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Early Term Test

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  1. Early Term Test Some Study Reminders

  2. General Topics • Sources for information to be tested are • My slides and classroom presentations of slides • Chapter 1-3 of textbook • Problems assigned as homework • Chapters 1-3 of textbook provide additional information about material covered on slides. • Understand material covered in homework problems • Most test questions will not be identical to problem question. • In particular, at least the data will probably be different.

  3. Some Items in Chapter 1 • Need good working understanding of “computer science” definition • E.g., understand its different parts • Need good working understanding of the properties “algorithm” • well-ordered, unambiguous, effectively computable, terminates,etc • Ability to identify whether a sequence of statements is an algorithm and explain why. • Have an understanding of the more important events and contributions of major players & events in CS history. • No emphasis on knowing precise dates • Know general time period that important events occurred. • E.g., Decade, During WW2, etc. • No emphasis on details of how devices work • Should know their purpose, esp. for more important devices.

  4. Some Items from Chapter 2 • Understanding the different issues involved in representing algorithms • Understanding the different types of operations required to represent algorithms. • Understanding the algorithms discussed in class. • Should be able to execute algorithm on data • Deciding whether or not an algorithm solves the problem it was intended to solve.

  5. Some Items from Chapter 3 • Understanding the concept of complexity • Understanding meaning and importance of both time and space complexity • Determining worst case or best case complexity for simple examples – especially variants of algorithms studied. • What operation(s) to choose in measuring time complexity • Knowing complexities of algorithms we have studied • Being able to recall and execute algorithms we have discussed in Chapter 2-3 on specific data. • Addition, telephone search, data cleanup, searching, sorting, pattern matching, etc. • Making simple modifications to algorithms studied. • Some knowledge about when “situation is out of hand” • E.g., polynomial bound, exponential algorithms, intractible, etc.

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