A basic algorithm course is about building up the abstract steps intended to solve a specific quandary. It introduces the going-to-be programmer to the fundamental tools mundanely utilized, namely reading from the standard input, writing on the standard output, conditional control structure, iterative control structure, and of course a trivial introduction to scalar data types (int [short], char, real [float, double], and boolean). The accompanying programming course is to concretize the aforementioned.
Further, the importance of data structures (their prerequisite are the scalar data types) appear when a beginner programmer has to move to "next level": manipulating arrays. Arrays allow to gather homogeneous values within one variable at run-time.
Niklaus Wirth made use of a very, very critical equation to entitle his book (Algorithms + Data Structures = Programs), in the 1970s already.
A data structures course is supposed to introduce students to the plethora of ways to organize data before engaging into its algorithmic solution.
The fate of a program's performance is fundamentally based on the choice of the data structure.
A virtuoso programmer may succeed to achieve the intended results most of the time, but might be surprised when their solution is adopted within a production environment, when the algorithm is going to be exposed to data of all kinds (vertically and horizontally).
A gullible programmer is the one who would try to solve the Towers of Hanoi using arrays. A sophomore student in Computer Science (recently introduced to recursion) might think that the recursive solution of the Towers of Hanoi problem is a perfect suggestion.
Would Facebook have been as efficient as it is, if any data structure other than Graphs was chosen?
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