CS2013-final-report

CSC 207: Algorithms and Object-Oriented Design, Grinnell College
Grinnell, Iowa USA
Henry M. Walker
walker@cs.grinnell.edu
http://www.cs.grinnell.edu/~walker/courses/207.sp12/
Knowledge Areas that contain topics and learning outcomes covered in the course
Knowledge Area
Total Hours of Coverage
Software Development Fundamentals (SDF) 16
Algorithms and Complexity (AL) 14
Programming Languages (PL) 12
Software Engineering (SE) 3
Computational Science (CN) 1
Systems Fundamentals (SF) 1
Social Issues and Professional Practice (SP) 1
Brief description of the course’s format and place in the undergraduate curriculum
This course is the third in Grinnell's three-course, multi-paradigm introductory CS sequence. Many students are
second-year students, but the course also attracts third-year and fourth-year students who are majoring in other
fields but also want to expand their background on topics they found interesting in the first two courses. As with
Grinnell's other introductory courses, each class session meets in a lab, and work flows seamlessly between lecture
and lab-based activities. The course includes a significant emphasis on collaboration in pairs during 23 in-class
labs. Additional programming assignments and tests are done individually. All course materials, including
readings and all labs, are available freely over the World Wide Web.
Course description and goals
CSC 207, Algorithms and Object-Oriented Design, explores object-oriented problem solving using the Java
programming language. Topics covered include principles of object-oriented design and problem solving, abstract
data types and encapsulation, data structures, algorithms, algorithmic analysis, elements of Java programming, and
an integrated development environment (IDE) (e.g., Eclipse).
Course topics
Topics and themes covered include:
• Principles of object-oriented design and problem solving
◦ Objects and classes
◦ Encapsulation, abstraction, and information hiding
◦ Inheritance
◦ Polymorphism
◦ Unit testing
◦ Integration testing
• Abstract data types, data structures, and algorithms
◦ Dictionaries
◦ Hash tables
◦ Binary search trees
◦ Priority queues
◦ Heaps
• Algorithmic analysis
◦ Upper-bound efficiency analysis; Big-O Notation
- 460 -