2. A Good Manager Measures
Process
process metrics
measurement
Product
project metrics
product metrics
3. Project Size Estimation
Accurate estimation of the problem size is
fundamental to satisfactory estimation of the other
project parameters such as effort , time duration for
completing the project and the total cost for
developing the software.
The project size is neither the number of the bytes that
the source code occupies nor the byte size of the
executable code.
The project size is a measure of the problem
complexity in terms of the effort and time required to
develop the product.
5. Metrics to estimate size
The IEEE glossary defines a metric as “a quantitative
measure of the degree to which a system, component,
or process possesses a given attribute.”
In software development, a metric (noun) is the
measurement of a particular characteristic of a program's
performance or efficiency.
Four metrics are popularly being used to estimate size.
They are
Count the lines
Lines of code(LOC)
Function point(FP)
Feature point
6. ways to count the lines
Lines of code, or LOC, looks like a simple concept.
However, it's not. There are several ways to count the
lines. Depending on what you count, you get a low or a
high line count. In the table below you can see various
alternatives. The "Supported as" column shows which
metrics Project Metrics supports.
7. Project metrics
Metric
Supported as
Description
Physical lines
LINES
This metric counts the
physical lines
Physical lines of code
(not supported)
This type of a metric
counts the lines but
excludes empty lines and
comments.
Logical lines
LLINES
A logical line covers one
or more physical lines.
Two or more physical
lines can be joined as one
logical line with the line
continuation sequence
8. Project metrics
Logical lines of code
LLOC
A logical line of code is
one that contains
actual source code. An
empty line or a
comment line is not
counted in LLOC
Statements
STMT
This is not a line count,
but a statement count
9. Line of code(LOC)
LOC is the popular and simplest one.
This measures the size of a project by counting the
number of source instruction in the development
program ignoring the commenting code and header
lines.
In order to estimate the LOC count at the beginning of
a project one would to make a systematic guess.
By using the lowest level modules(division of a
problem) , project managers arrive the total size
estimation.
10. Shortcomings of LOC
LOC gives a numerical value of problem size.
Problem:
If may vary widely with individual coding style.
Exampleone programmer may write several instruction
in a single line but another programmer may write these
instructions in several lines.
Solution:
count the language tokens rather than the lines of
code.
11. Shortcomings of LOC
LOC is a measure of the coding activity alone.
Problem:
a good problem size measure should consider
the total effort for specify, design, code , test etc.
It merely computes the number of source line in the
final program.
Problem:
coding is a very small part in the overall
software development activities.
12. Shortcomings of LOC
LOC metrics measure the lexical complexity of a program
and does not address the more important issue of logical or
structure complexity.
Problem
a program having complex logic would require
much more effort to develop than a program with simple
logic.
LOC measure correlates poorly with the quality and
efficiency of the code.
Problem
large code size does not imply better quality or
higher efficiently.
13. Shortcomings of LOC
It is very difficult to accurate estimate LOC in the final
product from the problem specification. The LOC
count can only be accurately computed only after the
code has been fully develop.
LOC metric penalizes use of high level programming
language ,code reuse etc. if a programmer use many
library routines or he/she reuse code then the LOC of
that problem is less but it not mean that the effort of
that program is very few. So it not the right way to
estimate the project size.
14. Function point metrics
This metric overcomes the shortcoming of the LOC metric.
In LOC metric size can be determine accurately only after
the product has fully been developed but in function point
size can be determine directly from program specification.
Here the size of a software product is directly dependent on
the number of different function or features it supported. It
also depend on the number of the file and the interfaces.
It is certain that a product support many features is larger
in size than a product with few features.
15. Steps to compute function point
Beside using the number of the input and output data
values function point metric computes the size of a
software product(in unit of function points or FPs).
The steps for computing function point-
To compute the unadjusted function point(UFP)
UFP is refined to reflect the differences in the complexities of
the different parameters
FP is computed by further refining UFP to account for the
specific characteristic of the project that can influence the
development effort.
UDP=(number of inputs)*4+(number of outputs)*5+(number
of inquires)*4+(number of files )*10+(number of
interfaces)*10
16. Different parameters of function
point
Number of inputs:
Here each data item input by the user is counted.
Data input should be distinguished from user inquiries.
Here the data item input by the user are not simply
added to compute the number of input but a group of
related inputs are consider as a single input.
Example- in employee payroll software the data itemname , age , sex , address are together consider as a
single input.
17. Different parameters of function
point
Number of outputs:
The output consider refer to reports printed , screen outputs ,
error message produce etc.
The individual data item within a report is not consider as a
output a set of related data item is consider as a output.
Number of inquires:
It is the number of distinct interactive queries which can be
made by the users.
Number of files:
Each logical file which implies a group of logically related
data is counted.
Logical file include data structure and physical files.
18. Different parameters of function
point
Number of interfaces:
The interface considered are the interface used to
exchange information with other system.
Complexity level of each parameter is graded as simple,
average , complex. The weight for the different
parameter can be compute based on the following tableType
Simple
Average
complex
Input
3
4
6
Output
4
5
7
Inquiry
3
4
6
Number of files
7
10
15
Number of
interfaces
5
7
10
19. Calculation of function point
Then technical complexity factor(TCF)for the project
is computed and the TCF is multiply with UFP to get
FP.
There are 14 parameter that can be influence the
development effort valued form 0(no influence)6(strong influence). The resulting numbers are
summed to get degree of influence(DI).
TCF=(.65+.01*DI)
DI vary from 0-84 and TCF vary from .65-1.35.
Finally FP is given as a product of UFP and TCF.
FP=UFP*TCF.
20. Feature point metric
Function point does not account the algorithm
complexity of a software.
It assume that the effort required to design and
develop any two functionalities of the system is exactly
the same. But normally it is not true.
To overcome this problem an extension of the function
point metric is proposed. That is
Feature point metric
In feature point metric an extra parameter is used.
That is
Algorithm complexity
21. Feature point metric
It is a superset of FP.
In this metric we compute the complexity of a
function.
So when used on real time and systems software,
Feature Points often generate higher totals than
Function Points
It is certain that grater effort is required to develop a
complex function and therefore its size should be
larger compared to simple function.
22. Advantages and disadvantages of
these metrics
Function point and feature point metrics are language
independent.
They are easily computed from the SRS document during
project planning.
But these metrics are very subjective. For example the data
student_details contains student name and address. It is
possible one consider it as a single unit of data and another
consider name and address are two different unit of data.
So there is a possibility different project manager consider
different function point measure in a same problem.
23. Conclusion
Project size estimation is an important thing which
can be determined by different metrics. It helps the
project manager to get the idea about different
parameter like effort, time etc.
Between two metrics function point(FP) is better than
line of code(LOC),because in LOC there is several
problem and we can not properly estimate the size of
project.
