Information About the First Test

The first test will be given in class on Wednesday, February 23.
The test will cover everything that we have done from the beginning
of the term through class on Friday, February 18. This includes
exceptions and the try..catch..finally statement;
the analysis of algorithms; recursion; linked lists;
the concept of abstract data types; stacks and queues;
binary trees, binary sort trees, and expression trees. The reading
for this material is Sections 8.3, 8.5, 9.1, 9.2, 9.3, and 9.4.
You are also responsible for what we've done in lab, including the
basics of `BufferedImage`.

You can expect a variety of questions on the test. There will be some definitions and essay-type questions. There will be one or two questions that ask you to analyze the run time of some code. Some questions will ask you to write code segments or methods or possibly even complete classes. There might also be some questions that ask you to read some code and figure out what it does.

Here are some terms and ideas that you should be familiar with:

exceptions how exception handling compares to other ways of dealing with errors handling exceptions: the try..catch statement the finally clause in a try statement, and why it might be used throwing exceptions checked exceptions and mandatory exception handling questions of efficiency of a program run-time analysis of algorithms worst-case analysis and average case analysis log_{2}(n) and how it arises in analysis of some algorithms "Big Theta" and "Big Oh" notation ( Θ(f(n)) and O(f(n)) ) comparing Θ(n) to Θ(log(n)), or Θ(n^{2}) to Θ(n*log(n)) disregarding "constant multiples" and "lower order terms" Linear Search and Binary Search Selection Sort and Insertion Sort have run time Θ(n^{2}) Exponential run time, such as Θ(2^{n}) a program with exponential run time is infeasible except for very small inputs recursion recursive methods recursive definition of the factorial function the recursive version of binary search base case of a recursion maze-solving, blob-counting, and similar recursions infinite recursion, and why "marking" locations as already visited is important recursive geometric objects such as the Sierpinski Carpet the QuickSort recursive algorithm the idea of QuickSortStep (but not the detailed code) the general idea of why QuickSort has average case run time Θ(n*log(n)) the worst case run time of QuickSort activation records and how they are used to implement subroutine calls How recursion is implemented using the stack of activation records linked data structures understanding names such as "employee.boss.name" and "node.next.next" simple linked lists the head of a list; why you always need to keep a pointer to the head traversing a linked list; using a "runner" to move down the list basic linked list processing, such as searching, or adding up items in a list the meaning of "while (runner != null)" and "runner = runner.next" adding a node to the head of a list why working at the head of a list is often a special case inserting and deleting nodes in a list using a "tail" pointer in a list; adding a node at the end of a list Abstract Data Types (ADTs) alternative implementations of ADTs relation of ADTs to interfaces and abstract classes the "Queue" ADT queue operations: enqueue, dequeue, isEmpty how to implement a queue as a linked list with tail pointer the "Stack" ADT stack operations: push, pop, isEmpty how to implement a stack as an array how to implement a stack as a linked list stacks are "LIFO"; queues are "FIFO" using a stack or queue as an alternative to recursion postfix expressions algorithm for using a stack to evaluate a postfix expression binary trees recursive processing of a binary tree recursive traversal of a tree inorder, preorder, and postorder traversals using a queue to process nodes in "breadth-first" order (aka "level order) binary sort tree inserting items into a binary sort tree searching for an item in a binary sort tree balanced binary tree inserting/searching in a balanced binary sort tree has run time Θ(log(n)) expression trees to represent binary expressions finding the value represented by a an expression tree using different classes to represent different kinds of node in an expression tree Integrated Development Environment (IDE) Eclipse javadoc, JavaDoc style comments, and why they are used BufferedImage: image.getRGB, image.setRGB, g.drawImage(image,0,0,null) using anonymous inner classes as event listeners the idea of "resource files" in a program version control system CVS sharing, importing, committing, and updating projects in CVS

Here are a few practice questions about pointers and linked data structures. These questions use the following classes:

class ListNode { class TreeNode { String item; int item; ListNode next; TreeNode left, right; } }

**1.**
Draw the data structure that is created by the following code segment:

ListNode n1, n2; n1 = new ListNode(); n1.item = "Joe"; n1.next = new ListNode(); n1.item = "Jane"; n2 = new ListNode(); n2.item = "Jill"; n2.next = n1; n2.next.next.next=n1;

**2.**
Write a code segment that will find and print the **longest** string in
the list. (If there are several strings with the same maximal length,
output the one that comes first in the list.)

**3.**
Write a method with one parameter of type `ListNode` and a return type
of *boolean*. The method should test whether the items in the list are
already sorted into increasing order.

**4.**
Write a recursive method with one parameter of type `TreeNode`
that finds the sum of all the numbers in the tree.

**5.**
The *height* of a binary tree is defined to be the number of nodes on the
longest path from the root to any leaf. The height of an empty tree
is zero. Figure out how to compute the height of a non-empty tree from the
heights of its left and right subtree, and write a recursive method, with
a parameter of type `TreeNode`, to find the height of a binary tree.

**6.**
Draw a binary tree containing at least 12 items, and list the
items in the order that they would be visited by a pre-order, by
an in-order, and by a post-order traversal.