Search results
Results from the WOW.Com Content Network
The Parsons problem format is used in the learning and teaching of computer programming. Dale Parsons and Patricia Haden of Otago Polytechnic developed Parsons's Programming Puzzles to aid the mastery of basic syntactic and logical constructs of computer programming languages, in particular Turbo Pascal , [ 1 ] although any programming language ...
The divide-and-conquer paradigm is often used to find an optimal solution of a problem. Its basic idea is to decompose a given problem into two or more similar, but simpler, subproblems, to solve them in turn, and to compose their solutions to solve the given problem. Problems of sufficient simplicity are solved directly.
Software developer Katrina Owen created Exercism while she was teaching programming at Jumpstart Labs. [6] The platform was developed as an internal tool to solve the problem of her own students not receiving feedback on the coding problems they were practicing.
Rather, it is a description or a template for solving a particular type of problem that can be deployed in many different situations. [2] Design patterns can be viewed as formalized best practices that the programmer may use to solve common problems when designing a software application or system.
The Computer Language Benchmarks Game (formerly called The Great Computer Language Shootout) is a free software project for comparing how a given subset of simple algorithms can be implemented in various popular programming languages.
Z3 was developed in the Research in Software Engineering (RiSE) group at Microsoft Research Redmond and is targeted at solving problems that arise in software verification and program analysis. Z3 supports arithmetic, fixed-size bit-vectors, extensional arrays, datatypes, uninterpreted functions, and quantifiers .
The General Problem Solver (GPS) is a particular computer program created in 1957 by Herbert Simon, J. C. Shaw, and Allen Newell intended to work as a universal problem solver, that theoretically can be used to solve every possible problem that can be formalized in a symbolic system, given the right input configuration.
Constraint programming (CP) [1] is a paradigm for solving combinatorial problems that draws on a wide range of techniques from artificial intelligence, computer science, and operations research. In constraint programming, users declaratively state the constraints on the feasible solutions for a set of decision variables.