The document discusses software metrics, defining them as measures related to software and its production, and explains their significance in evaluating complexity, quality, and developer productivity. It covers various types of metrics, including lines of code, cyclomatic complexity, object-oriented metrics, and quality metrics, while illustrating their importance for software development and project management. The document emphasizes different scales of measurement and their implications for assessing software attributes and team effectiveness.

1. Software Measurement Software Economics 2010

2. Anton Litvinenko Co-founder and CTO at Metrics tracking kit for software development

3. Key competence: software measurement and metrics 9 years of software development at Programeter, Mobi, and MicroLink

4. MSc in computer science at Tartu University

5. Agenda What is a software metric?

6. Are software metrics “ good ” or “ bad ”?

7. What is a “ measure ”?

8. What is a “measure”? “ Way of associating a number with some attribute of a physical object ” height -> meters temperature -> degrees Celsius

9. What is “measure”? One-to-one mapping between physical objects and formal objects (e.g numbers)

10. Same Stuff Formally Relational System – tuple consisting of Set of objects ( e.g. collections of apples )

11. Relations on these objects ( e.g. more, equal )

12. Binary operations on these objects ( e.g. combine, put together ) What would be the corresponding formal relational system?

13. Relationships and Operations Apples: Steve Jobs has 7 apples

14. Steve Ballmer has 4 apples Jobs has more apples

15. Jobs and Ballmer can cooperate and put their apples together to have a larger pile

16. We defined a “ complete transition ” from “ real world ” into “ formal world ”

17. Same Stuff Formally... again Let A be a relational system of physical objects (e.g. apples)

18. B be a relational system of formal objects ( e.g. numbers)

19. m be a measure from A to B then

20. Tuple A , B and m is a scale if Relations from A equivalent to relations from B

21. For each operator in A there is a corresponding operator in B

22. Why is this important?

23. What Can You Say?

24. Why is this important? Software design: 10 modules with complexity 20 – 30 range

25. 20 modules with complexity 10 – 30 range Which one is less complex?

26. We don't have intuition for such cases

27. Intelligence Barrier

28. Example: Temperature Facts : Steve : today is 40 ºF, yesterday was 80ºF

29. Anton : today is 4ºC, yesterday was 27ºC Statements : Steve : Yesterday was warmer than today

30. Anton : Yesterday was warmer than today

31. Example: Temperature Facts : Steve : today is 40 ºF, yesterday was 80ºF

32. Anton : today is 4ºC, yesterday was 27ºC Statements : Steve : Yesterday was 2x times warmer Is this a meaningful statement about temperature?

33. Statement is meaningful when it gives same result on all similar scales

34. Scales are similar when there is a transformation from one scale to another that retains all defined relations and operations

35. Nominal Scale Giving “ names ” to objects Equality Gender Any naming is similar to any other Numbers on t-shirts of football players Any unique numbering is similar to any other

36. View from 3000 feet :) Nominal Scales Gender T-shirt Numbering

37. Ordinal Scale Giving “ names ” in particular order More .... than ....

38. Middle element – median Rating of tennis players Similar: any other rating that retains the order

39. All Ordinal Scales Are Nominal Nominal Ordinal Gender T-shirt Numbering Top 100 Grading

40. Interval Scale Assigning numbers so that interval is also meaningful Both median and arithmetic mean

41. Similar – reachable via positive linear transformation : t(x) = ax + b Temperature in Celsius scale Similar: Fahrenheit scale

42. Interval Scales Are Ordinal Nominal Ordinal Interval Gender T-shirt Numbering Top 100 Grading Temperature

43. Ratio Scale Ratio of two measures is meaningful All statistical measures

44. Similar – reachable via positive linear transformation in form of t(x) = ax Length, height, ... Similar: Imperial units

45. Ratio Scales Are Interval Nominal Ordinal Interval Ratio Gender T-shirt Numbering Top 100 Grading Temperature Length Height

46. Absolute Scale Only one way of measuring objects ! Similar – identity transformation: t(x) = x Counting: My team has 5 members

47. My software is 25 lines of code

48. Absolute Scales Are Ratio Nominal Ordinal Interval Ratio Absolute Scales Gender T-shirt Numbering Top 100 Grading Temperature Length Height Team Size

49. Exercise 2 Cost is usually a measure with ratio scale

50. Quality is only ordinal (rarely interval)

51. Judgment in terms of value Quality per unit of cost

52. Should we pay 2x for 2x quality? Combining cost measure on a ratio scale with quality measure on ordinal scale , what scale do you get ?

53. In This Course: Metric = Measure

54. Software Metric is a measure of anything directly related to software or its production

55. Agenda What is a software metric?

56. Examples of software metrics Most famous :)

57. Can anybody name any software metric?

58. Lines Of Code (LOC) – Product Size 12 14 18

59. Lines Of Code

60. Lines Of Code – Summary Accurate, easy to measure How to interpret ... Empty lines

61. Comments

62. Several statements on one line Language dependent

63. Doesn't respect complexity and content

64. McCabe's Cyclomatic Complexity Thomas McCabe, 1976

65. Complexity of a program Number of linearly independent paths through a function

66. Usually calculated using flow graph V(G) = e – n + 2p e – num of edges, n – num of vertices, p – num of unconnected parts of graph

67. McCabe's Cyclomatic Complexity

68. McCabe's Cyclomatic Complexity e = 7

69. n = 6

70. p = 1

71. V(G) = 3

72. Cyclomatic Complexity – Summary Automated

73. Maintainability V(G) > 10 -> Probability of defects rises Testability V(G) is an upper bound for the branch coverage Each control structure was evaluated both to true and false V(G) is a lower bound for the path coverage All possible paths were executed Doesn't respect other types of complexity Data structure, data flow, interfaces

74. Exercise 3 Calculate LOC

75. Draw a flow graph

76. Calculate McCabe's cyclomatic complexity Code snippet

77. Agenda What is a software metric?

78. Examples of software metrics LOC and McCabe's cyclomatic complexity

79. Object oriented metrics

80. Object Oriented Metrics Shiyam Chidamber and Chris Kemerer , 1994 Metrics based on firm theoretical basis and experience of professional software developers

81. Measure unique aspects of the object oriented approach

82. Inheritance Metrics Depth of inheritance tree (DIT) Depth of the class in the inheritance tree Number of children (NOC) Number of immediate descendants NOC: 2 DIT: 2 NOC: 3 DIT: 1

83. Complexity Weighted method count (WMC) Sum of McCabe's cyclomatic complexities of all methods Response for a class (RFC) Number of public methods in a class and methods directly called by these

84. Complexity – Example RFC = 6, WMC = 1 + 2 + 1 = 4

85. Coupling Coupling between object classes (CBO) Number of classes given class is coupled to Lack of cohesion in methods (LCOM) Number of method pairs that do not share instance variables vs number of methods that share at least one instance variable

86. Coupling – Example CBO = 2, LCOM = 3 – 0 = 3

87. Coupling – Example LCOM = 2 – 1 = 1

88. Agenda What is a software metric?

89. Examples of software metrics LOC and McCabe's cyclomatic complexity

90. Object oriented metrics

91. Object oriented design quality metrics

92. Object Oriented Design Bad design symptoms: Rigidity, fragility, immobility, viscosity Class design principles Open closed principle , Liskov substitution principle , ... Package architecture principles Stable dependencies principle , Stable abstractness principle , …

93. OO Design Quality Metrics Robert Martin (aka Uncle Bob) , 1994

94. Measure quality of an object oriented design

95. Can we divide dependencies into “ good ” and “ bad ”? Dependencies Between Classes

96. Dependencies Stable (good) vs unstable (bad) class

97. Stable No need to change = independent

98. Hard to change = many dependents = responsible Unstable Depends on many = dependent

99. Easy to change = no dependents = irresponsible

100. Class Category Class category – group of highly cohesive classes Closed and open to changes together

101. Reused together

102. Same goal Packages in Java, namespaces in C#

103. Dependency Metrics Afferent Coupling (Ca) – number of classes outside the category depending on the classes inside the category Incoming dependencies Efferent Coupling (Ce) – number of classes inside the category depending on the classes outside the category Outgoing dependencies

104. Example - Coupling Package One Package Two Package Three Ca(Package One) = 1, Ce(Package One) = 2

105. Instability (I) Ratio of outgoing dependencies to total number of dependencies I = Ce / (Ca + Ce)

106. Stable -> I = 0 -> Ce = 0

107. Unstable -> I = 1 -> Ca = 0, Ce > 0

108. Should all categories be stable ?

109. Why a stable category needs to be extensible ? How?

110. Abstractness (A) Degree to which a category is abstract Ratio of abstract classes to the total number of classes in category Completely abstract -> A = 1 -> all classes are abstract

111. Completely concrete -> A = 0 -> no abstract classes in category

112. Is there a relationship between Instability and Abstractness ?

113. Main Sequence

114. Distance From Main Sequence D' = |A + I – 1| Normalized to range from [0, 1]

115. Agenda What is a software metric?

116. Examples of software metrics LOC and McCabe's cyclomatic complexity

117. Object oriented metrics

118. Object oriented design quality metrics

119. Developer and team metrics

120. Developer and Team Metrics Productivity How active developers are, how much work is being done Knowledge How much developers know the software they are working on Expertise What kind of tools and libraries developers use Team “healthiness” Communication and knowledge sharing

121. Productivity: Code Churn Metrics Amount of code changed in the software during the period of time