Introduction to Computer Science and Programming

Posted on May 13, 2024 in Computers

This document provides an overview of object-oriented program design, computer memory, machine language, and the software development life cycle.

The Von Neumann computer model consists of a CPU and memory.
Computer memory is made up of cells with unique addresses and stores information in binary format.
Machine language is the binary code that computers can understand.
High-level programming languages like Python and Java are used to write programs that are easier for humans to understand.
Compilers translate code in a programming language into machine or executable code.
Java programs are executed using the Java virtual machine.
Good program design involves dividing a complex problem into smaller sub-problems and designing modules or objects to solve each sub-problem.
Modularity, encapsulation, and information hiding are important principles in program design.
Objects in object-oriented programming have properties (instance variables) and behaviors (methods).
Variables of non-primitive types store addresses and can be compared using the equals method.

Address Book Program Design

This document discusses the design of an address book program using arrays and the Person class. It covers the implementation of adding and removing contacts, the use of arrays to store contact information, and the concept of array indices in Java.

The program implements an address book to store contact information of people.
It allows adding and removing contacts from the address book.
The Person class is used to store contact information.
The AddressBook class uses an array to store the list of contacts.
Arrays in Java store values in adjacent memory locations with unique indices.
Arrays are declared using square brackets and created using the new operator.
The AddressBook class has instance variables for the contact list and number of contacts.
The add method adds a new contact to the contact list, expanding the array if necessary.
The remove method removes a target contact from the contact list using linear search.
Parameters are used in methods to make them more general and allow different values to be passed.

Inheritance in Java Programming

This document discusses the concept of inheritance in Java programming, using the example of a Rectangle and Square class. It explains how to create subclasses, override methods, and use the instanceof operator. It also covers the importance of the superclass Object and the inheritance hierarchy.

Inheritance is a mechanism for deriving a new class from an existing one.
It allows for reusing existing classes, which is faster and cheaper than writing new classes from scratch.
The example of a Rectangle and Square class demonstrates how inheritance works.
A subclass inherits the attributes and methods of the superclass.
The instanceof operator can be used to determine the class of an object.
The super keyword is used in a derived class to refer to its parent class.
Casting can be used to convert primitive types to other primitive types.
Visibility in inheritance allows for accessing public and protected variables and methods.
A derived class is a more specific version of the original class.
Overriding methods allows a derived class to define a method with the same signature as a method in the parent class.

Polymorphism and Dynamic Binding

The document discusses polymorphism, dynamic binding, casting reference variables, and the instanceof operator in Java.

Polymorphism allows the behavior of a method to change depending on the type of the object being referenced.
Dynamic binding refers to the behavior when a superclass variable references an object of a subclass type.
Casting reference variables can be used to convert one class type to another within an inheritance hierarchy.
The instanceof operator tests whether the referenced object is an instance of a particular class.
Java’s class hierarchy includes the Object class at the top, with methods such as equals() and toString().
The Object class methods can be overridden in subclasses to provide more meaningful functionality.
Variables of type Object can reference objects of any type, allowing for flexibility in storing different object types.
The document emphasizes the importance of understanding the type of object being referenced for method invocation.
The document highlights the potential errors and runtime issues that can occur when casting reference variables.
The document suggests using the instanceof operator as a safer alternative to casting reference variables.

Program Errors and Debugging

The document discusses program errors, including compiler errors, runtime errors, and logic errors. It also covers debugging strategies and the importance of testing and defensive programming.

Program errors can be compiler errors, runtime errors, or logic errors.
Compiler errors are detected by the compiler and prevent the program from running.
Runtime errors occur when a program crashes due to exceptions or unexpected input.
Logic errors result in incorrect program results and can be caused by incorrect algorithms or mistakes in code.
Debugging strategies include tracing by hand, adding a main method for testing, using print statements, and using a debugger.
Testing is important to identify problems before software is used, but it can’t guarantee the absence of bugs.
Defensive programming involves checking for exceptional conditions and generating appropriate error messages.
Eclipse provides a debugger that allows for breakpoints, single-step execution, and variable inspection.
It is important to write robust programs that handle exceptional conditions and provide meaningful error messages.

Exceptions in Java Programming

This document discusses exceptions in Java programming, including their definition, examples, and handling methods.

Exceptions are abnormal or erroneous situations detected at runtime in Java programming.
Examples of exceptions include array index out of bounds, division by zero, and null pointer exception.
Exceptions can be thrown by the Java virtual machine or by a program itself.
Exceptions are objects that are created with the new operator and thrown with the throw statement.
Exceptions can be caught and handled using try-catch statements.
A try-catch statement executes the code in the try block and if an exception is thrown, control is passed to the corresponding catch clause.
If an exception is not caught and handled, it propagates to the method that invoked the method where the exception occurred.
Java has predefined exception classes such as ArithmeticException, IndexOutOfBoundsException, and NullPointerException.
Checked exceptions are checked by the compiler, while unchecked exceptions are not.
The finally block in a try-catch-finally statement always executes, regardless of whether an exception was thrown or not.

Scope of Variables in Java

The document discusses the scope of variables in Java, including instance variables, local variables, and block variables. It also explains that the scope of a variable is the block where it was declared.

The scope of a variable in Java is the block where it was declared.
There are three classes of variables in Java: instance variables, local variables, and block variables.
Variables can only be accessed after they have been declared.

Linked Data Structures

This document discusses linked data structures, specifically singly and doubly linked lists, and their advantages over array-based structures. It explains the concept of nodes and the use of generic types in Java. The document also covers the operations of inserting and deleting nodes in a linked list.

Linked data structures consist of items that are linked to other items, with each item pointing to another item.
Singly linked lists have each item pointing to the next item, while doubly linked lists have each item pointing to the next and previous items.
Advantages of linked lists include dynamic growth and shrinkage, and the ability to insert and delete items without shifting data.
Nodes in a linked list store data and a reference to another node, and can be designed to store data of any type using generic types.
Inserting a node in a linked list involves updating the pointers of the previous and next nodes.
Deleting a node in a linked list involves updating the pointers of the previous and next nodes, or updating the front pointer.
Doubly linked lists have nodes with pointers to both the next and previous nodes.
Algorithms are provided for inserting and deleting nodes in both singly and doubly linked lists.

Collections, Abstract Data Types, and Interfaces

This document discusses the concepts of collections, abstract data types (ADTs), and interfaces in Java programming. It also explains the use of generics and the implementation of interfaces and generic types. The document emphasizes the importance of choosing the right collection for a problem and the benefits of abstraction. It introduces the Bag ADT as an example and provides a Java interface for it. The document also covers the implementation of interfaces using the “implements” keyword and the use of generic types to create classes that work with any data type. It mentions the limitations of using primitive types as class parameters and the need to design methods to work with generic types. The document concludes by mentioning the use of data structures to implement collections.

A collection is a group of items treated as a unit, and the choice of collection can improve efficiency and simplicity.
An abstract data type (ADT) is a collection of data items with specified operations.
ADTs specify what operations do, not how they are performed.
Abstraction separates the purpose of an entity from its implementation.
Java interfaces define operations on ADTs and must be implemented by classes.
Generic types allow interfaces and classes to work with any data type.
Generic types cannot use primitive types, but wrapper classes can be used.
Generic methods must use the class parameter wherever the data type is used.
Data structures like arrays and linked lists are used to implement collections.

The Stack ADT

The document discusses the concept of abstraction and its importance in computer systems. It introduces the Stack ADT and its operations. It explains the array and linked list implementations of a stack. It also mentions the uses of stacks in computing, such as undo operations and evaluating postfix expressions.

Abstraction separates the purpose of something from its implementation.
The Stack ADT is a collection of data items with specific operations.
Stack operations include push, pop, peek, size, isEmpty, and toString.
The array implementation of a stack uses an array to store data items.
The linked list implementation of a stack uses nodes to store data items.
Stacks are used in computing for execution stacks and backtracking.
Stacks are used in word processors for checking parentheses and implementing undo operations.
Postfix expressions are evaluated using a stack.
The algorithm for evaluating a postfix expression involves scanning, pushing operands, and popping operators.
The result of evaluating a postfix expression is the final item on the stack.

Queues and Their Implementations

This document discusses the concept of a queue, its operations, and various implementations using linked lists and arrays.

A queue stores a collection of data items ordered linearly.
The front and rear of the queue determine where items can be added or removed.
Real-life examples of queues include waiting in line and processing keyboard input.
Queue operations include enqueue, dequeue, first, isEmpty, size, and toString.
Linked list implementation uses nodes with front and rear pointers.
Array implementation uses an array to store data items with front and rear indices.
Circular array implementation avoids shifting data items during dequeue.
The circular array can expand its capacity when full.
Printer queues and keyboard input buffers are real-world examples of queues.

The List ADT and Its Implementations

This document discusses the List abstract data type and different types of lists, including unordered, ordered, and indexed lists. It also covers the Comparable interface for comparing objects of a generic type and provides an overview of the List ADT and its operations. The document explores various implementations of the List ADT, such as array, circular array, and linked list. It also introduces the concept of doubly linked lists and explains the add and remove operations for an ordered list using linked lists.

A list is a collection of data items with a linear ordering, allowing for flexible addition and removal of items.
There are three types of lists: unordered, ordered, and indexed.
Unordered lists do not have a particular order, while ordered lists maintain a specific order based on the value of the data items.
Indexed lists reference data items by their position in the list.
The List ADT includes common operations like removeFirst, removeLast, contains, isEmpty, etc.
The Ordered List ADT adds the add operation to maintain the ordering of the list.
The Comparable interface allows for the comparison of objects of a generic type.
Array implementation of a list requires shifting of data when adding or removing items.
Linked list implementation uses nodes with references to the next and previous nodes.
Doubly linked lists have two references in each node, allowing for easier traversal.
The remove operation in a doubly linked list considers different cases, such as removing the front, rear, or another node.

Iterators and Their Implementations

This document discusses the concept of iterators and their purpose in accessing data items in a collection. It explains the methods of the Iterable interface and compares different implementations of iterators.

An iterator allows us to access data items in a collection one by one.
The Iterable interface has two primary methods: hasNext() and next().
The Iterator interface in the Java API specifies the methods of the iterator ADT.
Array and linked list implementations of iterators are presented.
The array implementation stores data items in an array and uses count and current variables.
The linked implementation stores data items in a linked list and uses count and current variables.
Java collections like ArrayList, HashSet, LinkedList, etc. provide iterator methods.
Iterators provide a uniform way to traverse collections without knowing their underlying data structure.
An example of using an iterator with an ArrayList is provided.
Iterators are advantageous as they abstract the implementation details of collections.

Memory Management in Java

This document explains memory management in Java, including memory allocation and deallocation, the different parts of memory, and the execution stack.

Memory in a Java program is allocated to different areas: execution stack, static heap, and dynamic heap.
The static heap stores code for class methods and static objects.
The dynamic heap is used to store dynamically created objects during program execution.
The execution stack is used to store information needed while a method is being executed.
Activation records are created for each method and contain information such as return address, parameters, and local variables.
The execution stack grows in one direction, while memory allocation for a program grows in the opposite direction.
When an object is created in a method, memory is allocated to the local variable in the execution stack and the object is created in the heap.
The execution stack is used to store activation records for each method called during program execution.
The program execution follows a stack-like structure, with activation records being pushed onto the execution stack and popped off when a method returns.
Java has automatic garbage collection to deallocate memory for objects that are no longer referenced by variables.

Recursion and Its Applications

This document discusses the concept of recursion and its use in solving problems. It explains recursive definitions and provides examples. It compares recursion with iteration and highlights the power of recursion as a problem-solving technique. It presents an example of recursive programming to compute the sum of numbers. It also explains how recursion works with the help of a program execution stack. The document concludes by discussing the choice between recursion and iteration for solving problems.

Recursion is a self-referential definition that consists of a base case and a recursive part.
Mathematical formulas can often be expressed recursively, such as the factorial definition.
Recursion defines something in terms of a smaller or simpler version of itself.
Iteration is repetition, while recursion defines something in terms of a smaller version of itself.
Recursion is a powerful problem-solving technique that can solve complex problems.
The sum of numbers between 1 and n can be computed iteratively or recursively.
Recursive algorithm for sum: base case is when n=1, recursive case is n + sum(n-1).
Recursion uses an execution stack to keep track of function calls and return values.
Recursion can be converted to iteration, but it may be more complex and require additional data structures.
The choice between recursion and iteration depends on the problem and its complexity.

Recursion and the Fibonacci Sequence

The document discusses the multiplying rabbits problem, the Fibonacci sequence, recursion, and the Towers of Hanoi problem.

The multiplying rabbits problem involves calculating the number of rabbits after a certain number of months.
The Fibonacci sequence is a sequence of numbers where each number is the sum of the two preceding ones.
A recursive algorithm is used to compute Fibonacci numbers, but it can be inefficient due to duplicated calls.
The Towers of Hanoi problem involves moving a set of disks from one peg to another following specific rules.
The algorithm for solving the Towers of Hanoi problem is recursive and involves moving smaller sets of disks.
Inverting an array involves swapping values in the array to reverse their order.
The algorithm for inverting an array is recursive and swaps values from the first and last positions.
Recursion should be used when a simple iterative algorithm is not possible.
Recursion should be avoided when the same recursive call is repeatedly made, as it can be slow.
The iterative algorithm for computing Fibonacci numbers is more efficient than the recursive algorithm.

Drawing Recursive Figures

The document discusses drawing recursive figures, specifically fractals, and their applications in various fields such as medicine, image compression, electronics, computer simulation, and art.

Fractals can be drawn using recursion, such as the Sierpinski Triangle.
The Sierpinski Triangle is created by drawing triangles of decreasing size at each vertex.
Fractals have applications in medicine, image compression, electronics, computer simulation, and art.
Fractals allow for the compact representation of complex shapes and mimic natural landscapes.

Trees and Tree Traversals

This document discusses the definition and terminology of trees, tree implementations, and tree traversal algorithms.

A tree is a non-linear data structure that stores information in a hierarchy.
Examples of trees in real life include family trees, table of contents, and class inheritance hierarchy.
Tree terminology includes parent, child, sibling, ancestor, and descendant nodes.
Trees can be represented using linked structures or arrays.
Binary trees are important and have applications in various fields.
Tree traversals include preorder, inorder, postorder, and level-order.
Preorder traversal visits the root node first, then the left and right subtrees.
Inorder traversal visits the left subtree, then the root node, and then the right subtree.
Postorder traversal visits the left and right subtrees first, and then the root node.
Level-order traversal visits the nodes in increasing order of level, from left to right.

Binary Tree Operations

, the binary tree ADT, & the LinkedBinaryTree class.

The document explains various operations that can be performed on a binary tree, such as getting the root, checking if the tree is empty, finding the size, & searching 4 a specific element.
It introduces the Binary Tree ADT interface, which includes methods 4 getting the root, checking if the tree is empty, & returning a string representation of the tree’s contents.
The LinkedBinaryTree class is presented, which implements the BinaryTreeADT interface & includes methods 4 creating an empty binary tree & a binary tree with a specified element in the root.
The size operation is discussed, which calculates the number of nodes in a tree by recursively adding the sizes of the lft & right subtrees.
The find operation is explained, which searches 4 a target value in a binary tree by performing a traversal of the tree.
The postorder iterator operation is described, which creates an iterator that returns the data items of a binary tree in the same order as a postorder traversal.
The use of binary trees in expression trees is menti1d, where binary trees R used 2 represent arithmetic expressions.
The evaluation of expression trees is discussed, which involves traversing the tree & applying operators 2 operands 2 calculate the value of the expression.

This document discusses the concepts of Binary Search Trees (BSTs) & Heaps, including their properties, implementation, & algorithms 4 sorting & searching.

Binary Search Trees (BSTs) R binary trees where the data in each internal node is greater than the data in any node in its lft subtree & smaller than or equal 2 the data in any node in its right subtree.
The properties of BSTs allow 4 efficient searching of target values by comparing them with the root & continuing the search on the lft or right subtree.
Inorder traversal of a BST accesses the data in ascending order, while a reversed inorder traversal accesses the data in descending order.
A min heap is a complete binary tree where the value in each node, except the root, is larger than or equal 2 the value stored in its parent.
A max heap is similar 2 a min heap, but the value in each node, except the root, is smaller than or equal 2 the value stored in its parent.
Heaps can be efficiently implemented using arrays, with the lft child of a node stored @ 2i+1 & the right child @ 2i+2.
The removeMin operation in a min heap removes the minimum value (stored in the root) & maintains the heap property.
The heapsort algorithm converts an array into a min heap & then repeatedly removes the minimum value 2 create a sorted array.
The algorithm 4 storing the data in a BST in a sorted array uses a reversed inorder traversal.
The algorithm 4 finding a target value in a BST uses a recursive search starting from the root.

This document discusses various sorting algorithms, including insertion sort, selection sort, mergesort, & quicksort. It also explains the concept of in-place sorting & divide & conquer.

The document covers different sorting algorithms such as insertion sort, selection sort, mergesort, & quicksort.
It explains the concept of in-place sorting, which is memory efficient.
The document provides a step-by-step explanation of insertion sort using stacks.
It demonstrates the process of in-place insertion sort & its efficiency.
The document also discusses selection sort, the most natural sorting algorithm.
It presents the divide-&-conquer technique 4 designing algorithms.
Quicksort is explained as a sorting algorithm that uses divide-&-conquer.
The document provides a detailed explanation of how quicksort works.
It includes an algorithm 4 quicksort implementation.
The document concludes with a summary of the key points covered in the txt.

The document explains the concept of Mergesort, a sorting algorithm that uses Divide-&-Conquer. It covers the steps involved in Mergesort & how it sorts a sequence of values. The document also includes the algorithm 4 Mergesort & the process of merging 2 sorted arrays.

Mergesort is a sorting algorithm that divides the input sequence in half & recursively sorts each half.
The sorted sub-sequences R then combined 2 get the entire sequence sorted.
The document provides visual representations of the sorting process using tables.
The algorithm 4 Mergesort is presented, including the input & output parameters.
The merge function is explained, which merges 2 sorted arrays 2 form a single sorted array.
The document assumes that the input is stored in an array.
The process of splitting the array in half & sorting each half is described.
The document also includes an example of how 2 sort a specific half of an array.
The overall goal of Mergesort is 2 sort an array in increasing order.