1. Lecture 17 Software Metrics
Software Engineering
Lecture 17
Software Metrics

2. What is a Software Metric?
Quantitative measure of the quality of software.
Measure of the difficulty of testing, understanding, or maintaining a piece of software
Measure of ease of using software

3. Size Metrics
The larger the more complex – There are many ways to define size of a program
1. Lines of Code (LOC)
Standard definition of LOC
Count number of lines and data definitions
Do not count comment lines
Count a line containing both a statement or part of a statement and a comment as an executable line.

4. Problems with LOC Lack of a Standard definition for line of code.
Application written in multiple language.
Size variation due to individual programming style.

5. Size Metrics 2. Number of Tokens -- A detailed measure of size
Size of program is number of tokens, where a token is a
lexical token
keyword, arithmetic operator, constants, grouping symbol such as parenthesis or bracket and so forth)

6. Data Structure Metrics
A count of amount of data input to , processed in, and output from software is called data structure metrics.

7. Information Flow Metrics
A coupling module increases with the complexity of interface and the total number of modules a module is coupled with.
We want a metric that is better at quantifying coupling between modules.
The information flow metrics attempt to define the complexity in terms of the total information flowing through a module

8. The complexity of module is considered as depending on the intra module complexity and the inter module complexity.
intra module complexity- size of the module in LOC
inter module complexity- Total information flowing in the module(inflow) and total info flowing out of the module(outflow

9. Design complexity
Dc= size*(inflow*outflow)raise to the power 2
Module complexity also depends upon no of modules to or from which it is flowing.
Dc= fan_in*fan_out+inflow*outflow
Fan_in- the no of modules that call this module
Fan_out- no of modules this module calls

10. Error prone
Dc > avg_complexity+ std_deviation
Complex
Avg_complexity <DC<Avg_complexity+std_deviation
Normal
Otherwise

11. Function Points Weighted sum of following:
1. External inputs - provided by user that describe distinct application-oriented data (e.g. file names)
2. External outputs - items provided to user that generate distinct application-oriented data (e.g. reports)
3. External inquiries - interactive inputs requiring a response
4. External files - machine readable interfaces to other systems
5. Internal files - logical master files in the system