Class 01: Introduction to the Course

Held Friday, August 25, 2000

Summary

Today we begin CSC152 by considering the core subject matters of the course: computer science, data structures, algorithms, and object-oriented design.

Notes

• Assignments:
  • Scan through the course web
  • Fill out the introductory survey by Monday's class.
  • Read lab J1 for Monday.
  • Read Appendix A of Bailey for Monday.
• Make sure to complete the introductory survey for Monday's class (there are always a few students who forget, and I really hate to embarass them in class).
  • It helps me if you fill out the survey sooner rather than later. I'll be reading about 50 surveys this weekend.

Overview

• Course overview
• Definition of computer science
• Introduction to data structures and algorithms
• Introduction to programming paradigms

About This Class

• CS152 is primarily a course in Data Structures and Algorithms. At some institutions, it has that name.
  • A data structure is a formalism for organizing and managing data. Often, the way you organize the information in your program permits or inhibits particular operations. Different structures may also lead to different costs (in time or space).
  • An algorithm expresses the steps involved in completing a task.
• CS152 is also a course in imperative and object-oriented programming.
  • Presumably, you've seen a little bit of each in CS151 (or whatever course you've taken previously). We will certainly talk more about both paradigms.
  • We will be doing our programming in Java. In the past, I've said that the language we use is less important than the concepts we learn. However, I must emphasize that you will not learn the concepts unless you also learn Java.
• Like most computer science courses, CS152 will have both theoretical and practical components. I hope you will enjoy relating the two.

Grounding Ourselves

• Before we delve too far into these issues, we should ground ourselves somewhat by asking ourselves a few questions (and I'll be asking these of the class).
  • What is Computer Science?
  • What is Computer Programming?
  • How are they similar? How are they different?
  • What is an algorithm?
  • What is a computer program?
• We also want to ask ourselves some practical questions.
  • What programming languages do we know?
  • What CS or programming concepts are we least comfortable with?
  • How comfortable are we with the workstations and Unix?
• Finally, I'd like you to reflect on the course (and you'll be doing this again on the introductory survey).
  • Why are you taking this course?
  • What do you expect to get out of this class?

Administrative Issues

• Please refer to the course web site for details.
• Teaching philosophy: I support your learning
• Policies
  • Attendance: I expect you to attend every class. Let me know when you'll miss class and why.
  • Grading: I'm a hard grader. I don't grade everything.
  • Course web
  • Etc.
• The exams
  • Three take-home exams during the semester. Plan to spend ten hours on each one.
  • An optional final to make up for a bad exam grade. (Last semester, I didn't give a final and just dropped the lowest exam. This semester, I'm much more likely to give the final.)
• The lab manual
  • Available online (locally only)
  • Using the online labs is okay.
  • Yes, you must buy a copy.
  • I will rarely collect labs. When I do, you can just summarize your answers on a separate sheet of paper.
  • No, I don't receive royalties.
• The book
  • Small, but expensive (what do you expect for a CS book?)
  • Written for a liberal arts audience
• Projects
  • The tradition is to do a large project
  • I'll list a few possibilities: Email client, Game, Image processing package, Four years at a glance, PseudoVax

Programming Paradigms

• Computer Scientists have developed a number of strategies for looking at algorithm and data design, including
  • procedural / imperative
  • object-oriented
  • functional
  • logical
  • declarative
• While individual definitions of each category may differ, most definitions have some similarities.
• In CS151, you studied functional and imperative programming.
• In CS152, you will study object-oriented and imperative programming.

An Introduction to Data Structures

• This semester, we'll talk about data structures and abstract data types. Many computer scientists treat them as equivalent terms.
• An abstract data type (ADT) is a collection of values and operations on those values. ADTs specify the what of data.
• A data structure is a structure designed to organize data.
• When we distinguish the two, we sometimes say that data structures implement abstract data types.
• Those of you coming from the Scheme-based 151 may already be familiar with two basic ADTs: the list and the vector.
• Both lists and vectors gather data into a sequence.
• More importantly, they provide facilities for manipulating the sequence.
  • You can extract an element from the sequence.
  • You can change an element in the sequence.
  • (Sometimes) you can insert or remove an element from the sequence.
• Vectors and lists differ in the operations they provide and the costs associated with each operation.
• In designing and building your own ADTs, you will be concerned with
  • The specification -- the description of the data structure and the operations it provides.
  • The implementation -- how you actually provide those operations (and how you store the data to provide those operations).
  • The algorithms used in the implementation.
  • The efficiency of your implementation -- how much it costs to provide those operations.
  • The applications of the data structure.
• Note that we want a clear barrier between specification and implementation, so that a client of one of your data structures need only know what you do and not how you do it. We often call this separation encapsulation or information hiding.
• This term, we will be looking at each of these aspects of a number of the key data structures in CS.