1. Early Midterm
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.
Additionally, both slides and Ch. 1-3 of text contain information about topics not covered in other
Test questions may cover some of these topics.
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
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.
Some knowledge about when situation is out of hand
E.g., polynomial bound, exponential algorithms, intractible, etc.