1. Software Modularity: Paradoxes,
Principles, and Architectures
Andrzej Olszak
Jaroslav Tulach

2. Andrzej Olszak
• Ph.D. Research fellow @ SDU
• Creator of Featureous tool
• Fights cancer @ Dako

3. Jaroslav Tulach
• Founder and architect of NetBeans IDE and RCP
• API designer
• Speaker and author
http://paradoxes.apidesign.org

4. Agenda
1. Dividing into modules (Andrzej):
1. Architectures
2. Principles
2. Designing module APIs (Jaroslav):
1. Paradoxes
2. Principles

5. Motivation
Getting out of the monolithic cave

6. The starting point
A monolithic system
• No apparent logical parts
– Everything changes
together
– Difficult to control
complexity

7. The goal
A modular system
• Decomposed into logical
modules
• Modules partial:
– Comprehension
– Change

8. The tool
A module system
• Wraps logical modules into
physical modules
– a.k.a. advanced JARs
– Enforce code isolation

9. A possible result
• Module system ⇏
Modular code
– It all depends on how you design
the modules

10. Part I
Architectures

11. A running example
• Let’s assume that this is our system
– 3 layers of code that provide 3 features to the users
“UI”
“Logic”
“Domain Model”
• This is the essence of your architecture if you use:
– MVC, MVP, Onion arch, Hexagonal arch, …

12. Modularizing layers
• There are at lease three options:
View
Controller
Model

13. Modularizing layers
• There are at lease three options:
View
Controller
Model
View
feature2
feature1
feature3
App Controller
Model

14. Choosing ‘best’ modularization
• Modularity is relative to change
– Modularization quality depends on the future changes [Parn’72]
• Let’s consider two change scenarios:
View
feature2
feature1
feature3
Controller
Model

15. Choosing ‘best’ modularization
• Modularity is relative to change
– Modularization quality depends on the future changes [Parn’72]
• Let’s consider two change scenarios:
1. Modify user functionality
View
feature2
feature1
feature3
Controller
Model

16. Choosing ‘best’ modularization
• Modularity is relative to change
– Modularization quality depends on the future changes [Parn’72]
• Let’s consider two change scenarios:
1. Modify user functionality
View
feature2
feature1
feature3
Controller
Model

17. Choosing ‘best’ modularization
• Modularity is relative to change
– Modularization quality depends on the future changes [Parn’72]
• Let’s consider two change scenarios:
1. Modify user functionality
View
feature2
feature1
feature3
Controller
Model

18. Choosing ‘best’ modularization
• Modularity is relative to change
– Modularization quality depends on the future changes [Parn’72]
• Let’s consider two change scenarios:
1. Modify user functionality
View
feature2
feature1
feature3
Controller
Model

19. Choosing ‘best’ modularization
• Modularity is relative to change
– Modularization quality depends on the future changes [Parn’72]
• Let’s consider two change scenarios:
1. Modify user functionality
View
feature2
feature1
feature3
Controller
Model

20. Choosing ‘best’ modularization
• Modularity is relative to change
– Modularization quality depends on the future changes [Parn’72]
• Let’s consider two change scenarios:
1. Modify user functionality 2. Migrate UI to JavaFX
View
feature2
feature1
feature3
Controller
Model

21. Choosing ‘best’ modularization
• Modularity is relative to change
– Modularization quality depends on the future changes [Parn’72]
• Let’s consider two change scenarios:
1. Modify user functionality 2. Migrate UI to JavaFX
View
feature2
feature1
feature3
Controller
Model

22. Choosing ‘best’ modularization
• Modularity is relative to change
– Modularization quality depends on the future changes [Parn’72]
• Let’s consider two change scenarios:
1. Modify user functionality 2. Migrate UI to JavaFX
View
feature2
feature1
feature3
Controller
Model

23. Choosing ‘best’ modularization
• Modularity is relative to change
– Modularization quality depends on the future changes [Parn’72]
• Let’s consider two change scenarios:
1. Modify user functionality 2. Migrate UI to JavaFX
View
feature2
feature1
No silver-bullet modularization
feature3
Controller
Model

24. Anticipating future changes

25. Anticipating future changes
Feature-oriented
evolutionary changes
75%
Other evolutionary changes
25%
Software costs in organizations [Moad’90, Nose’90, Erli’00]

26. Anticipating future changes
Feature-oriented
evolutionary changes
75%
Evolution &
maintenance
60-90%
Other evolutionary changes Initial development
25% 10-40%
Software costs in organizations [Moad’90, Nose’90, Erli’00]

27. Modularization in practice:
the case of NDVis
View
• Neurological analysis tool by VisiTrend
– Monolithic -> NetBeans MS Controller
– Improve functional customizability Model
– Improve reusability of core algorithms
Feature-oriented
restructuring
• Starting point
– 10 KLOC, 27 use cases
feature2
feature3
feature1
– Unfamiliar source code
– Complex and unfamiliar domain

28. Modularizing features with Featureous tool

29. Modularizing features with Featureous tool
1. Feature location
(a.k.a. traceability)

30. Modularizing features with Featureous tool
1. Feature location 2. Feature-oriented
(a.k.a. traceability) analysis

31. Modularizing features with Featureous tool
1. Feature location 2. Feature-oriented
(a.k.a. traceability) analysis
3. Iterative
Restructuring
4. Module APIs

32. Modularization @ 35 man-hours
• Explicit and pluggable features
• Reusable core

33. Part II
Principles

34. Separation of Concerns
• “To study an aspect of a subject matter in isolation”
[Dijk’74]
• Software consists of “concerns”
– Features
– Persistence
– Security
– Caching
...
• Refined by AspectJ [Kicz’96] and Hyper/J [Tarr’99]
– Multiple dimensions of concern – one dominant
– Scattering & Tangling

35. Reducing Scattering & Tangling
• Low Scattering
– “a concern implemented by few modules“
– reduces change scope and delocalization [Leto’86]
View
Controller
feature 1
scattering Model

36. Scattering & Tangling
• Low Scattering
– “a concern implemented by few modules“
– reduces change scope and delocalization [Leto’86]
• Low Tangling
– "modules dedicated to a single concerns“
– reduces change propagation and interleaving [Ruga’95]
tangling
feature 2 View
Controller
feature 1
scattering Model

37. A real-world metaphor

38. A real-world metaphor
http://xkcd.com/657/

39. Mapping SoC to other principles
SEPARATION OF CONCERNS

40. Mapping SoC to other principles
SEPARATION OF CONCERNS
LOW SCATTERING LOW TANGLING

41. Mapping SoC to other principles
SEPARATION OF CONCERNS
LOW SCATTERING LOW TANGLING
Information hiding
[Parn’72]
Low coupling
[Stev’74]
DRY
[Hunt’99]

42. Mapping SoC to other principles
SEPARATION OF CONCERNS
LOW SCATTERING LOW TANGLING
Information hiding Single responsibility
[Parn’72] [Mart’02]
Low coupling High cohesion
[Stev’74] [Stev’74]
DRY Common closure
[Hunt’99] [Mart’02]

43. Measuring SoC
• Concern location + concern-oriented metrics
– Trialed at Motorola [Simm’06]
• Static analysis + Cohesion and Coupling
– Issues: coupling vs. DRY, “uncohesive” java.util
• Repository mining for change-sets:
classes
http://swerl.tudelft.nl/bin/view/Main/TestHistory

44. Summary
• Module system is a tool, not the goal
• No “silver-bullet” modularization
• Restructuring layers into features is viable
• SoC – the root of all principles

45. References
[Parn’72] Parnas, D.L. (1972). On the criteria to be used in decomposing systems into modules. Communications of the
ACM, 15(12).
[Moad’90] Moad, J. (1990). "Maintaining the competitive edge". Datamation 61-62, 64, 66.
[Erli’00] Erlikh, L. (2000). "Leveraging legacy system dollars for E-business". (IEEE) IT Pro, May/June 2000.
[Nose’90] Nosek, J. & Palvia, P. (1990). "Software maintenance management: changes in the last decade". Journal of
Software Maintenance: Research and Practice 2 (3).
[Mart’11] Martin, R.C. (2011). http://blog.8thlight.com/uncle-bob/2011/09/30/Screaming-Architecture.html
[Dijk’74 ] Dijkstra, E. W. (1974). On the role of scientific thought. Selected Writings on Computing: A Personal Perspective.
[Kicz’96] Kiczales, G., Irwin, J., Lamping, J., Loingtier, J., M., Lopes, C., V., Maeda, C. and Mendhekar, A. (1996). Aspect-
oriented programming. ACM Computing Surveys, vol. 28.
[Tarr’99] Tarr, P., Ossher, H., Harrison, W. and Sutton, S. M. (1999). N degrees of separation: multi-dimensional
separation of concerns. In ICSE’99: Proceedings of the 21st international conference on Software engineering.
[Leto’86] Letovsky, S. and Soloway, E. (1986). Delocalized Plans and Program Comprehension. IEEE Software, 3(3).
[Ruga’95] Rugaber, S., Stirewalt, K. and Wills, L. M. (1995). The interleaving problem in program understanding. In
WCRE’95: Proceedings of the 2nd Working Conference on Reverse Engineering.
[Simm’06] Simmons, S., Edwards, D., Wilde, N., Homan, J. and Groble, M. (2006). Industrial tools for the feature location
problem: an exploratory study. Journal of Software Maintenance and Evolution Research and Practice, 18(6).
[Mart’02] Martin, R. C. (2002). Agile Software Development, Principles, Patterns, and Practices. Prentice Hall.
[Stev’74] Stevens, W. P., Myers, G. J. and Constantine, L. L. (1974). Structured Design. (E. Yourdon, Ed.)IBM Systems
Journal, 13(2).
[Hunt’99] Hunt, A., & Thomas, D. (1999). The Pragmatic Programmer: From Journeyman to Master. Addison-Wesley
Professional.
(Many of these papers are available online through Google Scholar, Citeseerx and the authors’ websites)

46. Feature tracer [backup]

48. Part III
Paradoxes of API Design

49. Modularity is relative to change
• API are like stars (paradox 19)
• Designing a universe
• Distributed development (paradox 2)
• Can't know all your users
• Envisioning them via use-cases
• Sustaining (paradox 3)
• One try to get API right

50. How to anticipate future changes?
• Client vs. Provider APIs (paradox 9)
• Open spaces
• Fixed points
• Stable API evolves
• Backward compatibility (paradox 6)
• Beware of API-less APIs (paradox 8)
• Mediawiki experience
• Loyal customer

51. Logical vs. Physical Design
• Design oriented on class relationship
• UML, specifications
• Packaging into JARs ignored (paradox 17)
• Influences deployment (paradox 7)
• Defines APIs
• Good common ground (paradox 11)
• Improves your design

52. A „weight“ of a module
• Environment for a module
• Modules don't live in vacuum
• Expressed by dependencies (paradox 17)
• Weight
• Number & scope of outgoing dependencies
• Less is more (paradox 19)
• Single responsibility principle

53. Use vs. Re-use
• Kirk Knoernchild
• Monolithic API is easier to use
• Modular API is easier to re-use
• Blackbox pattern (paradox 18)
• OSGi Capabilities
• Good tooling
• Wizards

54. SOLID APIs
• Single responsibility principle
• Meaning of modifiers (paradox 15)
• Client vs. provider APIs (paradox 9)
• Lightweight API modules
• Open/closed principle
• OK for provider APIs
• Disastrous for client APIs
• Proliferation of instanceof in user code
• Alternative behavior (paradox 16)

55. SOLID APIs II
• Liskov substitution principle
• AWT Frame extends Component!
• Don't expose deep hierarchies
• Use delegation rather than inheritance
• Client API should be in final classes
• 1:N factory methods

56. SOLID APIs III
• Interface segregation principle
• Lookup & discover
• OSGi declarative services
• Dependency inversion principle
• Code against interfaces, not implementations
• Does not imply classes are bad (paradox 9)
• Don't fear (injectable) singletons (paradox 14)

57. API in User Eyes
• Clueless users (paradox 1)
• Have always something else to do
• Evaluation of an API (paradox 4)
• Coolness
• Time to market
• Total cost of ownership

58. Collaboration
• Maintenance (paradox 10)
• Rely on patches
• Accepting unacceptable (paradox 13)
• Beauty (paradox 5)
• One writer and dozens of users
• Sacrifice the writer

59. Summary
• http://paradoxes.apidesign.org