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In object-oriented programming, a parent class is a class that is extended by another class, known as a child class. A grandparent class, on the other hand, is a class that is higher up in the inheritance hierarchy and is not directly extended by the child class. The key difference is that a parent class is directly related to the child class, while a grandparent class is further up the inheritance chain.

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What are the key differences between assembly language and programming language?

Assembly language is a low-level programming language that uses mnemonic codes to represent machine instructions directly. It is specific to a particular computer architecture and is closer to the hardware. On the other hand, a programming language is a high-level language that uses English-like syntax and is more abstract, making it easier for programmers to write and understand code. Programming languages are not tied to a specific computer architecture and are typically more portable and easier to maintain than assembly language.


What are the key differences between gfortran and Fortran 77?

gfortran is a modern open-source compiler for Fortran, while Fortran 77 is an older version of the Fortran programming language. Some key differences include improved features and optimizations in gfortran, better compatibility with modern systems, and support for newer language standards beyond Fortran 77.


What is the strong duality proof for linear programming problems?

The strong duality proof for linear programming problems states that if a linear programming problem has a feasible solution, then its dual problem also has a feasible solution, and the optimal values of both problems are equal. This proof helps to show the relationship between the primal and dual problems in linear programming.


What is the difference between a precondition and postcondition in C programming?

In C programming, a precondition is a condition that must be true before a function is called, while a postcondition is a condition that is guaranteed to be true after the function has been executed.


What are the key differences between dynamic programming and memoization, and how do they impact the efficiency and effectiveness of solving complex problems?

Dynamic programming and memoization are both techniques used to optimize the efficiency of solving complex problems by storing and reusing intermediate results. The key difference lies in their approach: dynamic programming solves problems by breaking them down into smaller subproblems and solving them iteratively, while memoization stores the results of subproblems to avoid redundant calculations. Dynamic programming can be more efficient for problems with overlapping subproblems, as it avoids recalculating the same subproblems multiple times. However, it may require more space and time complexity due to the iterative nature of solving subproblems. On the other hand, memoization can be more effective for problems with a recursive structure, as it stores the results of subproblems in a table for quick access. This can reduce the time complexity of the algorithm, but may require more space to store the results. In summary, dynamic programming is more suitable for problems that can be solved iteratively, while memoization is better for recursive problems. The choice between the two techniques depends on the specific problem and the trade-off between time and space complexity.

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