Skip to main content

ARRAY vs ARRAYLIST


ARRAY vs ARRAYLIST
Array is an object used to save similar data type elements and its size is limited.
Array is static in nature. Once created we cannot change size of array.
  • ·       Random access, linear data structure
  • ·       Fixed size once created
  • ·       Can contain objects and primitives
  • ·       Must declare element type
  • ·       It is not a class
  • ·       Elements accessible with index number
Eg: int[] ar=new int[3]; //stores complete integer types

Arraylist is a part of Collection Framework of util package to store different data type objects and it is growable. Arraylist is dynamic in nature. It can be re-size itself when needed depending upon capacity and load factor.
  • ·       Random access, linear data structure
  • ·       Dynamic size, grows automatically
  • ·       Can only contain objects
  • ·       Element type  is OBJECT
  • ·       It is a class with many methods
  • ·       Accessing methods like get() etc are available
Eg: Arraylist arr=new Arraylist();
       arr.add(13); //integer type
       arr.add(13); //string type

ArrayList<String> stringList = new ArrayList<String>(); //Generic ArrayList to Store only String objects

The Methods Of ArrayList class are:
1)Add - stringList.add(“item”);
2)Remove- stringList.remove(0);
3)Clear- stingList.clear();
4)Insert
5)TrimToSize
6)Sort
7)Reverse 

Example:
import java.util.ArrayList;
public class Program
{
          public static void main(String[] args)
          {
// Create new ArrayList.
                              ArrayList<Integer> elements = new ArrayList<>();
// Add three elements.
                              elements.add(10);
                              elements.add(15);
                              elements.add(20);
// Get size and display.
                              int count = elements.size();
                              System.out.println("Count: " + count);
// Loop through elements.
                              for (int i = 0; i < elements.size(); i++)
{
                                          int value = elements.get(i);
                                          System.out.println("Element: " + value);
                              }
          }
}

Output
Count: 3
Element: 10
Element: 15
Element: 20

Labels:

Comments

Post a Comment

Popular posts from this blog

Advantages and Disadvantages of EIS Advantages of EIS Easy for upper-level executives to use, extensive computer experience is not required in operations Provides timely delivery of company summary information Information that is provided is better understood Filters data for management Improves to tracking information Offers efficiency to decision makers Disadvantages of EIS System dependent Limited functionality, by design Information overload for some managers Benefits hard to quantify High implementation costs System may become slow, large, and hard to manage Need good internal processes for data management May lead to less reliable and less secure data
1 comment
Read more

Inter-Organizational Value Chain

The value chain of   a company is part of over all value chain. The over all competitive advantage of an organization is not just dependent on the quality and efficiency of the company and quality of products but also upon the that of its suppliers and wholesalers and retailers it may use. The analysis of overall supply chain is called the value system. Different parts of the value chain 1.  Supplier     2.  Firm       3.   Channel 4 .   Buyer
Post a Comment
Read more

Big-M Method and Two-Phase Method

Big-M Method The Big-M method of handling instances with artificial  variables is the “commonsense approach”. Essentially, the notion is to make the artificial variables, through their coefficients in the objective function, so costly or unprofitable that any feasible solution to the real problem would be preferred, unless the original instance possessed no feasible solutions at all. But this means that we need to assign, in the objective function, coefficients to the artificial variables that are either very small (maximization problem) or very large (minimization problem); whatever this value,let us call it Big M . In fact, this notion is an old trick in optimization in general; we  simply associate a penalty value with variables that we do not want to be part of an ultimate solution(unless such an outcome is unavoidable). Indeed, the penalty is so costly that unless any of the  respective variables' inclusion is warranted algorithmically, such variables will ...
Post a Comment
Read more