0
Empirically Based Evolution of a
Variability Management Approach
at UML Class Level
Anderson Marcolino, M.Sc.
State Univer...
2
Agenda
 Introduction
 Background
 SPL and Variability Management
 The Gomaa Method
 The SMarty Approach
 SMarty Ev...
3
Introduction
 Software Product Line (SPL) is a consolidated reuse technique,
in which several products share similar fe...
4
Introduction
 The SPL approach encompasses three main
activities:
 Domain Engineering
 Application Engineering
 Mana...
5
Introduction
 Four main concepts are taken into consideration
for VM:
 Variability, Variation Point and Variants
 PLU...
6
Objectives of this work
1. Comparing the effectiveness of SMarty and
PLUS with regard to the identification and
represen...
7
Background - PLUS
 The PLUS method
 It encompasses a variability management activity with regard to
use cases and clas...
8
Background - PLUS
 An example of the PLUS variability representation for
classes:
types
<<kernel>>
SortingElement
<<opt...
9
Background - SMarty
 Stereotype-based Management of Variability
(SMarty) approach
 It is composed of:
 an UML 2 profi...
10
Background - SMarty
 SMartyProfile comprises the following stereotypes, which
can be applied to UML models:
 <<variab...
11
Background - SMarty
 An example of the
SMarty variability
representation for
classes:
types
<<madatory>>
<<variationpo...
12
The Experimental Study
 Aim (Basili’s GQM template)
 Compare PLUS and SMarty, for the purpose of characterize
the mos...
13
The Experimental Study
 Planning
 Pilot Project
 Selection of Subjects
 Training
14
The Experimental Study
 Planning
 Hypotheses Formulation
 H0 : µ (effectiveness(X)) = µ (effectiveness(Y));
 H1 : µ...
15
The Experimental Study
 Planning
 Dependent Variables: the effectiveness calculated for each
variability management a...
16
The Experimental Study
 Planning
 Independent Variables:
 the variability management approach, a factor with
two tre...
17
The Experimental Study
Execution
 Instrumentation
 Participation Procedure
18
The Experimental Study
 Effectiveness of the Approaches
 Collected Data Normality Test: the Shapiro-Wilk normality te...
19
The Experimental Study
Box Plot of Effectiveness (Class)
Spreadsheet1 10v*12c
Median; Box: 25%-75%; Whisker: Non-Outlie...
20
The Experimental Study
 Effectiveness of the Approaches
 Mann-Whitney-Wilcoxon for SampleX and SampleY:
 Detailed ex...
21
The Experimental Study
 Threats to Validity
 Conclusion Validity
 Sample size is a major concern, which must be incr...
22
The Experimental Study
 Threats to Validity
 Internal Validity
 Differences among subjects – variations on skills we...
23
The Experimental Study
 Threats to Validity
 External Validity
 Instrumentation – failing to use real class models, ...
24
Empirical Evolution of SMarty
 Improvements for the SMarty approach based on the
feedback of the subjects:
 E-commerc...
25
Empirical Evolution of SMarty
 Improvements for the SMarty approach based on the
feedback of the subjects:
 Amount of...
26
Empirical Evolution of SMarty
 Based on such subjects feedback, the following
improvements were made:
 New guidelines...
27
Empirical Evolution of SMarty
 Based on such subjects feedback, the following
improvements were made:
 We realized th...
28
Revisiting objectives of this work…
1. Comparing the effectiveness of SMarty and PLUS with
regard to the identification...
29
Conclusion
 Industry needs that the scientific community tests existing and new
technologies, such as SMarty, identify...
30
Conclusion
 Shapiro-Wilk normality test was applied to both samples
 Mann-Whitney-Wilcoxon test analyzed the effectiv...
31
Future Works
 New experimental studies and replications must be planned and
conducted to make it possible to reduce th...
32
Acknowledgements
The authors would like to thank
CAPES (a Brazilian Funding Agency)
for supporting this work!!!
33
Questions? Contributions?
 If you prefer, contact me via e-mail:
 edson@din.uem.br
34
Tack! ! !
Thank you ! ! !
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Transcript of "COMPSAC 2014"

  1. 1. Empirically Based Evolution of a Variability Management Approach at UML Class Level Anderson Marcolino, M.Sc. State University of Maringá (DIN-UEM) – Brazil Edson OliveiraJr, Ph.D. edson@din.uem.br State University of Maringá (DIN-UEM) - Brazil Itana Gimenes, Ph.D. State University of Maringá (DIN-UEM) – Brazil Ellen Barbosa, Ph.D. University of São Paulo (ICMC-USP) – Brazil
  2. 2. 2 Agenda  Introduction  Background  SPL and Variability Management  The Gomaa Method  The SMarty Approach  SMarty Evolution based on Empirical Study  Conclusion and Future Works
  3. 3. 3 Introduction  Software Product Line (SPL) is a consolidated reuse technique, in which several products share similar features and variabilities  allowing mass customization for specific market needs  Variability represents how such products differ one another, thus  Variability Management (VM) is a key issue for the success of SPLs  Literature presents several well-known approaches for VM, especially object-oriented and UML-based.  However, their effectiveness was not experimentally analyzed, which can make technology transfer feasible
  4. 4. 4 Introduction  The SPL approach encompasses three main activities:  Domain Engineering  Application Engineering  Management (Organizational and Technical)  Variability management is one of the most important SPL management activities
  5. 5. 5 Introduction  Four main concepts are taken into consideration for VM:  Variability, Variation Point and Variants  PLUS and SMarty are two well-known approaches for VM in UML-based SPLs  However, PLUS has been taken as a basis for several UML- based SPL projects
  6. 6. 6 Objectives of this work 1. Comparing the effectiveness of SMarty and PLUS with regard to the identification and representation of variability in UML classes 2. Allowing the SMarty evolution in order to increase its effectiveness against PLUS
  7. 7. 7 Background - PLUS  The PLUS method  It encompasses a variability management activity with regard to use cases and classes, using stereotypes with no guidelines to apply them / Domain experts must use their knowledge for VM / Variant constraints are not available. Use Case? <<kernel>> Used to represent mandatory elements. Yes. <<optional>> Used to represent optional elements. It represents an element that can be selected or not in a specific product. Yes. <<alternative>> Used to represent alternative elements, mutually exclusive elements. Yes. Stereotype Description Does Use cases only!!! Use cases only!!!
  8. 8. 8 Background - PLUS  An example of the PLUS variability representation for classes: types <<kernel>> SortingElement <<optional>> NumericElement <<optional>> StringElement -sortingElements 1..*
  9. 9. 9 Background - SMarty  Stereotype-based Management of Variability (SMarty) approach  It is composed of:  an UML 2 profile, the SMartyProfile with stereotypes for VM in use case, class, component, sequence, and activity diagrams; and  a process, the SMartyProcess, with guidelines to support variability identification and representation
  10. 10. 10 Background - SMarty  SMartyProfile comprises the following stereotypes, which can be applied to UML models:  <<variability>> represents the concept of PL variability;  <<variant>> this abstract stereotype is specialized in four other non- abstract stereotypes which are: <<mandatory>>, <<optional>>, <<alternative_OR>>, and <<alternative_XOR>>;  <<mutex>> is a mutually exclusive relationship between two variants; and  <<requires>> is a relationship between two variants in which the selected variant requires the presence of another specific variant.
  11. 11. 11 Background - SMarty  An example of the SMarty variability representation for classes: types <<madatory>> <<variationpoint>> SortingElement <<alternative_OR>> NumericElement <<alternative_OR>> StringElement -sortingElements <<comment>> {allow sAddingVar = false, bindingTime = DESIGN_TIME, maxSelection = 2, minSelection = 1, name = "sorting element", variants = "NumericElement, StringElement"} 1..*
  12. 12. 12 The Experimental Study  Aim (Basili’s GQM template)  Compare PLUS and SMarty, for the purpose of characterize the most effectiveness, with respect to the capability of identification and representation of variabilities in Software Product Line class models, from the point of view of software product line architects, in the context of master and Ph.D. students of the Software Engineering area from the University of São Paulo (ICMC/USP) and Federal University of São Carlos (UFSCar).
  13. 13. 13 The Experimental Study  Planning  Pilot Project  Selection of Subjects  Training
  14. 14. 14 The Experimental Study  Planning  Hypotheses Formulation  H0 : µ (effectiveness(X)) = µ (effectiveness(Y));  H1 : µ (effectiveness(X)) < µ (effectiveness(Y)); and  H2 : µ (effectiveness(X)) > µ (effectiveness(Y)).  Where X = PLUS and Y = SMarty.
  15. 15. 15 The Experimental Study  Planning  Dependent Variables: the effectiveness calculated for each variability management approach (X and Y) as follows:
  16. 16. 16 The Experimental Study  Planning  Independent Variables:  the variability management approach, a factor with two treatments (X and Y); and  the SPL, a factor with two treatments (E-commerce and AGM SPLs).
  17. 17. 17 The Experimental Study Execution  Instrumentation  Participation Procedure
  18. 18. 18 The Experimental Study  Effectiveness of the Approaches  Collected Data Normality Test: the Shapiro-Wilk normality test was applied to the E-commerce and AGM samples providing the following results:  sample X was considered non-normal and sample Y was considered normal.
  19. 19. 19 The Experimental Study Box Plot of Effectiveness (Class) Spreadsheet1 10v*12c Median; Box: 25%-75%; Whisker: Non-Outlier Range Median 25%-75% Non-Outlier Range Outliers Extremes Effectiveness Y Approach. Effectiveness X Approach. -5 0 5 10 15 20 25 30
  20. 20. 20 The Experimental Study  Effectiveness of the Approaches  Mann-Whitney-Wilcoxon for SampleX and SampleY:  Detailed explanation on samples is in the paper  There is evidence that the X approach (PLUS) is more effective in identifying and representing variability in class models than the Y approach (SMarty)  This result corroborates to reject the null hypothesis (H0) of this study: PLUS is more effective than SMarty for SPLs class models and subjects taken into account.
  21. 21. 21 The Experimental Study  Threats to Validity  Conclusion Validity  Sample size is a major concern, which must be increased in prospective studies  Random capacity was not applied to subjects selection, thus generalization of results could not be inferred  Construct Validity  Independent variable variability modeling approach was guaranteed by the pilot project undertaken
  22. 22. 22 The Experimental Study  Threats to Validity  Internal Validity  Differences among subjects – variations on skills were reduced by performing training session and tasks in the same order  Fatigue effects – on average the experiment took 80 minutes, thus fatigue was not considered a problem for the study  Influence among subjects – could not be really controlled. They took the experiment under the supervision of a human observer.
  23. 23. 23 The Experimental Study  Threats to Validity  External Validity  Instrumentation – failing to use real class models, as the e-commerce and AGM are not commercial SPLs. More experiments must be carried out with real SPLs.  Subjects – we could take advantages of the benefits of taking into account students for performing experiments as pointed out by Carver et al. (2003)
  24. 24. 24 Empirical Evolution of SMarty  Improvements for the SMarty approach based on the feedback of the subjects:  E-commerce SPL  Subjects reported difficulties on the application of SMarty to the e- commerce SPL class model as it has no elements of class modeling, such as, inheritance, aggregation, and generalization  E- commerce was analyzed to improve SMarty  Training session  Subjects indicated that they need more time for training and application of SMarty
  25. 25. 25 Empirical Evolution of SMarty  Improvements for the SMarty approach based on the feedback of the subjects:  Amount of stereotypes  Subjects questioned the difference between PLUS and SMarty as the later has several more stereotypes  Arrangement of the SPL models:  E-commerce class models are mode complex than AGM  E-commerce models were the first models given to the subjects
  26. 26. 26 Empirical Evolution of SMarty  Based on such subjects feedback, the following improvements were made:  New guidelines were added to SMarty, encompassing the level of abstraction and elements of the e-commerce class models  CL2. Class models elements, related with associations in which their attributes have aggregationKind as none, or, do not represent aggregation or composition, suggest mandatory or optional variants.  CL2.1. For the identification of possible optional variants classes related through associations where the multiplicity in one of the ends of an association, to each object class found at the opposite end match * (zero or more) or 0..n where n is any integer different from zero; suggest an optional class
  27. 27. 27 Empirical Evolution of SMarty  Based on such subjects feedback, the following improvements were made:  We realized that with a few less stereotypes, PLUS is easier to apply. However, such an “easibility” might jeopardize the generation of specific products as we can observe ambiguity in PLUS class models
  28. 28. 28 Revisiting objectives of this work… 1. Comparing the effectiveness of SMarty and PLUS with regard to the identification and representation of variability in UML classes  PLUS is more effective 1. Allowing the SMarty evolution in order to increase its effectiveness against PLUS  New guidelines for class models  need a new experiment  Reduce stereotypes or avoid ambiguity during specific products generation?  New experiment is being carried out
  29. 29. 29 Conclusion  Industry needs that the scientific community tests existing and new technologies, such as SMarty, identifying their effectiveness to make technology transfer easier and reliable.  The experimental study presented in this paper demonstrates the ability to use variability management approaches. Their effectiveness were analyzed by modeling variability in class models of two SPLs.  Empirical based improvements could be made to SMarty in order to incorporate support for different class model elements by means of new guidelines
  30. 30. 30 Conclusion  Shapiro-Wilk normality test was applied to both samples  Mann-Whitney-Wilcoxon test analyzed the effectiveness of PLUS and SMarty  Obtained results provide evidence that the PLUS is more effective than SMarty for modeling variability in UML class models, taking into account the E-commerce and the AGM SPLs for this study.
  31. 31. 31 Future Works  New experimental studies and replications must be planned and conducted to make it possible to reduce the threats, increasing the effectiveness of SMarty towards generalizing the results.  As new experiments, we are:  planning a new experiment for characterize the improved version of SMarty effective against PLUS; and  planning an experiment to analyze the effectiveness of PLUS and SMarty and their impact on the generation of specific products.
  32. 32. 32 Acknowledgements The authors would like to thank CAPES (a Brazilian Funding Agency) for supporting this work!!!
  33. 33. 33 Questions? Contributions?  If you prefer, contact me via e-mail:  edson@din.uem.br
  34. 34. 34 Tack! ! ! Thank you ! ! !
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