![A Simple Algorithm
INPUT: a sequence of n numbers
T is an array of n elements
T[1], T[2], …, T[n]
OUTPUT: the smallest number among them
Performance of this algorithm is a function of
n
13
min = T[1]
for i = 2 to n do
{
if T[i] < min
min = T[i]
}
Output min](https://image.slidesharecdn.com/aalecture01-250412084649-8f279f96/85/AA-Lecture-01-of-my-lecture-os-ghhhggh-ppt-13-320.jpg)
![Pseudo-code conventions
Variables ( such as i, j, and key) are local to the given
procedure. We shall not us global variables without explicit
indication.
Array elements are accessed by specifying the array name
followed by the index in square brackets. For example, A[i]
indicates the ith element of the array A. The notation “…" is
used to indicate a range of values within an array. Thus,
A[1…j] indicates the sub-array of A consisting of the j
elements A[1], A[2], . . . , A[j].
A particular attributes is accessed using the attributes
name followed by the name of its object in square
brackets.
For example, we treat an array as an object with the
attribute length indicating how many elements it
contains( length[A]).
21](https://image.slidesharecdn.com/aalecture01-250412084649-8f279f96/85/AA-Lecture-01-of-my-lecture-os-ghhhggh-ppt-21-320.jpg)
AA Lecture 01 of my lecture os ghhhggh.ppt
- 1. Introduction to Algorithms The Role of Algorithms in Computing Course Instructor: Engr. Samina Bilquees
- 2. Computational problems A computational problem specifies an input-output relationship What does the input look like? What should the output be for each input? Example: Input: an integer number n Output: Is the number prime? Example: Input: A list of names of people Output: The same list sorted alphabetically 2
- 3. Algorithms A tool for solving a well-specified computational problem Algorithms must be: Correct: For each input produce an appropriate output Efficient: run as quickly as possible, and use as little memory as possible – more about this later 3 Algorithm Input Output
- 4. Algorithms Cont. A well-defined computational procedure that takes some value, or set of values, as input and produces some value, or set of values, as output. Written in a pseudo code which can be implemented in the language of programmer’s choice. 4
- 5. Correct and incorrect algorithms Algorithm is correct if, for every input instance, it ends with the correct output. We say that a correct algorithm solves the given computational problem. An incorrect algorithm might not end at all on some input instances, or it might end with an answer other than the desired one. We shall be concerned only with correct algorithms. 5
- 6. Problems and Algorithms We need to solve a computational problem “Convert a weight in pounds to Kg” An algorithm specifies how to solve it, e.g.: 1. Read weight-in-pounds 2. Calculate weight-in-Kg = weight-in-pounds * 0.455 3. Print weight-in-Kg A computer program is a computer-executable description of an algorithm 6
- 7. The Problem-solving Process 7 Problem specification Algorithm Program Executable (solution) Analysis Design Implementation Compilation
- 8. From Algorithms to Programs 8 Problem C++ Program C++ Program Algorithm Algorithm: A sequence of instructions describing how to do a task (or process)
- 9. Practical Examples Internet and Networks The need to access large amount of information with the shortest time. Problems of finding the best routs for the data to travel. Algorithms for searching this large amount of data to quickly find the pages on which particular information resides. Electronic Commerce The ability of keeping the information (credit card numbers, passwords, bank statements) private, safe, and secure. Algorithms involves encryption/decryption techniques. 9
- 10. Hard problems We can identify the Efficiency of an algorithm from its speed (how long does the algorithm take to produce the result). Some problems have unknown efficient solution. These problems are called NP-complete problems. If we can show that the problem is NP-complete, we can spend our time developing an efficient algorithm that gives a good, but not the best possible solution. 10
- 11. Components of an Algorithm Variables and values Instructions Sequences A series of instructions Procedures A named sequence of instructions we also use the following words to refer to a “Procedure” : Sub-routine Module Function 11
- 12. Components of an Algorithm Cont. Selections An instruction that decides which of two possible sequences is executed The decision is based on true/false condition Repetitions Also known as iteration or loop Documentation Records what the algorithm does 12
- 13. A Simple Algorithm INPUT: a sequence of n numbers T is an array of n elements T[1], T[2], …, T[n] OUTPUT: the smallest number among them Performance of this algorithm is a function of n 13 min = T[1] for i = 2 to n do { if T[i] < min min = T[i] } Output min
- 14. Greatest Common Divisor The first algorithm “invented” in history was Euclid’s algorithm for finding the greatest common divisor (GCD) of two natural numbers Definition: The GCD of two natural numbers x, y is the largest integer j that divides both (without remainder). i.e. mod(j, x)=0, mod(j, y)=0, and j is the largest integer with this property. The GCD Problem: Input: natural numbers x, y Output: GCD(x,y) – their GCD 14
- 15. Euclid’s GCD Algorithm GCD(x, y) { while (y != 0) { t = mod(x, y) x = y y = t } Output x } 15
- 16. Euclid’s GCD Algorithm – sample run 16 while (y!=0) { int temp = x%y; x = y; y = temp; } Example: Computing GCD(72,120) temp x y After 0 rounds -- 72 120 After 1 round 72 120 72 After 2 rounds 48 72 48 After 3 rounds 24 48 24 After 4 rounds 0 24 0 Output: 24
- 17. Algorithm Efficiency Consider two sort algorithms Insertion sort takes c1n2 to sort n items where c1 is a constant that does not depends on n it takes time roughly proportional to n2 Merge Sort takes c2 n lg(n) to sort n items where c2 is also a constant that does not depends on n lg(n) stands for log2 (n) it takes time roughly proportional to n lg(n) Insertion sort usually has a smaller constant factor than merge sort so that, c1 < c2 Merge sort is faster than insertion sort for large input sizes 17
- 18. Algorithm Efficiency Cont. Consider now: A faster computer A running insertion sort against A slower computer B running merge sort Both must sort an array of one million numbers Suppose Computer A execute one billion (109 ) instructions per second Computer B execute ten million (107 ) instructions per second So computer A is 100 times faster than computer B Assume that c1 = 2 and c2 = 50 18
- 19. Algorithm Efficiency Cont. To sort one million numbers Computer A takes 2 . (106 )2 instructions 109 instructions/second = 2000 seconds Computer B takes 50 . 106 . lg(106 ) instructions 107 instructions/second 100 seconds By using algorithm whose running time grows more slowly, Computer B runs 20 times faster than Computer A For ten million numbers Insertion sort takes 2.3 days Merge sort takes 20 minutes 19
- 20. Pseudo-code conventions Algorithms are typically written in pseudo-code that is similar to C/C+ + and JAVA. Pseudo-code differs from real code with: It is not typically concerned with issues of software engineering. Issues of data abstraction, and error handling are often ignored. Indentation indicates block structure. The symbol " " ▹ indicates that the remainder of the line is a comment. A multiple assignment of the form i ← j ← e assigns to both variables i and j the value of expression e; it should be treated as equivalent to the assignment j ← e followed by the assignment i ← j. 20
- 21. Pseudo-code conventions Variables ( such as i, j, and key) are local to the given procedure. We shall not us global variables without explicit indication. Array elements are accessed by specifying the array name followed by the index in square brackets. For example, A[i] indicates the ith element of the array A. The notation “…" is used to indicate a range of values within an array. Thus, A[1…j] indicates the sub-array of A consisting of the j elements A[1], A[2], . . . , A[j]. A particular attributes is accessed using the attributes name followed by the name of its object in square brackets. For example, we treat an array as an object with the attribute length indicating how many elements it contains( length[A]). 21