Course: CSC 331 Algorithm Analysis

1
Course CSC 331 Algorithm Analysis

• Dave Powell
• Modified by Kelly Van Busum (Dec 2002)

2
Course Description

• Students analyze structures and appropriate
  algorithms for sorting, merging and searching in
  the contexts of mass storage devices, internal
  main memory and artificial intelligence
  applications. Topics include graph algorithms,
  dynamic storage allocation and garbage
  collection.

3
Course Goals

• Introduce students to algorithm solution
  techniques for a wide range of generic problem
  patterns.
• Provide analytical foundation to select among
  competing algorithms for particular problem
  solution.
• Give mathematical grounding/rigor for
  understanding library api functionality.

4
Topics

• Asymptotic notations and algorithm efficiency
  classes.
• Mathematical techniques for analyzing
  nonrecursive and recursive algorithms
• Brute-force strategy and brute force algorithms,
  including exhaustive search
• Divide and conquer and divide and conquer
  algorithms
• Searching algorithms (Trees, Hash Tables)
• Greedy algorithms (Graphs)
• Dynamic Programming
• Alpha Beta Pruning
• Backtracking and branch and bound
• P and NP problems, approximation algorithms

5
Miscellaneous

• Software Java
• Hardware Intel Pentium with Linux or Windows
• Project Required - Yes. Many small projects
• Presentation Required Yes.
• Expected knowledge/topics from previous course
  Data structures, Beginning knowledge of analysis
  from CSC 230

6
ACM Guidelines

• Textbook
• Proposed Data Structures and Algorithm Analysis
  in Java, Mark Weiss. (KV Needs to be updated,
  dont have reference available)
•  ACM Topics
• PF2 - Algorithms and problem solving
• PF4 - Recursion
• AL1 - Basic algorithmic analysis (4)
• AL2 - Algorithmic strategies (6)
• AL3 - Fundamental computing algorithms (12)
• IS2 - Search and constraint satisfaction (5)

7
ACM Guidelines (Contd.)

• DS5 Graph theory/trees
• IS1 Fundamental issues in intelligent systems
• SE1 SE12 Software Engineering