Software metrics

When designing a bridge, an architect has al sorts of tools & techniques to verify it won't collapse.

Us software developers... We build. And with a bit of luck, we'll even test. And then we pray it doesn’t collapse :)

Can we measure software? Can we compare code objectively? Can we predict problems?

Transcript

1. Measure twice, cut once SOFTWARE METRICS
2. @matthiasmullie Software metrics
3. Make software measurable instead of relying on intuition. Software metrics
4. Presentation title Software metrics
5. Presentation title Software metrics
6. Presentation title Software metrics
7. Software metrics COMPLEXITY
8. Every code path adds complexity Counts # of code paths Software metrics » Complexity Cyclomatic complexity
9. • Analyze control flow • Start at 1 • Increase at every decision path
 (if, for, case, …) Software metrics » Complexity Cyclomatic complexity
10. if ($user->isLoggedIn()) { echo 'Welcome back, ' . $user->getName(); } else { echo 'Hi there, stranger!'; } Cyclomatic complexity = 2 Software metrics » Complexity Cyclomatic complexity
11. Every code path adds complexity Counts # possible outcomes Software metrics » Complexity NPath complexity
12. Software metrics » Complexity NPath complexity if ($user->getSalutation()) { echo $user->getSalutation().' '; } if ($user->getName()) { echo $user->getName(); } else { echo 'anon'; } Outcomes: • $salutation anon • anon • $salutation $name • $name
13. Every operation adds complexity Software metrics » Complexity Halstead measures
14. • Analyze vocabulary • Count amount of operators
 (+, -, =, &&, ... and reserved words,
 like if and for) • Count amount of operands
 (values, variables & function names) Software metrics » Complexity Halstead measures
15. if ($user->isLoggedIn()) { echo 'Welcome back, ' . $user->getName(); } else { echo 'Hi there, stranger!'; } Operands = 4 (4 unique) Software metrics » Complexity Halstead measures
16. if ($user->isLoggedIn()) { echo 'Welcome back, ' . $user->getName(); } else { echo 'Hi there, stranger!'; } Operators = 11 (7 unique) Software metrics » Complexity Halstead measures
17. Engineered to match human analysis Software metrics » Complexity Maintainability index
18. Combination of: • Cyclomatic complexity • Halstead measures • Lines of code Software metrics » Complexity Maintainability index
19. Metrics for matthiasmullie/minify, MatthiasMullie\Minify\JS::stripWhitespace See https://www.cauditor.org/matthiasmullie/minify/c17eb048daa44b43fa98bfa405147e77a040df76/metrics Software metrics » Complexity Maintainability index
20. Questions? Software metrics » Complexity
21. Software metrics COUPLING
22. Amount of incoming dependencies = other classes using this one Common for core functionality Software metrics » Coupling Afferent coupling
23. class Afferent { function __construct() {} } class Efferent { function __construct(Afferent $a) {} } Afferent: 1, Efferent: 0 Software metrics » Coupling Afferent coupling
24. Changes here may break things elsewhere Must be stable & thoroughly tested Software metrics » Coupling Afferent coupling
25. Amount of outgoing dependencies = other classes being used Common for controllers Software metrics » Coupling Efferent coupling
26. class Afferent { function __construct() {} } class Efferent { function __construct(Afferent $a) {} } Afferent: 0, Efferent: 1 Software metrics » Coupling Efferent coupling
27. • Harder to read/maintain • Harder to reuse • Harder to test in isolation • Brittle Software metrics » Coupling Efferent coupling
28. Changes elsewhere may break things here Probably violates single responsibility principle Software metrics » Coupling Efferent coupling
29. = efferent coupling / total coupling = efferent coupling / (efferent + afferent) Resilience to change Software metrics » Coupling Instability
30. High efferent coupling = likely to be impacted by changes in
 = other classes = not stable Software metrics » Coupling Instability
31. Low afferent coupling = change is easy because there isn’t much
 = that depends on this = not stable Software metrics » Coupling Instability
32. Stable = good … as long as you don’t need to change the implementation! Software metrics » Coupling Instability
33. Aim for extremes, make classes as stable or unstable as possible! Unstables can be refactored/decomposed later. Better than having dependencies everywhere. Software metrics » Coupling Instability
34. Counts # of ancestors Software metrics » Coupling Depth of inheritance
35. class Ancestor {} DIT: 0 class Descendant1 extends Ancestor {} DIT: 1 class Descendant2 extends Descendant1 {} DIT: 2 Software metrics » Coupling Depth of inheritance
36. Inheritance is not bad! • Code reuse • Polymorphism Software metrics » Coupling Depth of inheritance
37. But too much is! • Less stable: change in ancestor can affect descendants • More complexity: methods of all ancestors are inherited Software metrics » Coupling Depth of inheritance
38. Questions? Software metrics » Coupling
39. WHY WOULD I CARE? Software metrics
40. Presentation title Software metrics » Usage Which would you rather maintain?
41. Presentation title Software metrics » Usage
42. Software metrics » Usage Complexity This guy has something going on! Let’s see…
43. It’s not too crazy! But: • Recursion • 3 loops • 4 conditions • Callback function Software metrics » Usage Complexity
44. Method does too much: • Data transformation • Processing • Cleanup Hard to test & prove right! Software metrics » Usage Complexity
45. Software metrics » Usage Complexity This guy has a lot going on…
46. Presentation title Software metrics
47. Software metrics » Usage Coupling • Lots of outgoing dependencies • Some inheritance Very brittle!
48. Changes in any of these could affect this class! Software metrics » Usage Coupling
49. Software metrics » Usage Refactoring • 1000+ LOC class • Pretty complex • Very unstable • Self-contained, barely reusable
50. Software metrics » Observations Software metrics » Usage Reduced complexity everywhere Decreased + increased stability
51. Software metrics » Observations Refactoring • Greatly reduced “monster class” • Split into multiple reusable pieces Software metrics » Usage
52. Questions? Software metrics » Usage
53. OBSERVATIONS Software metrics
54. Software metrics » Observations Spikes!
55. Complexity often caused by a few commits! Watch out with new features & rewrites. Software metrics » Observations Spikes!
56. Presentation title Software metrics » Observations
57. Software metrics » Observations No evolution
58. • No change over time • No change across projects Do developers have a “signature”? Software metrics » Observations No evolution
59. Software metrics » Observations Personalities? 2 guys working on same project: • One was very fast (but messier) • One was a lot more thorough Who’s who?
60. Software metrics » Observations Personalities?
61. Software metrics » Observations Personalities? M essy Thorough
62. Software metrics » Observations Personalities? Can metrics show personality traits? Please help me figure that out! https://www.cauditor.org/user/feedback
63. Presentation title
64. Questions? Software metrics
65. mullie.eu • mullie.eu/measuring-software-complexity • mullie.eu/measuring-software-coupling • cauditor.org/help/metrics Software metrics Resources