Algorithms and Data Structures

a.      Algorithm basic  notions.

b.      Complexity Measurement: temporal and spatial costs.

c.      Case Analysis: best, worst and average cases.

d.      Asymptotic Notation.

e.      Analysis of control structures.

a.      Recursion vs. Iteration.

b.      When to  use the recursion.

c.      Simple examples of recursion.

e.      Examples: factorial, Fibonacci

a.      Logical description of list ADT.

b.      List Types: sorted, generic, stacks, queues, deques, and cyclic lists.

c.      Different representations of lists ADT:

         i.     Sequential/linked Representation

         ii.     Static/dynamic representation

d.      Implementation through the use of vectors and pointers.

e.      Operations on lists (creation, search, insertion, etc.).

f.       Examples of lists applications.

a.      Logical description of the tree structure. Graphic representation.

b.      Types of trees: general trees, binary trees.

c.      Binary tree ADT.

d.      Operations in binary trees.

e.      Tree Traversal: pre-order, in-order, post-order.

f.       Variants of binary trees.

g.      Binary Search Trees.

h.      AVL Trees.