CMSC420 - Data Structures

This year, this course has three different instructors, all of whom teach this course differently. At present, we have information for only Michelle Hugue and Larry Davis. We are currently working on getting information from Venkatramanan Subrahmanian. If you have any questions about their section of the course and how they will be presenting the material, please ask them directly.

Michelle Hugue | 0101 & 0201

Section	Day & Time	Location
0101	TuTh 2:00pm - 3:15pm	CSI 3117
0201	TuTh 3:30pm - 4:45pm	CSI 1122

Course Description
Description, properties, and storage allocation of data structures including lists and trees. Algorithms for manipulating structures. Applications from areas such as data processing, information retrieval, symbol manipulation, and operating systems.

Course Prerequisite(s)
Prerequisite: Minimum grade of C- in CMSC351 and CMSC330; and permission of CMNS-Computer Science department. Or must be in the (Computer Science (Doctoral), Computer Science (Master's)) program.

Class Webpage
CMSC420 Fall 2016 - Meesh

Hours Per Week
The workload for this course is at least the 10 hours associated with a 3 credit class. Programming and debugging skills, or a lack thereof, make it hard to give a decent estimate here.

Languages Used
JAVA

Recommended Prior Experience

Projects, Exams, or other Assessments

Misc Info
We often refer to this course as "data structures in context." The class presents a practical approach to data structures for computer intensive products that can be proven to satisfy correctness and performance requirements. One can obtain almost any data structure from a book or online. However, it takes experience to identify data structures known to provide the desired behavior; to extend them to satisfy the specific application; and to evaluate the deliverables to show that they satisfy the composite standard and custom requirements. The lectures, the project (three linked parts) and the exams are designed to provide students with such experience. This includes having projects which require sustained effort rather than last minute code-a-thons, exams written to elicit knowledge, not empty verbiage, and course policies which reward hard work and learning from mistakes. To put it bluntly, I'll do my best to help you to make mistakes and then support your efforts to learn from them. This is a thinking class, not an echo information class.

Larry Davis | 0102

Day & Time	Location
MW 3:30PM - 4:45PM	CSI 2117

Course Description
Sorting and searching (trees, tries, hashing), representations for higher dimensional data (kd trees, quadtrees and others), big data applications.

Hours per week
2 - 4 Hours per week

Languages Used
Fairly open. Java mostly

Recommended Prior Experience
Just the standard sequence through the 300 level.

Projects, Exams, or other Assessments
Usually 2-3 exams, 3 projects

Misc Info
Emphasis is on algorithms and data structures, not proofs. Projects designed to exercise methods covered in class.

Venkatramanan Subrahmanian | 0301

Day & Time	Location
TuTh 11:00AM - 12:15PM	CSI 2117

Web Accessibility