CSC307 Lecture 11

Introduction to Software Engineering
Software Metrics
(202407)

Code metrics are essential tools for assessing the quality and complexity of software. Today, we review size metrics, including Lines of Code (LOC), effective Lines of Code (eLOC), and logical Lines of Code (lLOC); the complexity metric that measures the number of linearly independent paths in a program called Cyclomatic Complexity (CC); and structural metrics, including Abstractness and Instability, that evaluate the balance between abstraction and concrete implementation, and the degree of dependency, respectively.

Transcript

1. Dr. Javier Gonzalez-Sanchez javiergs@calpoly.edu www.javiergs.info o ffi ce: 14 -227 CSC 307 Introduction to Software Engineering Lecture 11. Software Metrics
2. Reminder 2 Do not forget to submit your Individual proposal of What feature(s) you are implementing in your final project.
3. FRIDAY: Work on your project NO LECTURE / NO LAB MONDAY: CI/CD WEDNESDAY: CI/CD + Full Review FRIDAY: Final Exam Announcement 3
4. Code Metrics
5. Metrics Size LOC eLOC lLOC Complexity Cyclomatic Complexity Software Metrics 5
6. Software Metrics Size
7. Size Metrics • LOC – Lines of Code Metric. Including lines of a single br a ce or p a renthesis • LOC a re used to cre a te time a nd cost estim a tes. • LOC a re a tr a cking tool to me a sure the degree of progress on a module or project. • An experienced developer c a n g a ge a LOC estim a te b a sed upon knowledge of p a st productivity on projects. 7
8. Size Metrics • eLOC – e ff ective Lines of Code Metric. Only code st a tements • An e ff ective line of code or eLOC is the me a surement of a ll lines th a t a re not comments, bl a nks or st a nd a lone br a ces or p a renthesis. These c a n in f l a te LOC metrics by 20 to 40 percent. • This metric more closely represents the qu a ntity of work performed. 8
9. Size Metrics • lLOC – logic a l Lines of Code Metric. • These st a tements a re termin a ted with a semi-colon. • The control line for the "for" loop cont a in two semi-colons but a ccounts for only one semi colon. 9
10. Example 10
11. Test Yourselves
19. Software Metrics Complexity
20. Function Metrics • Cyclomatic Complexity. It is a quantitative measure of the number of linearly independent paths. • P a ths occur when "while,” "for,” "if,” "c a se," a nd "goto" keywords a ppe a r within the function. • If the source code cont a ined no control f low st a tements (condition a ls or decision points), the complexity would be 1 • If the code h a d one single-condition IF st a tement, there would be two p a ths through the code: one where the IF st a tement ev a lu a tes to TRUE a nd a nother one where it considers to be FALSE. • Two nested single-condition IFs, or one block with two conditions, would produce a complexity of 3. 20
21. Cyclomatic Complexity 21 CC = Edge - Node + 2 Or CC = ConditionalNodes + 1
22. Cyclomatic Complexity i = 0; n=4; while (i<n-1) { j = i + 1; while (j<n) { if (A[i]<A[j]) swap(A[i], A[j]); } i=i+1; } // CC = 9 - 7 + 2 = 4 // CC = 3 + 1 = 4 (Condition nodes are 1,2 and 3 nodes) // A set of possible execution path of a program // 1, 7 // 1, 2, 6, 1, 7 // 1, 2, 3, 4, 5, 2, 6, 1, 7 // 1, 2, 3, 5, 2, 6, 1, 7 22
23. Complexity Number Meaning 1-10 Structured and well written code High Testability Cost and Effort is less 10-20 Complex Code Medium Testability Cost and effort is Medium 20-40 Very complex Code Low Testability Cost and Effort are high >40 Not at all testable Very high Cost and Effort Cyclomatic Complexity 23
24. Test Yourselves
25. Reminder 25 Which of the following projects is in a better stand?
28. Structural Metrics Abstractness Instability
29. Is this a good design? 29
30. Is this a good design? 30
31. Abstractness of a Package • It is the degree to which a cl a ss or p a ck a ge emph a sizes a bstr a ction over concrete implement a tion • It is a v a lue 0 to 1: • For p a ck a ges, It is the r a tio of a bstr a ct cl a sses or interf a ces to the tot a l number of cl a sses within a p a ck a ge. • For cl a sses, It is 0 for a concrete cl a ss a nd 1 for a n interf a ce or a bstr a ct cl a sses 31
32. Instability • Indic a tes whether: ( a ) the item is m a inly used by others (st a ble – h a rd to ch a nge); or (b) it m a inly depends on other items (in-st a ble – ch a nge a ble). • It is a v a lue between 0 a nd 1: • 0 only incoming dependencies to • 1 (only outgoing dependencies). 32
33. Structural Metrics Distance
34. Distance • Dist a nce: how f a r a p a ck a ge is a w a y from the M a in Sequence • D = A + I – 1 • V a lues -1 to 1 • Absolute Dist a nce |D| 34
35. Distance 35 Abstract Concrete Stable Hard to Change Only incoming dependencies Unstable Changeable Only outgoing dependencies the m ain sequence Painful Useless 0 1 1 0 Instability Abstractness
36. project3.common.model project3.client.UI project3.server.controller
37. Test Yourselves
39. Questions 39
40. Lab 11 Software Metrics
41. Reminder 41 Calculate metrics for your Paint App 3.0 (or 2.0)
42. For each class: LOC eLOC lLOC Max CC A I D Draw the Distance Chart Reminder 42
43. Let’s Work 43
44. CSC 307 Introduction to Software Engineering Javier Gonzalez-Sanchez, Ph.D. javiergs@calpoly.edu Summer 2024 Copyright. These slides can only be used as study material for the class CSC307 at Cal Poly. They cannot be distributed or used for another purpose.