Upon completion of this
course, a student should be able to:
- Understand the meaning of asymptotic time complexity analysis. In
particular:
- Describe the value of big-oh notation.
- Describe the limitations of big-oh notation.
- Provide a definition for big-oh notation.
- Describe the differences between the following time complexity
notations: big-oh, omega, theta.
- Be able to analyze the time complexity of simple functions with loops
and conditionals.
- Be able to analyze the time complexity of simple recursive functions.
- Be able to compare the time complexity of two alternate functions.
- Be able to analyze the time complexity of a program with multiple
simple function calls with known time complexity.
- Be able to use induction to prove/disprove the suggested time
complexity of a given function.
- Interpret and write templated generic algorithms.
- Interpret and write C++ code using the following STL container classes:
vector, list, stack, deque, priority queue, queue, set, and map.
- Understand the underlying organzation of the following data structures:
vector, double/singly-linked-list, deque, stack, queue, priority queue, hash
table, binary search tree, set, and map.
- Describe and explain the time complexity for inserting, finding, and
deleting items to/from the following data structures: vector, list, deque,
stack, queue, priority queue, heap, hash table, binary tree, set, and map.
- Compare and contrast the following data structures: vector,
double/singly-linked-list, deque, stack, queue, priority queue, binary
search tree, set, hash table, and map.
- Describe the differences between the set and multiset data structures.
- Describe the differences between the map and multimap data structures.
- Define the term adaptor class and be able to implement a simple adaptor
class, e.g., stack, queue.
- Demonstrate the use of binary tree traversals (inorder, preorder,
postorder.
- Define a collision as it relates to hash tables and describe ways of
coping with collisions.
- Interpret and develop simple hashing functions.
- Prove algorithm correctness using inductive assertions.