Operating Systems: Key Concepts

A collection of data organized in a specific way, allowing efficient storage, retrieval, and manipulation of data. Examples include arrays, linked lists, trees, and graphs.

A step-by-step procedure or set of rules for solving a problem or performing a task. It must be finite, definite, and effective.

A method for solving problems by breaking them down into smaller, more manageable subproblems, solving each subproblem recursively, and combining the solutions to solve the original problem.

An algorithmic paradigm that makes the locally optimal choice at each step with the hope of finding the global optimum. However, it does not always guarantee the best solution.

An optimization technique where problems are solved by breaking them down into overlapping subproblems and saving the solutions to these subproblems to avoid recomputation.

A step-by-step procedure for visiting and processing each node in a tree data structure exactly once.

A searching algorithm that starts at the root node and explores each branch as far as possible before backtracking.

A searching algorithm that explores all the neighbors of the current node before moving to the next level of neighbors.

A sorting algorithm that repeatedly steps through the list, compares adjacent elements and swaps them if they are in the wrong order.

A sorting algorithm that divides the input array into two halves, recursively sorts each half, and then merges the sorted halves.