Computing and Algorithms: What you Need to Know
Items in blue color have been discussed in previous courses
Items with yellow background have been discussed this semester
A. Computers and Programming
a. Von Neumann architecture
b. Number systems, Binary number system,
c. Basic idea what operating systems do
d. Basic idea how programs are executed
e. If statements, while, do-while and for loops
(150)
f. Array processing, 1D and 2D
(150)
g. Classes and objects, return values, pass by reference, pass by value (150, 155)
h. Static and non-static methods
i. Recursive methods
(150, 155)
(150, 155, 250)
B. Data structures
Be able to describe the defining features of each structure, its basic operations and
their complexity, how it can be implemented
a. Linked lists, doubly linked lists.
Basic operations, complexity
(155)
b. Stacks, with linked nodes and with arrays,
Basic operations, complexity of basic operations
(155)
c. Queues, linked nodes and with arrays
Basic operations, complexity of basic operations
(155)
d. Circular arrays
(155)
e. Trees, Binary trees, Binary search trees, tree traversals
Binary nodes, basic operations
(155)
1
f. Sets, Bags, Maps, Dictionaries
(155)
g. AVL trees
(250)
h. Hash tables, creating and search, complexity
(250)
i. Binary heaps, priority queues implemented with binary heaps,
Basic operations, complexity
(250)
j. Graphs, graph representation, graph algorithms (see C(c) below) (250)
C. Algorithms
Be able to describe how each algorithm works and its complexity. Be able to identify
algorithms given their pseudocode.
a. Search: linear search and search in a sorted array, Binary tree search
(150, 155)
b. Sorting
Be able to state the application of each algorithms, whether it is recursive or not,
and memory requirements
i. Simple sorts: insertion, selection, bubble sort
ii. Advanced sorting:
1. Merge sort
2. Quick sort
3. Heap sort
4. Shell sort
(150, 155)
(155)
(155 )
(250)
(250)
c. Graph algorithms
i. Topological sort and scheduling networks
ii. Shortest path algorithms
iii. Minimal spanning trees
(250)
(250)
(250)
d. Huffman codes
e. Set algorithms – subset generation
(250)
(250)
2
D. Design methods
(250)
Be able to describe each design method and give examples of algorithms
developed with that method
a.
b.
c.
d.
e.
f.
g.
h.
i.
j.
Brute force and exhaustive search
Divide and conquer
Decrease and conquer
Transform and conquer
Genetic algorithms
Greedy algorithms
Branch and bound
Dynamic programming
Iterative improvement
Space and time tradeoffs
E. Algorithm analysis
a.
b.
c.
d.
e.
(250)
Big O notation, Theta and omega, be able to manipulate Big O expressions
Analyzing loops
Analyzing recursive methods with recurrence relations
Solving recurrence relations
NP problems
F. Some other stuff, not studied in cmsc 250
a. Databases
b. Web programming, client-server computing, networking
c. Basic idea about methods in Artificial Intelligence
d. Basic idea about computability, Finite State Automata, Turing machines
3