Introduction and a Review of Basic Concepts Syllabus

Introduction and a Review of Basic Concepts • Syllabus and goals of the course • Object oriented programming contrasting to C programming – Objects, classes, methods – Instantiation, references – Polymorphism, inheritance – Constructor, destructor, garbage collection – Encapsulation – Public, private, protected • Data structures already introduced: Stacks, queues, linked lists • Recursion and induction Understanding data structures and algorithms is a major difference separating computer scientists from one who reads a manual and begins to program.

C versus Java • The dot in Java is equivalent to the -> C; there is no Java equivalent to the C dot operator. Generally, use -> in most cases and declare variables using the ‘*’ (indicating pointer) • There is no Boolean in C. Many programmers declare TRUE and FALSE using #define • C has no garbage collection. To avoid memory leaks, make sure to free whatever you malloc. • Use NULL in C, instead of the null in Java • Use scanf for input, but make sure to clear the input buffer after an error (scanf("%s*")) • C has no methods (it has functions), so dot notation makes no sense. Replace: object. method by function(data • There is no length property in arrays and strings. Array sizes must be stored in a separate variable. • Be careful with pointers and memory management. C doesn’t catch all errors at compile time.

Strings in C • There is no String type, use an array of characters (char *data). • C has no “+” operator for string concatenation. Use strcat, but make sure you have an allocated area in memory to hold the larger string. • To truncate a string, store '' in the appropriate index. • To format output, use printf. • For both puts and printf, make sure to follow the output with fflush(stdout); . Otherwise, output only occurs when the accumulated print buffer gets large enough. • There are many string functions in C, all starting with str. There is also memory manipulation functions, all starting with mem. • Make sure your strings end with a null. Java has the length in the front of a string; C has a null at the end.

Analysis of Algorithms • Definition of Algorithm. Why study data types and algorithm? – Step-by-step solution to a problem – Often the problem can be specified in terms of the size of the data set (n). • Algorithm performance (The technical term is complexity) – A good algorithm implemented by a bad programmer will beat a bad algorithm implemented by a good programmer – A time function, f, of the dataset size is often used to measure effectiveness as the data set size grows. For example, f(n) <= c*n, where c is a constant > 0. Other examples of the growth rate are c*n 2, c*lg n, c, lg 2 n, etc. – Big Oh notation. • How to determine if an algorithm is a good one? – – How fast does it work on a given data set? What is the Relationship between time and data set size? How does it perform on different data set sizes? Growth is more important than a given run’s performance

Big Oh Notation Measurement of algorithm efficiency in terms of memory or time as the problem size increases • Formal Definition: f(n) = O(g(n)) means there are positive constants c and z, such that 0 ≤ f(n) ≤ cg(n) for all n ≥ z. The values of c and z must be fixed for the function f and must not depend on n. • Explanation of terms: 1. 2. 3. 4. g(n) is a well known function to which we want to compare our algorithm. f(n) is how our algorithm performs on different size data sets z is an integer. For all data set sizes smaller than z, we don’t consider the algorithm’s efficiency c is a positive constant. By multiplying g by this constant, all functions with equal or smaller slopes will satisfy the Big Oh definition requirements. Review of logarithms. Conversion of logarithms Logn x = logq x / logq n

Time or memory Pictorial View of Big Oh z Data set size

Allocate Unique Random Numbers • Declare the free list int free. List[MAX]; • Initialize the free list for (i=0; i<MAX; i++) free. List[i] = i; free. Count = MAX; • Allocate an entry from the free list – Find a random index into the free list: index = (int)(rand() * free. Count); – Get the value from the free list (key = free. List[index]; ) – Replace the index with the last value in the free. List[index] = free. List[--free. Count]; • Release an entry back to the free list – Put the value to the end of the free list free. List[free. Count++] = key;

Abstract Data Type A general-purpose data structure encapsulated from the user through a well-defined set of operation • Design – Design the operations that are to be used – Design the data structure to be used • Examples (What operations? What data-structure? ) – – Java’s primitive floating point number Stacks, queues, and linked lists. To be covered: Trees, priority queues, hash tables, graphs. Arrays (Ordered and Unordered) • Array operations and complexities (insert, delete, find, expand, sort, access, traverse) • Advantages and disadvantages