Algorithms designed to solve problems involving combinations, arrangements, and selections of discrete objects.

The process of determining the efficiency and performance of an algorithm, focusing on time and space complexity.

A mathematical notation used to describe the upper limit of an algorithm's time complexity, indicating its worst-case scenario.

A measure of the amount of time an algorithm takes to complete as a function of the input size.

A measure of the amount of memory space an algorithm uses as a function of the input size.

A field of mathematics that studies graphs, which are structures used to model pairwise relations between objects.

Arrangements of a set of objects in a specific order, crucial in combinatorial problems.

Selections of items from a larger pool, where the order does not matter, significant in probability and statistics.

A programming technique where a function calls itself to solve smaller instances of the same problem.

Techniques that involve repeating a set of operations until a condition is met, often used in algorithm design.

Methods used to improve the efficiency of algorithms, reducing time or space complexity.

The process of identifying and removing errors from computer programs to ensure correct functionality.

A high-level description of an algorithm that uses the structural conventions of programming languages but is intended for human reading.

An in-depth analysis of a specific instance or project, used to illustrate the application of algorithms in real-world scenarios.

Organized formats for storing and managing data, essential for effective algorithm implementation.

The process of searching for the best solution from a finite set of solutions in combinatorial problems.

The process of defining a step-by-step procedure for solving a specific problem.

Algorithms that perform operations using the least amount of resources possible, optimizing performance.

Using graphical representations to analyze and present the complexity of algorithms.

The skill of conveying complex information clearly and effectively to various audiences.

Practical uses of algorithms in solving actual problems in fields like computer science and operations research.

The process of effectively communicating the results and findings of algorithmic research or projects.

Methods for evaluating and learning from one's experiences to enhance future performance.

Fundamental concepts that guide the study of combinations and arrangements in mathematics.

The actual coding and execution of an algorithm in a programming language.

The study of the resources required for an algorithm to run, including time and space.