“What should I work on next?” Code metrics can help you answer that question. They can single out sections of your code that are likely to contain bugs. They can help you get a toehold on a legacy system that’s poorly covered by tests.

1. Your Own Metric System
Ian Dees ·@undees
OSCON 2012

3. pragprog.com/titles/dhwcr

5. Setting

6. The forces against us
❥ Entropy drags our code down
❥ Apathy drags us down

7. Stay engaged and productive

8. Knowing our code
can help us do our jobs
and have more fun

9. Risk #1
Missing or poor information
can waste our time
or lead us to cause harm

10. Two steps forward
1. Ask questions about your code
2. Choose metrics that answer those questions

11. Purpose of metrics

12. purpose of metrics
Help you answer a question

13. purpose of metrics
What mess should I
clean up next?

14. purpose of metrics
The product backlog
isn’t a substitute
for your brain

15. Risk #2
Making structural changes
can introduce new bugs
(or expose existing ones)

16. purpose of metrics
Where are the bugs
(likely to be)?

17. purpose of metrics
/**
* REMOVE THIS CODE
* BEFORE WE SHIP!
*/

18. purpose of metrics
Have we forgotten anything
for this release?

19. purpose of metrics
These questions are for us

20. purpose of metrics
Not for someone else

21. purpose of metrics
Questions from others:
(outside the scope of our metrics)

22. purpose of metrics
Should we hold the release?

23. purpose of metrics
errors/KLOC →
time →

24. purpose of metrics
Who’s got the best
KLOC or error rate?

25. purpose of metrics
It was time to fill out the management form for
the first time. When he got to the lines of code
part, he thought about it for a second, and then
wrote in the number: -2000.
After a couple more weeks, they stopped asking
Bill to fill out the form, and he gladly complied.
—folklore.org

26. purpose of metrics
Have we met our target
complexity or coverage?

28. purpose of metrics
Metrics serve you,
not the other way around

29. purpose of metrics
Keep the job fun

30. purpose of metrics
More fun than
actually working?

31. Risk #3
There is a trap here for the
distractible

32. Common metrics

33. common metrics
Languages
❥ C:
a case study
❥ Perl:
the beginner’s experience
❥ <your lang>
just ask!

34. common metrics
Repo for this talk
github.com/undees/oscon

35. common metrics
Cyclomatic complexity

36. common metrics
E – N + 2P

37. common metrics
1. Start with a score of 1
2. Add 1 for each if, case, for, or
boolean condition

38. Volume speaking_volume(
bool correct_room,
bool correct_time) {
if (correct_room && correct_time) {
return INTELLIGIBLE;
} else {
// rehearsing
return INAUDIBLE;
}
}
complexity: 1

39. Volume speaking_volume(
bool correct_room,
bool correct_time) {
if (correct_room && correct_time) {
return INTELLIGIBLE;
} else {
// rehearsing
return INAUDIBLE;
}
}
complexity: 2

40. Volume speaking_volume(
bool correct_room,
bool correct_time) {
if (correct_room && correct_time) {
return INTELLIGIBLE;
} else {
// rehearsing
return INAUDIBLE;
}
}
complexity: 3

41. common metrics
pmccabe
parisc-linux.org/~bame/pmccabe

42. $ pmccabe *.c | sort -nr | head -10
3 3 3 6 8!oscon.c(6): speaking_volume
1 1 2 16 5!oscon.c(16): main

43. common metrics
Perl::Metrics::Simple

44. sub speaking_volume {
my $correct_room = shift;
my $correct_time = shift;
if ($correct_room && $correct_time) {
return 'intelligible';
} else {
# rehearsing
return 'inaudible';
}
}

45. $ countperl lib
...
Tab-delimited list of subroutines, with most complex at top
-----------------------------------------------------------
complexity sub path size
4 speaking_volume lib/OSCON.pm 9
...

47. $ wc -l oscon.c

48. Risk #4
Blindly reducing one number
can add complexity and bugs

49. common metrics
Test coverage

50. common metrics
1. Instrument your program
2. Watch your tests run
3. Report which lines get executed

51. common metrics
Addresses
“epic confidence” fail
opensourcebridge.org/sessions/923

52. common metrics
Testable code is more...
testable

53. common metrics
gcov

54. int main() {
assert(speaking_volume(true, true) == INTELLIGIBLE);
return 0;
}

55. $ gcc -fprofile-arcs
-ftest-coverage
-c oscon.c
$ gcc -fprofile-arcs
oscon.o

56. $ gcov oscon.c
$ cat oscon.c.gcov

57. 1: 6:Volume speaking_volume(bool correct_room, bool correct_time) {
1: 7: if (correct_room && correct_time) {
1: 8: return INTELLIGIBLE;
-: 9: } else {
-: 10: // rehearsing
####: 11: return INAUDIBLE;
-: 12: }
-: 13:}

58. common metrics
Devel::Cover

59. $ cover -test
$ cat cover_db/coverage.html

61. Risk #5
High code coverage
can make you think
your code is good

62. Custom metrics

63. X-rated-ness

64. custom metrics
Carlin’s 7 Dirty Words
1. 5.
2. 6.
3. 7.
4.

65. custom metrics
Our 7 Dirty Words
1.XXX 5.HACK
2.TODO 6.#if 0
3.FIXME 7.#ifndef TESTING
4.TBD

66. custom metrics
Our 7 Dirty Words
1. 5.
2. 6.
3. 7.
4.

67. $ ack -cl 'XXX|TODO|FIXME'
oscon.c:1

68. custom metrics
Test::Fixme

69. use Test::Fixme;
run_tests(where => 'lib',
match => qr/XXX|TODO|FIXME/);

70. $ make test
...
t/test-fixme.t .. 1/1
# Failed test ''lib/OSCON.pm''
# at t/test-fixme.t line 2.
# File: 'lib/OSCON.pm'
# 34 # XXX:remove the temp limit before we deploy
# Looks like you failed 1 test of 1.
t/test-fixme.t .. Dubious, test returned 1 (wstat 256, 0x100)
Failed 1/1 subtests

71. custom metrics
Churn

72. custom metrics
Recently changed code
may have new bugs

73. custom metrics
Frequently-changed code
may have problems

74. git log --pretty=oneline
--since=2012-05-04
oscon.c | wc -l

75. custom metrics
Missing documentation

76. custom metrics
Errors by time of day

77. custom metrics
Play by Play: Zed Shaw
peepcode.com/products/play-by-play-zed-shaw

78. What do we get
from all this?

79. Found a real
dependency problem
with pmccabe

80. Found dead code with gcov

81. Did a quick churn check
at manual test time

82. Found places we can
DRY up the code

83. Relative, not absolute!

84. Content-Type:
multipart/wish

85. ❥ Find the answers you need
❥ Look like heroes
❥ Have fun

86. Fin

87. Credits
flickr.com/photos/aussiegall/286709039
flickr.com/photos/bensutherland/252230820