CSC 3102: Advanced Data Structures and Algorithm Analysis
Rigorous study of abstract data types and algorithmic performance analysis. Encompasses asymptotic notations (Big-O, Omega, Theta), balanced search trees (AVL, red-black), heaps, priority queues, hashing tables, disjoint set forests, sorting algorithms, and…
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Common aliases: CSC 3102
Study Resources for Advanced Data Structures and Algorithm Analysis
Final Exam 2016
Midterm (Exam 1) 2014
Midterm (Exam 2) 2014
Midterm (Exam 1) 2017
Midterm (Exam 2) 2017
Worksheet 1
Worksheet 2
Quiz 1
Study Guide 1
Assessment Inventory for CSC 3102 (9 Documents)
| Document | Format | Year | Access |
|---|---|---|---|
| Midterm (Exam 1) 2017 | Midterm | 2017 | Illustrative Archive |
| Midterm (Exam 2) 2017 | Midterm | 2017 | Illustrative Archive |
| Final Exam 2016 | Final | 2016 | Illustrative Archive |
| Midterm (Exam 1) 2014 | Midterm | 2014 | Illustrative Archive |
| Midterm (Exam 2) 2014 | Midterm | 2014 | Illustrative Archive |
| Worksheet 1 | Worksheet | — | Illustrative Archive |
| Worksheet 2 | Worksheet | — | Illustrative Archive |
| Quiz 1 | Quiz | — | Illustrative Archive |
| Study Guide 1 | Study Guide | — | Illustrative Archive |
Complete inventory of all 9 assessments (sorted by most recent). Select any document to inspect or use the search bar above to filter.
Course Overview & Exam Syllabus
Course Description
Rigorous study of abstract data types and algorithmic performance analysis. Encompasses asymptotic notations (Big-O, Omega, Theta), balanced search trees (AVL, red-black), heaps, priority queues, hashing tables, disjoint set forests, sorting algorithms, and graph algorithms (traversals, shortest paths, minimum spanning trees). Explores algorithmic design paradigms including divide-and-conquer, greedy heuristics, and dynamic programming.
This archive catalogs 9 free educational resources and past exams for CSC 3102 (Advanced Data Structures and Algorithm Analysis) at Louisiana State University (LSU), containing 4 midterm papers, 1 final examination, 1 quiz, 2 worksheets, and 1 study guide. Dated documents represent 3 distinct academic years between 2014 and 2017.
Core Exam Topics & Learning Objectives
- Asymptotic time and space complexity: Big-O, Big-Omega, Big-Theta, and recurrence relations via Master Theorem in CSC 3102 at LSU
- Balanced search tree architectures: AVL trees, Red-Black trees, B-trees, and binary heap operations for Advanced Data Structures and Algorithm Analysis
- Graph algorithm mastery: BFS/DFS traversals, Dijkstra's shortest paths, Bellman-Ford, Prim's, and Kruskal's MST algorithms in CSC 3102
- Algorithm design strategies: divide-and-conquer, greedy selection heuristics, dynamic programming memoization, and NP-completeness at Louisiana State University (LSU)
Frequently Asked Questions
Which assessment formats are cataloged in this CSC 3102 archive?
This collection for CSC 3102 at Louisiana State University (LSU) catalogs 9 total resources across the following formats: Midterms, Finals, Quizzes, Worksheets, Study Guides. Each document is listed in the assessment inventory table with its individual format tag and academic year where recorded.
What academic years are covered in this CSC 3102 collection?
Dated materials in this archive span from 2014 to 2017, representing 3 distinct academic years. Coverage varies by the records currently cataloged for this course.
How can students access these free CSC 3102 past exams?
All cataloged CSC 3102 past exams and study materials are free to request. The catalog, metadata, assessment inventory, and illustrative thumbnails are public; source documents are not shown on this page. Use the connect options to request a study resource, and confirm current course topics and grading policies with the Louisiana State University (LSU) course syllabus.