1. Creator: ACSession No: 7 Slide No: 1Reviewer: SS CSE300Advanced Software EngineeringSeptember 2005 Software Measurement – Estimation and Productivity CSE300 Advanced Software Engineering University of Sunderland © 2005 Anne Comer anne.comer@sunderland.ac.uk

2. CSE300Advanced Software EngineeringSeptember 2005 Creator/Editor: ACSession No:7 Slide No: 2Reviewer: SS Objectives for this Lecture 1.The review the estimation and measurement of product attributes 2.Identify the range of product attributes 3.Look in detail at cyclomatic complexity

3. CSE300Advanced Software EngineeringSeptember 2005 Creator/Editor: ACSession No:7 Slide No: 3Reviewer: SS Product Attributes There are a range of attributes that can be measured.. Size, Data flow structure, Control flow structure, Functionality

4. CSE300Advanced Software EngineeringSeptember 2005 Creator/Editor: ACSession No:7 Slide No: 4Reviewer: SS Product type vs. measure Code - KLOC ( KDSI + NCLOC), bytes, Specification - function points, Natural Lang. - no. of words/sentences/pages/diagrams Documents Design - no. of subsystems, modules, ‘children’

5. CSE300Advanced Software EngineeringSeptember 2005 Creator/Editor: ACSession No:7 Slide No: 5Reviewer: SS Structure Measurement of structure has been influenced by two things: Structured design & programming methods Complexity of individual modules

6. CSE300Advanced Software EngineeringSeptember 2005 Creator/Editor: ACSession No:7 Slide No: 6Reviewer: SS Measures from Graph Models flow of control of a program or within a design flow of data within a program or between modules in a design

7. CSE300Advanced Software EngineeringSeptember 2005 Creator/Editor: ACSession No:7 Slide No: 7Reviewer: SS Control Flow Graph 10 input p 20 if p > 39 then 50 30 m = 3 40 g = ‘fail’ 50 if p > 65 then 80 60 m = 4 70 g = ‘pass’ 80 m = 5 90 g = ‘distinction’ 100 print g 10 20 30 50 40 60 80 70 90 100

8. CSE300Advanced Software EngineeringSeptember 2005 Creator/Editor: ACSession No:7 Slide No: 8Reviewer: SS Graph properties Edge- a connection between two nodes Node- a l.o.c., a statement Loop- a loop

9. CSE300Advanced Software EngineeringSeptember 2005 Creator/Editor: ACSession No:7 Slide No: 9Reviewer: SS Attributes of Graphs There are a number of measurable attributes of graph models of control flow… no. of edges- size no. of nodes- size min. no. of paths covering each edge once - testability min. no. of paths covering each loop once - testability min. no. of paths covering every node - testability

10. CSE300Advanced Software EngineeringSeptember 2005 Creator/Editor: ACSession No:7 Slide No: 10Reviewer: SS Cyclomatic Complexity (i) McCabe was interested in control flow.. Cyclomatic complexity measures - no. of linearly independent paths through the program

11. CSE300Advanced Software EngineeringSeptember 2005 Creator/Editor: ACSession No:7 Slide No: 11Reviewer: SS Cyclomatic Complexity (ii) Measured in three ways… no. edges - no. nodes +2 no. of regions in the graph no. of predicate nodes +1

12. CSE300Advanced Software EngineeringSeptember 2005 Creator/Editor: ACSession No:7 Slide No: 12Reviewer: SS Cyclomatic Complexity (iii) When is it useful? - As an indicator of testability - OK - As a measure of ‘complexity’ - dubious

13. CSE300Advanced Software EngineeringSeptember 2005 Creator/Editor: ACSession No:7 Slide No: 13Reviewer: SS Key Points LOC is too specific a measure LOC is language dependent – no really accepted standards Size, data structure, control structure, function Graph measures indicate complexity Cyclomatic complexity does not measure complexity; it may measure testedness