1. Constraint Solver for Product Lines
Project 1 Presentation
Jianfeng Chen
jchen37@ncsu.edu
April 9, 2015
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 1 / 18

2. Software features
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 2 / 18

3. Software features
Software engineering is becoming more and more complex.
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 2 / 18

4. Software features
Software engineering is becoming more and more complex.
More and more features.
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 2 / 18

5. Software features
Software engineering is becoming more and more complex.
More and more features.
C2C online trading system: database, commercial data encryption, mil-
lisecond(microsecond) response, customable GUI, chatting module, email
connection, etc.
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 2 / 18

6. Software features
Software engineering is becoming more and more complex.
More and more features.
C2C online trading system: database, commercial data encryption, mil-
lisecond(microsecond) response, customable GUI, chatting module, email
connection, etc.
An operating system have thousands of modules and features.
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 2 / 18

7. Software features
Software engineering is becoming more and more complex.
More and more features.
C2C online trading system: database, commercial data encryption, mil-
lisecond(microsecond) response, customable GUI, chatting module, email
connection, etc.
An operating system have thousands of modules and features.
Among them, which features should be implemented?
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 2 / 18

8. Feature model
Feature tree:
http://www.digplanet.com/wiki/Feature_model
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 3 / 18

9. Feature model
Feature tree:
http://www.digplanet.com/wiki/Feature_model
Many features are related to others.
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 3 / 18

10. Feature model
Feature tree:
http://www.digplanet.com/wiki/Feature_model
Many features are related to others.
Cross-tree constraints complex the problem.
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 3 / 18

11. Feature model
Feature tree:
http://www.digplanet.com/wiki/Feature_model
Many features are related to others.
Cross-tree constraints complex the problem.
Cross-tree constraints are widespread in the software products.
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 3 / 18

12. Feature model
Feature tree:
http://www.digplanet.com/wiki/Feature_model
Many features are related to others.
Cross-tree constraints complex the problem.
Cross-tree constraints are widespread in the software products.
Ex. more than three fourths features in eCos(an open source real-time oper-
ating system) are referred by some constraints.
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 3 / 18

13. Feature model
SPLOT
open repository
more than 600 feature models
SXFM language; parser is available
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 4 / 18

14. Goals
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 5 / 18

15. Goals
INPUT:
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 5 / 18

16. Goals
INPUT:
feature model(including constraints)
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 5 / 18

17. Goals
INPUT:
feature model(including constraints)
some important feature attributes:
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 5 / 18

18. Goals
INPUT:
feature model(including constraints)
some important feature attributes:
cost
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 5 / 18

19. Goals
INPUT:
feature model(including constraints)
some important feature attributes:
cost
familiarity(used before?)
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 5 / 18

20. Goals
INPUT:
feature model(including constraints)
some important feature attributes:
cost
familiarity(used before?)
defects
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 5 / 18

21. Goals
INPUT:
feature model(including constraints)
some important feature attributes:
cost
familiarity(used before?)
defects
OUTPUT: configurations (select which features?)
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 5 / 18

22. Goals
INPUT:
feature model(including constraints)
some important feature attributes:
cost
familiarity(used before?)
defects
OUTPUT: configurations (select which features?)
GOALS:
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 5 / 18

23. Goals
INPUT:
feature model(including constraints)
some important feature attributes:
cost
familiarity(used before?)
defects
OUTPUT: configurations (select which features?)
GOALS:
⇓ constraint violations
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 5 / 18

24. Goals
INPUT:
feature model(including constraints)
some important feature attributes:
cost
familiarity(used before?)
defects
OUTPUT: configurations (select which features?)
GOALS:
⇓ constraint violations
⇑ feature richness
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 5 / 18

25. Goals
INPUT:
feature model(including constraints)
some important feature attributes:
cost
familiarity(used before?)
defects
OUTPUT: configurations (select which features?)
GOALS:
⇓ constraint violations
⇑ feature richness
⇑ used features
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 5 / 18

26. Goals
INPUT:
feature model(including constraints)
some important feature attributes:
cost
familiarity(used before?)
defects
OUTPUT: configurations (select which features?)
GOALS:
⇓ constraint violations
⇑ feature richness
⇑ used features
⇓ defects
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 5 / 18

27. Goals
INPUT:
feature model(including constraints)
some important feature attributes:
cost
familiarity(used before?)
defects
OUTPUT: configurations (select which features?)
GOALS:
⇓ constraint violations
⇑ feature richness
⇑ used features
⇓ defects
⇓ total cost
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 5 / 18

28. Genetic algorithms
http://www.abrandao.com/2015/01/21/simple-php-genetic-algorithm/
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 6 / 18

29. Domination
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 7 / 18

30. Domination
Reverse the uprise objectives ⇒ all objectives are the less the better.
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 7 / 18

31. Domination
Reverse the uprise objectives ⇒ all objectives are the less the better.
A 3 7 4 2 7
B 4 7 6 2 7
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 7 / 18

32. Domination
Reverse the uprise objectives ⇒ all objectives are the less the better.
A 3 7 4 2 7
B 4 7 6 2 7
A dominates B
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 7 / 18

33. Domination
Reverse the uprise objectives ⇒ all objectives are the less the better.
A 3 7 4 2 7
B 4 7 6 2 7
A dominates B
A 4 7 6 2 7
B 4 4 6 1 5
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 7 / 18

34. Domination
Reverse the uprise objectives ⇒ all objectives are the less the better.
A 3 7 4 2 7
B 4 7 6 2 7
A dominates B
A 4 7 6 2 7
B 4 4 6 1 5
B dominates A
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 7 / 18

35. Domination
Reverse the uprise objectives ⇒ all objectives are the less the better.
A 3 7 4 2 7
B 4 7 6 2 7
A dominates B
A 4 7 6 2 7
B 4 4 6 1 5
B dominates A
A 3 7 4 2 7
B 4 4 6 1 7
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 7 / 18

36. Domination
Reverse the uprise objectives ⇒ all objectives are the less the better.
A 3 7 4 2 7
B 4 7 6 2 7
A dominates B
A 4 7 6 2 7
B 4 4 6 1 5
B dominates A
A 3 7 4 2 7
B 4 4 6 1 7
A is indifferent from B
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 7 / 18

37. Method 1: Differential Evolution
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 8 / 18

38. Method 1: Differential Evolution
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 8 / 18

39. Method 1: Differential Evolution
continuous: new = A + F ∗ (B − C)
binary: for each bit, new = A|B|C basing on some lottery.
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 8 / 18

40. Method 1: Differential Evolution
What if indifferent?
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 9 / 18

41. Method 1: Differential Evolution
What if indifferent?
add to the population pool!
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 9 / 18

42. Method 1: Differential Evolution
What if indifferent?
add to the population pool!
How to prune?
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 9 / 18

43. Method 1: Differential Evolution
What if indifferent?
add to the population pool!
How to prune?
[Deb, Kalyanmoy, et al. 2002]
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 9 / 18

44. Method 2: Indicator-based search
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 10 / 18

45. Method 2: Indicator-based search
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 10 / 18

46. Method 2: Indicator-based search
Binary quality indicator
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 10 / 18

47. Method 2: Indicator-based search
Binary quality indicator
Fitness F(x) = i∈Px −e−I(i,x)/κ
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 10 / 18

48. Method 2: Indicator-based search
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 11 / 18

49. Method 2: Indicator-based search
Initialization
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 11 / 18

50. Method 2: Indicator-based search
Initialization
Get fitness
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 11 / 18

51. Method 2: Indicator-based search
Initialization
Get fitness
Eliminate the individuals with smallest fitness
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 11 / 18

52. Method 2: Indicator-based search
Initialization
Get fitness
Eliminate the individuals with smallest fitness
Mating selection
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 11 / 18

53. Method 2: Indicator-based search
Initialization
Get fitness
Eliminate the individuals with smallest fitness
Mating selection
Variation
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 11 / 18

54. Method 2: Indicator-based search
Initialization
Get fitness
Eliminate the individuals with smallest fitness
Mating selection
Variation
Terminate or back to second step
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 11 / 18

55. Results
FM test (medium size)
166 features
112 leaves
46 cross-tree constraints
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 12 / 18

56. Results
IBEA.FM.
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 13 / 18

57. Results
DE vs IBEA.FM.
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 14 / 18

58. Results
DE vs IBEA.FM.
Figure: Features NOT provided
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 14 / 18

59. Results
DE vs IBEA.FM.
Figure: Defects
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 15 / 18

60. Further discussion
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 16 / 18

61. Further discussion
Stopping criterion
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 16 / 18

62. Further discussion
Stopping criterion
improvement/deterioration accumulation
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 16 / 18

63. Further discussion
Stopping criterion
improvement/deterioration accumulation
customable weight
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 16 / 18

64. Further discussion
Stopping criterion
improvement/deterioration accumulation
customable weight
Running time
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 16 / 18

65. Further discussion
Stopping criterion
improvement/deterioration accumulation
customable weight
Running time
DE-FM-500 gens-54s
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 16 / 18

66. Further discussion
Stopping criterion
improvement/deterioration accumulation
customable weight
Running time
DE-FM-500 gens-54s
IBEA-FM-500 gens-83s
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 16 / 18

67. Further discussion
Stopping criterion
improvement/deterioration accumulation
customable weight
Running time
DE-FM-500 gens-54s
IBEA-FM-500 gens-83s
In average, IBEA = 1.3*DE
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 16 / 18

68. Further discussion
Stopping criterion
improvement/deterioration accumulation
customable weight
Running time
DE-FM-500 gens-54s
IBEA-FM-500 gens-83s
In average, IBEA = 1.3*DE
Front Quality
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 16 / 18

69. Further discussion
Stopping criterion
improvement/deterioration accumulation
customable weight
Running time
DE-FM-500 gens-54s
IBEA-FM-500 gens-83s
In average, IBEA = 1.3*DE
Front Quality
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 16 / 18

70. Future work
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 17 / 18

71. Future work
pruning in differential evolution (flocking behaviors)
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 17 / 18

72. Future work
pruning in differential evolution (flocking behaviors)
mutate with reservations
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 17 / 18

73. Future work
pruning in differential evolution (flocking behaviors)
mutate with reservations
reconstruct the feature tree (reduce the search space)
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 17 / 18

74. Future work
pruning in differential evolution (flocking behaviors)
mutate with reservations
reconstruct the feature tree (reduce the search space)
chaff algorithm
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 17 / 18

75. Future work
pruning in differential evolution (flocking behaviors)
mutate with reservations
reconstruct the feature tree (reduce the search space)
chaff algorithm
Satz/Z3
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 17 / 18

76. Thank you!
Jianfeng Chen (jchen37@ncsu.edu) Constraint Solver for Product Lines April 9, 2015 18 / 18