Syllabus

Course Information

Required Materials:

Course Description

Data structures are essential building blocks in obtaining efficient algorithms. This course aims to introduce students to advanced data structure concepts, including geometry (multi-dimensional data structures), dynamic optimality, memory hierarchy, hash, integers, dynamic graphs, strings, and succinct.

Learning Objectives

Course Student Learning Outcomes (CSLO)

  1. Understand definitions and tradeoffs of advanced data structures.
  2. Be able to implement, in a programming language of choice, these advanced data structures.

MS in CS Program Objectives (CSPO):

  1. Be well prepared to enter a career.
  2. Be exposed to the latest, cutting-edge technology.

Assessments and Grading:

Method of Evaluation

Assessment % of Final Grade CSLO CSPO
Assignments 60% 1,2 1, 2
Group Presentations 30% 1 1, 2
Class Participation 10% 1 1

Grade Scale:

D grades are not used. Refer to the Graduate Catalog for description of NG (No Grade), W, & other grades.

Assessments:

Lateness Policy:

Assignments that are late are assessed a 10% per day late penalty. Saturday and Sunday are each days.

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Course Topics and Schedules (subject to change)

Week Topic Assessments
1: Aug 26 Introduction -
  Review -
2: Sep 2 Time Travel: Temporal Data Structures -
  Geometric: Multi Dimensional Data Structures -
  Dynamic Optimality -
  Memory Hierarchy -
  Integer -
  Static Tree and Strings -
  Succint -