arvutamisraskuse

Arvutamisraskus, often translated as computational difficulty or computational complexity, refers to the resources, typically time and memory, required to solve a computational problem. It is a fundamental concept in computer science and theoretical computer science, particularly within the field of complexity theory. Problems are classified based on their computational difficulty, allowing for a systematic understanding of which problems are tractable (solvable in a reasonable amount of time) and which are intractable (believed to be unsolvable in a practical timeframe).

The most common measure of computational difficulty is time complexity, which describes how the runtime of an algorithm grows as the size of the input increases. This is often expressed using Big O notation, such as O(n) for linear time or O(n^2) for quadratic time. Memory complexity, or space complexity, measures the amount of memory an algorithm needs. Problems are categorized into complexity classes like P (polynomial time solvable) and NP (nondeterministic polynomial time verifiable). The distinction between P and NP is a major open question in computer science, known as the P versus NP problem. Understanding arvutamisraskus is crucial for designing efficient algorithms and for determining the feasibility of solving complex real-world problems.