Announcements:

syllabus available below: follow the links

report template available here

first assignment available here: due by January, 29th.

Info. Class

Description of the class

Syllabus available here
Important information is also available here about: how and when to contact your instructor, labs, etc.

This course is a survey of classic algorithms and data structures, useful for sorting, manipulating graphs, storing data collections and mappings. Students will acquire an understanding of generalization techniques for evaluating the complexity of these algorithms, and they will be able to apply these algorithms to a wide range of computer science problems. Introductory techniques for determining correctness and evaluating complexity will be presented. Students are expected to master basic skills and to develop an intuitive understanding of how the surveyed analysis techniques are commonly used. The main objective is that students develop their critical thinking skills and become able to make an appropriate choice of data structures given any problem, and to justify their choice in an articulate explanation.

As far as assignments and exams , there will be:

reading assignments, and homework assignments (randomly checked);

(announced AND un-announced) quizzes throughout the semester;

programming assignments: most probably 5 -- turning all of them and making at least a C at each of them are required to pass the class;

3 mid-terms;

1 final exam.

Teaching Assistant
The labs will be held by a teaching assistant. Your TA: Geovany Ramirez, geoabi@gmail.com

Peer Leading Sessions
Peer Leading sessions will be held each week during half of the lab times. Two peer-leaders are in charge of those sessions: David Vera, dvera@miners.utep.edu, and Robert Preston, rwpreston@miners.utep.edu. For more information about peer-leaders and peer-led team learning, go to this website.

Textbook

Data Structures and Algorithms}, by Aho, Ullman and Hopcroft, Eds. Addison-Wesley

More details about the class: a tentative schedule

This class will meet every Tuesday and Thursday, from noon to 1:20pm in room 308.

The content of classes is (tentatively) expected to be as follows:

week #1: Presentation of syllabus. Introduction to algorithm analysis.

week #2: Algorithm analysis

week #3: Algorithm analysis (the end) / arrays and linked-lists review

week #4: Stacks

week #5:

week #6: Queues / Discrete Event Simulation

week #7: Discrete Event Simulation / Trees

week #8: Trees: general trees, traversals / Binary trees

week #9: Trees: binary trees, binary search trees, algorithms, classical problems and algorithms

week #10: Balanced trees: AVL, heaps

week #11: Review of sorting algorithms: analysis, purpose, problems -> mostly about heap sort

week #12: Graphs: definition, use

week #13: Graphs: classical problems and algorithms

week #14: Advanced topics

week #15: General reviews

week #16: week of the final exam

Material for the class:

Exercises given in class:

Algorithm analysis:

Homework on ...:

References, and other material:

for arrays and linked-lists: 1, 2, 3,

Quizzes and Exams:

Quiz on complexity:

Quiz on Stacks and queues:

Midterm 1:

Midterm 2:

Midterm 3: Lab Assignments:

More details about labs: attendance policy, late assignment policy, details about written reports (1, 2, 3)

1st lab assignment: here: due by January, 29th, to be done individually.

More material from the past semesters: here.

Martine Ceberio

Last modified: Mon Jan 14 21:20:32 MST 2008