2014•Unpublished venueRequires access

The analysis and research on computational complexity

Qiang Gao, Xinhe Xu

Abstract

Computational complexity is a branch of the theory of computation. It is used to measure how hard a problem is solved and the common measures include time and space. The classes of time complexity generally include: P, NP, NP-hard, NP-complete and EXPTIME; the classes of space complexity generally include: PSPACE, NPSPACE, PSPACE-hard and PSPACE-complete. Researching computational complexity of a problem can make it explicit whether there is an effective solving algorithm of the problem or not. This paper introduces and analyzes some fundamental concepts of computational complexity, and discusses complete problems of time complexity and space complexity by examples; What's more, the relation among complexity classes is analyzed in detail.

About this research paper

What this paper is about

Why it matters

OpenAlex reports 13 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Key concepts: PSPACE, Computational complexity theory, Complexity class, Structural complexity theory, Descriptive complexity theory, Worst-case complexity, Asymptotic computational complexity, PH