The list must be sorted.

Binary search eliminates half of the search space with each step, resulting in logarithmic time complexity.

Binary search uses a divide and conquer approach by repeatedly dividing the search space in half.

The target element is not in the list, requiring the algorithm to eliminate all possible elements.

The target element is the middle element in the first step.

By comparing the target value to the middle element and eliminating half of the list in each step.

Sorting ensures that elements are in a predictable order, allowing binary search to correctly narrow down the search space.

It serves as the pivot point for comparison, determining which half of the list to eliminate.

Comparisons determine whether the target value is greater than, less than, or equal to the middle element, guiding the search.

Binary search performs significantly better on larger lists compared to linear search due to its logarithmic time complexity.

1. Sort the list. 2. Find the middle element. 3. Compare with the target. 4. Eliminate half the list. 5. Repeat until found or not found.

1. Ensure the list exists. 2. Populate the list with data. 3. Sort the list in ascending or descending order.

1. Compare the target with the middle element. 2. If target is greater, set low to mid + 1. 3. If target is smaller, set high to mid - 1.

1. Continue dividing and comparing until low > high. 2. If low > high, the target is not in the list. 3. Return a 'not found' indicator (e.g., -1).

1. Get the sorted list. 2. Define the target value. 3. Initialize low to 0 and high to len(list) - 1.

1. Sum low and high index. 2. Divide sum by 2. 3. Take the integer part of the result.

1. Check if target equals middle element. 2. If equal, the target is found. 3. If not equal, proceed to eliminate half of the list.

1. If target > middle element, set low = mid + 1. 2. If target < middle element, set high = mid - 1.

1. Check if low <= high. 2. If true, repeat steps to find the middle element and compare. 3. If false, target is not found.

1. Return the index of the middle element. 2. Terminate the search. 3. Optionally, perform additional actions (e.g., print a message).

Linear Search: Works on unsorted lists, O(n) time complexity | Binary Search: Requires sorted lists, O(log n) time complexity.

Linear Search: Less efficient, checks each element | Binary Search: More efficient, eliminates half of the data with each step.

Linear Search: Minimal, no extra memory needed | Binary Search: Minimal, no significant extra memory needed.

Linear Search: Simple to implement | Binary Search: More complex to implement due to sorting and halving.

Linear Search: Target is the first element | Binary Search: Target is the middle element.

Linear Search: Target is the last element or not present | Binary Search: Target is not present.

Linear Search: Applicable to unsorted lists | Binary Search: Not applicable to unsorted lists.

Linear Search: Performance degrades linearly with data size | Binary Search: Performance degrades logarithmically with data size.

Linear Search: Easier to understand | Binary Search: More complex to understand.

Linear Search: No preprocessing needed | Binary Search: Requires preprocessing (sorting).