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by betterunix
4575 days ago
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I disagree; abstractions are good, and it is more important for students to learn to think abstractly than to learn how a computer works "under the hood." The vast majority of computing tasks involve abstract problems with abstract solutions -- computing account balances, querying databases, cryptography, UIs, networking, etc. Even basic things in a CS curriculum like data structures and algorithms require abstract approaches and gain very little from knowing low-level details. There is a place for the low-level details: computer architecture, compilers, and operating systems. Students should take these courses to be well-rounded and to see how theory is translated into practice, but elsewhere things should be done at a high level. |
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I'd disagree somewhat. Data structures, from a CS perspective, often involve learning about low-level implementation details (why is accessing a hash O(1)? Why do array elements have to be the same size? What's the difference between representing a graph as a linked list versus a 2-dimensional matrix?). It's similar with algorithms.
Even though you CAN use completely abstract computational models to learn algorithms, many of the most important algorithms are designed around tradeoffs between real-world resources and being able to map abstract algorithms to a low-level language like C is a very useful skill to those who have it.