Goals and Outcomes

Understand several interesting data structures and their properties.
Learn how to use data structures and other tools to solve problems in various application areas.
Gain experience in reading the relevant research literature and other publications used to disseminate knowledge in the ﬁeld.
Practice the appropriate and ethical use of existing material of diﬀerent kinds, such as source code, services, and documentation.
Gain experience in contributing to the body of knowledge.
Learn how to analyze of the running times of programs using simple mathematical methods.
Gain experience in conducting and documenting experimental studies of programs.
Improve our programming skills, with attention to software engineering principles.
Improve our communication skills, with particular emphasis on written communication and, further, well-written programs.

Upon successful completion of this course, students are able to

List commonly used data structures, and the advantages and drawbacks of each.
Determine suitable data structures for solving a given problem.
Eﬀectively read suitable publications related to the topic.
Use resources such as others’ code and writing in an ethical and professional manner.
Contribute to the body of knowledge at an undergraduate level.
Analyze the running times of programs using simple methods.
Perform simple experimental studies of programs.
Program with attention to community standards and good practices.
Communicate their programming work eﬀectively.
Meet Quantitative Literacy General Education requirements, such as being able to [following text is from U. Maine Gen. Ed. documents]:
- Translate problems from everyday spoken and written language to appropriate quantitative questions.
- Interpret quantitative information from formulas, graphs, tables, schematics, simulations, and visualizations, and draw inferences from that information.
- Solve problems using arithmetical, algebraic, geometrical, statistical, or computational methods.
- Analyze answers to quantitative problems in order to determine reasonableness. Suggest alternative approaches if necessary.
- Represent quantitative information symbolically, visually, and numerically.
- Present quantitative results in context using everyday spoken and written language as well as using formulas, graphs, tables, schematics, simulations, and visualizations.