CS 218: DESIGN AND ANALYSIS OF ALGORITHMS
University of California, Riverside
4 Units, Lecture, 3 hours; research, 3 hours. Prerequisite(s): CS 141; graduate standing. Covers efficient algorithms and data structures for problems from a variety of areas such as sorting, searching, selection, linear algebra, graph theory, and combinatorial optimization. Focuses on techniques for algorithm design (greedy, divide-and-conquer, dynamic programming) and rigorous proofs of correctness and time- and space-complexity (amortized analysis, Master Theorem). May be taken Satisfactory (S) or No Credit (NC) with consent of instructor and graduate advisor.
Average GPA: 3.28
Grade distribution records: 758 students across 18 terms.
Grade distribution
| Grade | Students | Percent |
|---|---|---|
| A+ | 127 | 16.8% |
| A | 165 | 21.8% |
| A- | 101 | 13.3% |
| B+ | 103 | 13.6% |
| B | 85 | 11.2% |
| B- | 55 | 7.3% |
| C+ | 13 | 1.7% |
| C | 47 | 6.2% |
| C- | 9 | 1.2% |
| D+ | 1 | 0.1% |
| D | 28 | 3.7% |
| D- | 4 | 0.5% |
| F | 11 | 1.5% |
| NP | 7 | 0.9% |
| S | 2 | 0.3% |
Based on 758 student grade records across 18 terms and 7 professors.
Instructors
- Yihan Sun 202 students, Average GPA 3.56
- Stefano Lonardi 132 students, Average GPA 3.05
- Amey Bhangale 130 students, Average GPA 2.99
- Yan Gu 128 students, Average GPA 3.41
- Marek Chrobak 60 students, Average GPA 2.74
- Mingxun Wang 56 students, Average GPA 3.44
- Silas Richelson 50 students, Average GPA 3.63