Java Exercise 6 :

write a program to calculate relative size ranges for very small, small, medium, large, and very large ranges using standard deviation.

Thoroughly test the program.  Test the program using the data provided in tables 1, and 2.  Expected values are included in table 3.

Class Name	Class LOC	Number of Methods
each_char	18	3
string_read	18	3
single_character	25	3
each_line	31	3
single_char	37	3
string_builder	82	5
string_manager	82	4
list_clump	87	4
list_clip	89	4
string_decrementer	230	10
Char	85	3
Character	87	3
Converter	558	10

Table 1. LOC/Method Data

Chapter	Pages
Preface	7
Chapter 1	12
Chapter 2	10
Chapter 3	12
Chapter 4	10
Chapter 5	12
Chapter 6	12
Chapter 7	12
Chapter 8	12
Chapter 9	8
Appendix A	8
Appendix B	8
Appendix C	20
Appendix D	14
Appendix E	18
Appendix F	12

Table 2. Pgs/Chapter

	VS	S	M	L	VL
LOC/Method	4.3953	8.5081	16.4696	31.8811	61.7137
Pgs/Chapter	6.3375	8.4393	11.2381	14.9650	19.9280

Table 3. Expected Values

relative size tables are used to give you a framework for judging the size of new parts in your planned products.  For example, if you know the sizes of all previously developed parts of a certain type, you can then better judge the likely size of a new part of that type.  The standard deviation procedure described in the following section allows you to balance your esimates so they more or less conform to the normal distribution. 

The medium range (M) is the area from -0.5 standard deviations to +0.5 standard deviations from the mean, as shown in Figure 1.  Assuming that the data approximates a normal distribution, the likely number of parts that are within plus or minus 0.5 standard deviation of the average value is 38.3 percent.  Following similar logic, the range percentages area are as follows:

·         6.68 % should be very small

·         24.17% should be small

·         38.2% should be medium

·         24.17% should be large

·         6.68% should be very large

Example of calculating a relative size table

Class Name	Class LOC	Number of Methods	LOC/method
each_char	18	3	6.0000
string_read	18	3	6.0000
single_character	25	3	8.3333
each_line	31	3	10.3333
single_char	37	3	12.3333
string_builder	82	5	16.4000
string_manager	82	4	20.5000
list_clump	87	4	21.7500
list_clip	89	4	22.2500
string_decrementer	230	10	23.0000
Char	85	3	28.3333
Character	87	3	29.0000
Converter	558	10	55.8000

Class Name	LOC/method	ln(xi)
each_char	6.0000	1.7918
string_read	6.0000	1.7918
single_character	8.3333	2.1203
each_line	10.3333	2.3354
single_char	12.3333	2.5123
string_builder	16.4000	2.7973
string_manager	20.5000	3.0204
list_clump	21.7500	3.0796
list_clip	22.2500	3.1023
string_decrementer	23.0000	3.1355
Char	28.3333	3.3440
Character	29.0000	3.3673
Converter	55.8000	4.0218
Total		36.4197

Class Name	LOC/method	ln(xi)	(ln(xi)-avg)2
each_char	6.0000	1.7918	1.0196
string_read	6.0000	1.7918	1.0196
single_character	8.3333	2.1203	0.4641
each_line	10.3333	2.3354	0.2173
single_char	12.3333	2.5123	0.0836
string_builder	16.4000	2.7973	0.0000
string_manager	20.5000	3.0204	0.0479
list_clump	21.7500	3.0796	0.0773
list_clip	22.2500	3.1023	0.0905
string_decrementer	23.0000	3.1355	0.1115
Char	28.3333	3.3440	0.2943
Character	29.0000	3.3673	0.3201
Converter	55.8000	4.0218	1.4890
Total		36.4197	5.2350

Program :

 

import java.text.DecimalFormat;

public class Day {

      double loc[]={18,18,25,31,37,82,82,87,89,230,85,87,558};

      double methods[]={3,3,3,3,3,5,4,4,4,10,3,3,10};

      public static void main(String[] args) {

            Day myobj=new Day();

            myobj.locpermethod();

      }

      public void locpermethod()

      {

            double locperm[]=new double[50];

            double tot=0,lo=0,avg=0,sq=0,tot1=0,avg1=0,srt=0;

            DecimalFormat df = new DecimalFormat("0.0000");

            for(int i=0;i<13;i++)

            {

                 

                  locperm[i]=loc[i]/methods[i];

                  lo=Math.log(locperm[i]);

                  tot=tot+lo;

     

            }

            avg=tot/13;

            System.out.println(df.format(tot));

            System.out.println(df.format(avg));

           

            for(int i=0;i<13;i++)

            {

                  lo=Math.log(locperm[i]);

                  sq=Math.pow((lo-avg),2);

                  tot1=tot1+sq;

                  }

           

            avg1=tot1/12;

            System.out.println(df.format(tot1));

            System.out.println(df.format(avg1));

            srt=Math.sqrt(avg1);

            System.out.println(df.format(srt));

           

            double vs=avg-(2*srt);

            double s=avg-srt;

            double m=avg;

            double l=avg+(srt);

            double vl=avg+(2*srt);

           

            System.out.println(df.format(vs));

            System.out.println(df.format(s));

            System.out.println(df.format(m));

            System.out.println(df.format(l));

            System.out.println(df.format(vl));

     

      }

         

}

Program developed by Rajkumar

Output :

36.4197
2.8015
5.2350
0.4363
0.6605
1.4805
2.1410
2.8015
3.4620
4.1225