queues are not designed for efficient lookups. [18, 20, 23]
Question 4: A list of patient appointment check-in times is generated and is already *mostly* sorted, but a few entries are out of order. To finalize the sort, which of the following sorting algorithms would be the most efficient choice for this specific scenario?
- Merge Sort
- Selection Sort
- Insertion Sort (Correct answer)
- Quicksort
Correct answer: Insertion Sort
Insertion Sort has a best-case time complexity of O(n) when the data is already sorted or nearly sorted. It works by iterating through the list and only shifting elements when an out-of-place item is found, making it very efficient for this use case. Other algorithms like Merge Sort (O(n log n)) or Selection Sort (O(n^2)) do not adapt as well to nearly-sorted data. [5, 8, 17, 21]
Question 5: A developer needs to implement a function that searches for a specific patient ID within a very large, sorted array of millions of patient IDs. To ensure the function is as fast as possible, which search algorithm should be used?
- Sequential Search
- Linear Search
- Exhaustive Search
- Binary Search (Correct answer)
Correct answer: Binary Search
For a sorted collection, Binary Search is the most efficient algorithm. It works by repeatedly dividing the search interval in half, leading to a time complexity of O(log n). Linear (or Sequential) Search would check every element one by one, which is much slower with a time complexity of O(n). [2, 4, 6, 7]
Question 6: A business analyst requests a new feature: 'Display a list of all providers who have had at least one appointment in the last 30 days that started more than 15 minutes late.' From a problem-solving perspective, what is the most logical first step in designing the algorithm?
- Choose a data structure, like a list or set, to hold the final provider names.
- Identify the necessary input data: a list of appointments with provider, scheduled time, and actual start time. (Correct answer)
- Write a loop that iterates from today's date back 30 days.
- Design the user interface to display the list of providers.
Correct answer: Identify the necessary input data: a list of appointments with provider, scheduled time, and actual start time.
The first step in any algorithmic problem-solving process is to understand the problem by identifying the required inputs and expected outputs. Before any processing, filtering, or storing can occur, the developer must first define and figure out how to obtain the necessary data points (provider, scheduled time, actual start time) for each relevant appointment. [1, 3, 12, 13]
Epic Skills Assessment Algorithmic Problem Solving Questions and Answers
A developer needs to find if any duplicate patient IDs exist in a very large list containing millions of encounter records.
They are considering two approaches:
Approach A: Use a nested loop.
For each ID in the list, iterate through the rest of the list to check for a match.
Approach B: Iterate through the list once, adding each ID to a Hash Set.
If an ID is already in the set when attempting to add it, a duplicate has been found.
Which statement best describes the performance of these two approaches as the list size grows?