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  • A primary concern for this course is efficiency. You might believe that faster computers make it unnecessary to be concerned with efficiency. However… So we need special training.
  • If you are willing to pay enough in time delay. Example: Simple unordered array of records.
  • Alternate definition: Better than known alternatives (“relatively efficient”). Space and time are typical constraints for programs. This does not mean always strive for the most efficient program. If the program operates well within resource constraints, there is no benefit to making it faster or smaller.
  • Typically want the “simplest” data structure that will meet the requirements.
  • These questions often help to narrow the possibilities. If data can be deleted, a more complex representation is typically required.
  • The space required includes data and overhead. Some data structures/algorithms are more complicated than others.
  • The first goal is a worldview to adopt The second goal is the “nuts and bolts” of the course. The third goal prepares a student for the future.
  • The concept of an ADT is one instance of an important principle that must be understood By any successful computer specialist: managing complexity through abstraction.
  • In this class, we frequently move above and below “the line” separating logical and physical forms.
  • But NO constraints on HOW the problem is solved
  • “ Correct” means computes the proper function. “ Concrete steps” are executable by the machine in question. We frequently interchange use of “algorithm” and “program” though they are actually different concepts.
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