CS350: Data Structures Class Notes
Class 1: Monday, September 1, 2008
Today we began with the usual organizational stuff—went over the syllabus, talked about
the web page and book, etc. In particular,
• You may want to pick up a copy of Python Pocket Reference by Mark Lutz, ISBN
0-596-00940-2. If you have an unmarked copy, you can use this during testing.
Highlighting and your name are okay.
• Be sure to get the errata for your text.
Please read the syllabus.
Overview of the course
We tried to put the course in context by addressing the following four questions:
1. What is computer science? We didn’t really attempt to answer this question.
Everyone should have a idea ant this is really a moving target. If pressed, a common
definition is the study of algorithms.
2. What is computer engineering? If pressed, a common definition is applying
engineering principles to computer hardware.
3. What is software engineering? If pressed, a common definition is applying
engineering principles to computer software.
4. What is data structures? If pressed, a common definition is the study of both the
organization of data and of the algorithms used to manipulate data. The separation of
data structures and algorithms unclear at best.
Program Life Cycle
Different authors draw different distinctions, but basically we include:
1. Analysis—This includes identifying the relevant data and the operations on that
data.
2. Design—This includes organizing the data and identifying algorithms that will be
used.
3. Implementation or Coding
4. Testing & Debugging
5. Maintenance
Other possible items include specification, risk analysis, unit coding and unit testing as
opposed to system coding and system testing, deployment, etc. For our purposes, we will
