Unit 7 Session 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: lst = [1, 3, 5, 7, 9], target = 5
Output: True
Explanation: The target value 5 exists in the list, so the function returns True.
EDGE CASE
Input: lst = [1, 3, 5, 7, 9], target = 2
Output: False
Explanation: The target value 2 does not exist in the list, so the function returns False.
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.
This problem is a classic application of binary search, using recursion to reduce the search space efficiently:
Plan the solution with appropriate visualizations and pseudocode.
General Idea: Use binary search to find if the target exists in the list.
1) Initialize two pointers, `left` and `right`, at the start and end of the list, respectively.
2) While `left` is less than or equal to `right`:
a) Compute the middle index `mid`.
b) If the element at `mid` is the target, return True.
c) If the target is less than the element at `mid`, adjust `right` to `mid - 1`.
d) If the target is greater than the element at `mid`, adjust `left` to `mid + 1`.
3) Return False if the target is not found after exhausting the search.
⚠️ Common Mistakes
Implement the code to solve the algorithm.
def binary_search(lst, target):
# Initialize left and right pointers
left, right = 0, len(lst) - 1
# Iterate while left pointer is less than or equal to right pointer
while left <= right:
# Find the middle index
mid = (left + right) // 2
# If the middle element is the target, return True
if lst[mid] == target:
return True
# If the target is less than the middle element, search the left half
elif lst[mid] > target:
right = mid - 1
# If the target is greater than the middle element, search the right half
else:
left = mid + 1
# If target is not found, return False
return False
Review the code by running specific example(s) and recording values (watchlist) of your code's variables along the way.
Evaluate the performance of your algorithm and state any strong/weak or future potential work.
Assume n
represents the length of the list.
O(log n)
because the binary search algorithm halves the search space with each iteration.O(1)
because we only use a few variables for pointer management, without any additional data structures.