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NC = P problem The P vs NP problem is a major unsolved question in computer science that asks whether every problem whose solution can be quickly verified by a computer (NP) can also be quickly solved by a computer (P). This question has profound implications for fields such as cryptography, algorithm design, and computational theory. [1]
Computer science is the study of computation, information, and automation. [1] [2] [3] Computer science spans theoretical disciplines (such as algorithms, theory of computation, and information theory) to applied disciplines (including the design and implementation of hardware and software).
Donald Knuth - The Art of Computer Programming; Ellen Ullman - Close to the Machine; Ellis Horowitz - Fundamentals of Computer Algorithms; Eric Raymond - The Art of Unix Programming; Gerald M. Weinberg - The Psychology of Computer Programming; James Gosling - The Java Programming Language; Joel Spolsky - The Best Software Writing I
For example, one of the long-standing open questions in computer science is to determine whether there is an algorithm that outperforms the 2-approximation for the Steiner Forest problem by Agrawal et al. [3] The desire to understand hard optimization problems from the perspective of approximability is motivated by the discovery of surprising ...
The question of whether P equals NP is one of the most important open questions in theoretical computer science because of the wide implications of a solution. [3] If the answer is yes, many important problems can be shown to have more efficient solutions.
SICP has been influential in computer science education, and several later books have been inspired by its style. Structure and Interpretation of Classical Mechanics (SICM), another book that uses Scheme as an instructional element, by Gerald Jay Sussman and Jack Wisdom; Software Design for Flexibility, by Chris Hanson and Gerald Jay Sussman
In computer science, brute-force search or exhaustive search, also known as generate and test, is a very general problem-solving technique and algorithmic paradigm that consists of systematically checking all possible candidates for whether or not each candidate satisfies the problem's statement.
Code: The Hidden Language of Computer Hardware and Software; Compilers: Principles, Techniques, and Tools; Computer Graphics: Principles and Practice; Computers and Intractability; Concepts, Techniques, and Models of Computer Programming; Concrete Mathematics