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  2. CS50 - Wikipedia

    en.wikipedia.org/wiki/CS50

    CS32 (Computational Thinking and Problem Solving), taught by Michael D. Smith, [29] is an alternative to CS50 but does not have a free online version. [30] The next course in sequence after CS32 or CS50 is CS51: Abstraction and Design in Computation, instructed by Stuart M. Shieber with Brian Yu as co-instructor. [31]

  3. Geometric constraint solving - Wikipedia

    en.wikipedia.org/wiki/Geometric_constraint_solving

    Geometric constraint solving is constraint satisfaction in a computational geometry setting, which has primary applications in computer aided design. [1] A problem to be solved consists of a given set of geometric elements and a description of geometric constraints between the elements, which could be non-parametric (tangency, horizontality, coaxiality, etc) or parametric (like distance, angle ...

  4. David J. Malan - Wikipedia

    en.wikipedia.org/wiki/David_J._Malan

    David Jay Malan (/ m eɪ l ɛ n /) is an American computer scientist and professor. Malan is a Gordon McKay Professor of Computer Science at Harvard University, and is best known for teaching the course CS50, [2] [3] which is the largest open-learning course at Harvard University and Yale University and the largest massive open online course at EdX, with lectures being viewed by over a million ...

  5. SAT solver - Wikipedia

    en.wikipedia.org/wiki/SAT_solver

    In computer science and formal methods, a SAT solver is a computer program which aims to solve the Boolean satisfiability problem.On input a formula over Boolean variables, such as "(x or y) and (x or not y)", a SAT solver outputs whether the formula is satisfiable, meaning that there are possible values of x and y which make the formula true, or unsatisfiable, meaning that there are no such ...

  6. Constraint satisfaction problem - Wikipedia

    en.wikipedia.org/wiki/Constraint_satisfaction...

    Constraint satisfaction problems (CSPs) are mathematical questions defined as a set of objects whose state must satisfy a number of constraints or limitations. CSPs represent the entities in a problem as a homogeneous collection of finite constraints over variables , which is solved by constraint satisfaction methods.

  7. Answer set programming - Wikipedia

    en.wikipedia.org/wiki/Answer_set_programming

    In ASP, search problems are reduced to computing stable models, and answer set solvers—programs for generating stable models—are used to perform search. The computational process employed in the design of many answer set solvers is an enhancement of the DPLL algorithm and, in principle, it always terminates (unlike Prolog query evaluation ...

  8. Computational thinking - Wikipedia

    en.wikipedia.org/wiki/Computational_thinking

    Computational thinking (CT) refers to the thought processes involved in formulating problems so their solutions can be represented as computational steps and algorithms. [1] In education, CT is a set of problem-solving methods that involve expressing problems and their solutions in ways that a computer could also execute. [ 2 ]

  9. Core Python Programming - Wikipedia

    en.wikipedia.org/wiki/Core_Python_Programming

    Core Python Programming is a textbook on the Python programming language, written by Wesley J. Chun. The first edition of the book was released on December 14, 2000. [1] The second edition was released several years later on September 18, 2006. [2] Core Python Programming is mainly targeted at higher education students and IT professionals. [3]

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