Topics
Operating System
- Introduction to Operating System (OS)
- Idea of an Operating System
- Windows NT
- LINUX
- File Systems and Its types
- File Operations
- Access Methods and its types
- Allocation Methods
- Concepts Related to Process Management
- Concepts related to memory management
- Basics of Graphical User Interface (GUI)
- Access and Security Aspects of O.S.
Data Structures
C++ Programming
- Introduction to C++ Programming
- Idea Behind Object-Orientated Programming
- Object-orientated programming approach
- Object-Oriented Terms and Concepts
- Classes and Objects
- Constructors and Destructors
- Functions in C + +
- Arrays in C++
- Pointers in C++
- References in C++
- Strings in C++
- Inheritance
- Virtual functions and polymorphism
- Friends in C++
- Operator overloading and type conversions
- Files and Stream
HyperTex Markup Language (HTML)
- Introduction to searching
- Linear search
- Binary search
Searching
To find any record (maybe data item) matching the specific criteria in a group of items or list is called searching. For searching various algorithms are available:
a) Linear searching b) Binary searching
Linear Searching
If 'N' items are given and you want to find whether item is present in group of items or not this is used. This is the simplest approach, where every data item is compared with the item to be found. Here, there is no prerequisite condition for the list to be sorted.
Binary Searching
This approach only works on lists which are sorted in increasing order numerically.
Procedure is as follows
- Calculate position of mid-point
- Compare the value of mid-point element with the number. If desired value is less than the value of mid-point element, then reduce the search in second half considering midpoint of the interval.
- Repeat the search if interval is not empty.
- On successful search, position is printed.
To narrow down search, binary search is used. The complexity is measured by the number of f(n) of comparisons to locate ITEM in DATA where DATA contains n elements. Each comparison reduces sample size in half. So we require at most f(n) comparisons to locate ITEM where f (n) = [log2n]+1.
Applications & Limitations
This algorithm is used to search ordered array. To find out the target element whether it is present or not. If present; then correspondingly give position in the array.
It’s limitations include that the given list must be sorted.
