Presentation at SCAM 2016 in Raleigh, USA

1. SATT: Tailoring Code Metric
Thresholds for Different
Software Architectures
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Maurício Aniche, Christoph Treude, Andy Zaidman, Arie van Deursen, Marco Gerosa
@mauricioaniche, @ctreude, @azaidman, @avandeursen, @gerosa_marco

2. Medical Exams
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3. SCAM 2016 3
Sugar level 150 [70,120]

4. SCAM 2016 4
Coupling 10 < 15
How to find
this number?

5. SCAM 2016 5
Benchmarking

6. 1. order by metric value
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7. 1. order by metric value
2. weight
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8. 1. order by metric value
2. weight
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LOC=100

9. 1. order by metric value
2. weight
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LOC=100 LOC=200

10. 1. order by metric value
2. weight
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100,000 LOC
LOC=100 LOC=200

11. 1. order by metric value
2. weight
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100,000 LOC
LOC=100
0.001%
LOC=200
3. weight aggregation

12. 1. order by metric value
2. weight
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100,000 LOC
LOC=100
0.001%
LOC=200
0.002%
3. weight aggregation

13. 1. order by metric value
2. weight
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100,000 LOC
LOC=100
0.001%
LOC=200
0.002%+0.001%
3. weight aggregation

14. 1. order by metric value
2. weight
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100,000 LOC
LOC=100
0.001%
LOC=200
0.003%
3. weight aggregation

15. 1. order by metric value
2. weight
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100,000 LOC
3. weight aggregation
0% 100%

16. 0% 10% 30% 70% 80% 90% 100%
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1. order by metric value
2. weight
3. weight aggregation

17. 4. extract thresholds from metric values where
aggregated weight is 70%, 80% and 90%
0% 10% 30% 70% 80% 90% 100%
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1. order by metric value
2. weight
3. weight aggregation

18. SCAM 2016 18

19. Benchmark
in Controllers
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20. Benchmark
in Controllers
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21. That’s not what
we want
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22. SCAM 2016 22
Quantiles
Coupling (CBO)

23. SATT for the rescue
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25. Controllers Other classes
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26. 1. order by metric value
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27. 1. order by metric value
only controllers
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28. 1. order by metric value
2. aggregate the weight
0% 10% 30% 70% 80% 90% 100%
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29. 1. order by metric value
2. aggregate the weight
3. extract thresholds from metric values where
aggregated weight is 70%, 80% and 90%
0% 10% 30% 70% 80% 90% 100%
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30. Our studySCAM 2016 30

31. projects’ sample
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32. CK
metrics
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33. RQ1. What differences in metric values
distributions does SATT find for common
architectural styles such as MVC?
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34. RQ2. Can the differences in distributions
thus found be explained from the
architectural constraints imposed on
classes fulfilling dedicated architectural
roles?
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35. RQ3. What impact do these differences
have on the use of thresholds for quality
assessments?
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36. Differences!
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37. RQ1. The approach indeed finds architectural roles
that present significantly higher (or lower) values
for certain metrics when compared to other classes.
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38. We talked to experts
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39. SCAM 2016 39
“Controllers are coupled to the framework while
Services are coupled to domain objects.”
“Entities contain getters and setters”

40. RQ2. Experts considered most of the differences in
metric values for architectural roles to be coherent.
Their key explanation is that architectural roles
have specific responsibilities.
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45. RQ3. The state-of-art approach tends to return
doubtful results for architectural roles that have
metric values distribution significantly different
from other classes. Our approach improves it by
using the architectural role’s metric values
distribution to define thresholds.
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46. Same for Android!
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47. SCAM 2016 + ICSME 2016 =
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48. • Benchmark-based assessment techniques do
not take the architectural role of a class into
consideration.
• SATT provides a specific threshold for an
architectural role when its metric values are
significantly different from other classes.
• The approach seems to provide better results
in these cases.
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49. SATT: Tailoring Code Metric
Thresholds for Different
Software Architectures
49
Maurício Aniche, Christoph Treude, Andy Zaidman, Arie van Deursen, Marco Gerosa
@mauricioaniche, @ctreude, @azaidman, @avandeursen, @gerosa_marco