Algorithms & Programming Fundamentals

The execution time decreases inversely with n.

The execution time remains constant regardless of n.

The execution time increases quadratically.

The execution time increases linearly with n.

Multithreaded execution within single process context

Shared-memory model using mutex locks

Event-driven programming relying on I/O callbacks

Actor model coordinating via message passing

As linear searches can only operate on unsorted data, removing the need for initial sorting.

Because linear search uses less memory during operation due to the absence of recursive calls.

Since all elements must be checked anyway, linear searches find targets quicker if they tend to appear early in the list.

Because overhead costs make binary search less effective on small lists despite its lower Big O notation value.

Random search

Binary search

Linear search

Unordered search

HTTP (Hypertext Transfer Protocol)

RTP (Real-Time Protocol)

FTP (File Transfer Protocol)

SMTP (Simple Mail Transfer Protocol)

Merge Sort

Binary Search

Quick Sort

Bubble Sort

O(N)

O(√N)

O(2^N)

O(NlogN)

Singly linked lists require traversal of the entire data structure.

Performance degrades due to comparisons needed to find the right placement; hence worst case becomes quadratic.

Even though accessing the next node is a simple operation, it still involves parsing each element.

Removing front or back does not affect the remaining nodes thus constant.

It helps developers focus on high-level concepts without worrying about low-level details.

It ensures that all possible cases are handled explicitly, making programs longer but easier to understand.

It allows programmers to write code that can be understood only by experts in a given field.

It requires developers to use more complex syntax and structures to improve program efficiency.

It allows programmers to consider operations without needing specific implementation details, facilitating comparisons between different algorithms' efficiencies.

By requiring detailed knowledge of how data is represented internally leading to better optimized code.

ADTs mandate adding extra layers of complexity.

The explicit definition associated with ADTs forces algorithm designers into tighter constraints, decreasing efficiency potential.