JCSU Unit 2 Problem Set 1 (Click for link to problem statements)
Understand what the interviewer is asking for by using test cases and questions about the problem.
- Established a set (2-3) of test cases to verify their own solution later.
- Established a set (1-2) of edge cases to verify their solution handles complexities.
- Have fully understood the problem and have no clarifying questions.
- Have you verified any Time/Space Constraints for this problem?
HAPPY CASE Input: nested_list = [ [1, 2], [3, 4], [5, 6] ] Output: [1, 2, 3, 4, 5, 6] Explanation: The nested list is flattened to a single list containing all elements.
EDGE CASE Input: nested_list = [[]] Output: [] Explanation: An empty list of lists results in an empty flattened list.
Match what this problem looks like to known categories of problems, e.g. Linked List or Dynamic Programming, and strategies or patterns in those categories.
For list flattening problems, we want to consider the following approaches:
Plan the solution with appropriate visualizations and pseudocode.
General Idea:
Iterate through each sublist in the nested list, and then iterate through each element in the sublist. Append all elements to a new list in order.
flattened to store the flattened elements.nested_list:
flattened.flattened list.Implement the code to solve the algorithm.
def flatten_list(nested_list):
flattened = [] # Initialize an empty list to store the flattened elements
for sublist in nested_list: # Iterate through each sublist in the nested list
for element in sublist: # Iterate through each element in the sublist
flattened.append(element) # Append the element to the flattened list
return flattened # Return the flattened list
Review the code by running specific example(s) and recording values (watchlist) of your code's variables along the way.
Example 1:
Example 2:
Evaluate the performance of your algorithm and state any strong/weak or future potential work.
Assume n is the total number of elements in all sublists.
