Address tha gaps when using Goals and SysML to support self-adaptive SCPSs

1. Self-Adaptation
Driven by Goals in
SysML Models
Amal Ahmed Anda
Aanda027@uottawa.ca
April 20, 2018

2. Introduction
Hardware
Cyber
2
Socio-Cyber-Physical Systems
Cyber-Physical
Systems
Smart
Contracts
Intelligent
Transportation
System (ITS)
Air traffic
control
systems
Adaptive
SOS

3. • Modeling people preferences and concerns, in addition
to software and hardware elements
• Managing uncertainty and emergent properties
• Adapting to changes in requirements or the surrounding
environment
• Managing complexity
• Managing traceability (for consistency, completeness,
change management, impact analysis and trade-off analysis)
3
Socio-Cyber-Physical Systems challenges:
Introduction

4. Motivation
• Manage a comprehensive traceability between:
• Reduce uncertainty early at design
• Support adaptive behavior
by considering users’ concerns while
p.4
Socio-Cyber-Physical Systems requirements need to:
Goals, Requirements, Design Code
and
Designing, Implementing, Executing the systems
and
These activities are not supported by Traditional
Requirements Engineering (RE)

5. Motivation
• Lace and Kirikova, 2018 provided a high-level activities
of the needed modifications.
• Upcoming (SysML 2.0,2019) requested for proposal to
include goals and evaluation in its requirements
diagram.
“Proposals for SysML v2 shall include a capability to represent
goals, objectives, and evaluation criteria.”
p.5
Lace, K., & Kirikova, M. (2018). Required Changes in Requirements Engineering Approaches for Socio-Cyber-
Physical Systems.
Adapting the RE activities to model SCPSs has already addressed

6. Background
User Requirements Notation
6
G
R
L
UCM
intentional elements
+ actors + links
+ indicators + strategies
responsibilities
+ causality
+ components
+ scenarios
FM*
features
+ variability
ITU-T, Recommendation Z.151 (10/12): User Requirements Notation (URN) - Language Definition, Geneva, Switzerland, 2012

7. 7
On Goal-oriented Modeling
• For systems with socio-technical aspects
• Languages such as i* and GRL define concepts for
goals, actors, relationships (and indicators)
• Traceability between requirements and stakeholder
objectives
• Tradeoff analysis and holistic decision making
• Support for adaptive behavior
Background

8. 8
Background
GRL model of hybrid car system

9. Background
9
New
Modified
SysML and UML Models

10. 10
• For systems, often with hardware, software, and
personnel
– Cyber-physical systems (CPS)
– Systems of systems (SoS)
• SysML defines model elements for problems, rationales,
stakeholders, and requirements (but with little
semantics)
• Named requirement with user-defined attributes
• Requirements can be linked for traceability and analysis
• Predefined relationships (containment, verification…)
Background
On SysML

11. 11
Background
SysML requirements diagram of hybrid car system

12. 12
Adaptation activities at runtime MAPE Cycle
Adaptation strategies
Monitor
Analyze Plan
Environment
System
Decide to
adapt
Select the best
Execution
Strategy
Sensors
Nothing
wrong
Symptoms
Monitor
results
Data
Background

13. The Proposed Approach
p.13
Social concerns
System design
Textual
requirements
Implementation

14. Vision
14
We envision substantially improved
requirements engineering activities
exploiting SysML modeling
through the integration of goal modeling
and analysis,
with a particular focus on SCPS context

15. 15

16. Literature Review
16
Search 1: Goals &
SysML  361
Search 2: SysML &
Adaptation  307
Experts & forward refs:
Goals & adaptation
12+2
• Scopus
• IEEE Xplore
• ACM DL
• Web of Science
• Google Scholar
Inclusion & exclusion
criteria
+
Data set includes
49 papers
DBs
Inclusion & exclusion
criteria
Inclusion & exclusion
criteria
29 papers 11 papers
9 papers

17. Results and Discussion
• The existing integrations with SysML
– Using requirements (leads by goal-oriented
technique)
– Using part of the goal model
– Using goal model
• The existing supports for runtime adaptation
– Static decision using If event Then action (Action
policy)
– Dynamic decision using equations (utility and goal
policies)
17
The results were classified into two groups:

18. 18
Existing Integrations With SysML Model
L. Apvrille and Y. Roudier, “SysML-Sec: A SysML environment for the design and development of secure embedded systems,”
APCOSEC, Asia-Pacific Counc. Syst. Eng., pp. 8–11, 2013.
Extending requirements diagrams to include security NFRs

19. Existing Integrations With SysML Model
19
Parametric diagram for tradeoff analysis of a microgrid system
D. Spyropoulos and J. S. Baras, “Extending Design Capabilities of SysML with Trade-off Analysis: Electrical Microgrid Case Study,”
Procedia Comput. Sci., vol. 16, pp. 108–117, 2013.

20. Existing Integrations With SysML Model
20
Goal model mapped to SysML requirements diagram
Ahmad, M., & Bruel, J.(2014) A comparative study of RELAX and SysML/Kaos. In Technical Report. Institut de Recherche en
Informatique de Toulouse, University Toulouse II Le Mirail, France.

21. 21
X. Cui and R. Paige, “An integrated framework for system/software requirements development aligning with business motivations,” in
Proceedings - 2012 IEEE/ACIS 11th International Conference on Computer and Information Science, ICIS 2012, 2012, pp. 547–552.
Business motivations mapped to SysML requirements diagram
Existing Integration With SysML Model

22. 22
Method C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11
Apvrille and Roudier
(2013)
N P P N P N N N N N N
Spyropoulos and Baras
(2013)
P P P N P P N N N N W
Ahmad et al. (2015) Y Y P N Y N N N N P W
Cui and Paige (2012) Y Y P N Y N N N N N N
C1:Communication between Goals and SysML
C2:Consistency and completeness
C3:Traceability (goal, req., design and code.)
C4:Scalability
C5:Change management
C6:Trade-off analysis and solutions
C7:Concurrent modeling
C8:Usability: Number of tools and
model import and export
C9:Ease of integration
C10:Goal reasoning and adaptation
C11:Adaptation type
Assessment
Y=Yes, N=No, P=Partially, W=Weak

23. • C9:Ease of integration: Remodeling goals with design tools
– Causes information loss and inconsistencies
– Consumes too much development effort and time (duplication of
work)
• C3:Traceability : Unmanageable traceability
– Hurt by low usability, low scalability and lack of model
synchronization
– Hurts consistency and completeness checks
– Hurts the change management process
• C6/C10: Cannot conduct goal-based reasoning or tradeoff analysis at
runtime.
23
Result

24. 24
W. Qian, X. Peng, B. Chen, J. Mylopoulos, H. Wang, and W. Zhao, “Rationalism with a dose of empiricism: combining goal reasoning
and case-based reasoning for self-adaptive software systems,” Requir. Eng., vol. 20, no. 3, pp. 233–252, 2015.
Goal-based reasoning supports Case-Based Approach
The Runtime Adaptation Support
No

25. Goal model extended with conditions
25
M. Morandini, L. Penserini, A. Perini, and A. Marchetto, “Engineering requirements for adaptive systems,” Requir. Eng., vol. 22, no. 1, 2017.
The Runtime Adaptation Support

26. 26
Baresi, L. and Pasquale, L. (2010a) Adaptive goals for self-adaptive service compositions. In Web Services (ICWS),
2010 IEEE international conference on, 353–360. IEEE.
The Runtime Adaptation Support
Analysis activity

27. 27
Goal-based reasoning was not used in strategy selection
Baresi, L. and Pasquale, L. (2010a) Adaptive goals for self-adaptive service compositions. In Web Services (ICWS),
2010 IEEE international conference on, 353–360. IEEE.
The Runtime Adaptation Support

28. 28
Assessment
Method C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11
Qian et al. (2015) - N N N N Y N - - P W
Morandini et al. (2017) - P P N P N N - - N W
Baresi and Pasquale
(2010a)
- P P N P N N - - P W
C1:Communication between Goals and SysML.
C2:Consistency and completeness.
C3:Traceability. (goal, req., design and code.)
C4:Scalability.
C5:Change management.
C6:Trade-off analysis and solutions.
Y=Yes, N=No, P=Partially, -=Does not exist, W= Weak
C7:Concurrent modeling
C8:Usability: Number of tools and
model import and export
C9:Ease of integration
C10:Goal reasoning and adaptation
C11:Adaptation type

29. 29
Adaptation
taxonomy
Qian et al.
(2015)
Morandini et al.
(2017)
Baresi and
Pasquale
(2010a)
Adaptation Type Open Closed Closed
Decision Dynamic Static Static
Approach Strategy Pre-made Pre-made Pre-made
Temporal Adaptation Reactive Proactive/Reactive Reactive
Adaptation Assessment
Adaptation taxonomy
Krupitzer, C., Roth, F. M., VanSyckel, S., Schiele, G. and Becker, C. (2015) A survey on engineering
approaches for self-adaptive systems. Pervasive and Mobile Computing, 17, 184–206.

30. 30
Adaptation Assessment
Goal dimension Qian et al. (2015)
Morandini et al.
(2017)
Baresi and
Pasquale (2010a)
Goal Evolution Static Static Dynamic
Flexibility Not constrained Constrained Constrained
Multiplicity Multiple Multiple Multiple
Timeliness Not guaranteed Guaranteed Not guaranteed
Goal dimension
Andersson, J., De Lemos, R., Malek, S. andWeyns, D. (2009) Modeling dimensions of self-adaptive software
systems. Software engineering for self-adaptive systems, 27–47.

31. • Goal models have been used in the adaptation processes of the
collected methods but their reasoning processes are
characterized as:
– Generating unsuitable solutions at times
– Spending unguaranteed times for adaptation (Modifying goals)
– Not dealing with unknown situations (Using conditions)
31
Goal Model at Runtime
• Goal-based reasoning is not used in all of the adaptation
process activities:
– Monitoring
– Analyzing (deciding about the need for adaptation)
– Planning or strategy selection

32. Conclusion
• Still managing complete traceability between
stakeholders goals, system requirements, design and
implementation artifacts is a challenge that faces all the
collected methods
• Using goal model in adaptation process improves
systems:
– Flexibility
– Ability to deal with unknown conditions at runtime
32

33. Conclusion
However, goal-based reasoning was often
incomplete, imprecise, or not used in all
Monitoring, Analysis, and Planning activities.
This hurts the ability of goal models to
support self-adaptation.
There are hence opportunities for
improvement!
33

34. Future Work
• Manage traceability between
stakeholders goals, requirements and
system design
• Support self-adaptation by integrating:
Goal and Features models
34
MAPE cycle
Simulation tools
The developed systems will be able to adapt while
monitoring their quality

35. Future Work
35
RMS
Control
Control
Manageable traceability
Acceleration
Acceleration

36. 36
Assessment of the Proposed Approach
C1:Communication between Goals and SysML.
C2:Consistency and completeness.
C3:Traceability (goal, req., design and code)
C4:Scalability.
C5:Change management.
C6:Trade-off analysis and solutions.
Y=Yes, N=No, P=Partially, -=Not exist, W=Weak
C7:Concurrent modeling
C8:Usability: Number of tools and
model import and export
C9:Ease of integration
C10:Goal reasoning and adaptation
C11:Adaptation type
Method C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11
The proposed
approach
Y Y Y Y Y Y N N P Y W

37. Adaptation strategies
Monitor
Analyze Plan
Environment
System
Decide to
adapt
Select the best
Execution
Strategy
Sensors
Nothing
wrong
Symptoms
Monitor
results
Data
37
Goal Reasoning Supports the MAPE Cycle
Future Work

38. 38
Support adaptation at design time
Future Work
Constraints
Objective function/s
Simulation
tools
Valid designs

39. 39
Assessment of the Proposed Approach
Adaptation
taxonomy
Adaptation
Type
Decision
Approach
Strategy
Temporal Adaptation
The proposed
approach
Simi-open Dynamic Pre-made Reactive/Proactive
Goal Dimension
Goal
Evolution
Flexibility Multiplicity Timeliness
The proposed
approach
Simi-dynamic Not constrained Multiple Guaranteed
Increase the flexibility Dealing
Unknown situation

40. Collaboration!
• We are looking for SysML users interested in
integrating goals with SysML models at design
time.
• Integrating goals with SysML models at
runtime, real examples of self-adaptive
systems that can be used as case studies
40

41. References
1. W. Qian, X. Peng, B. Chen, J. Mylopoulos, H. Wang, and W. Zhao, “Rationalism with a dose of
empiricism: combining goal reasoning and case-based reasoning for self-adaptive software
systems,” Requir. Eng., vol. 20, no. 3, pp. 233–252, 2015.
2. M. Morandini, L. Penserini, A. Perini, and A. Marchetto, “Engineering requirements for
adaptive systems,” Requir. Eng., vol. 22, no. 1, pp. 77–103, 2017.
3. D. Spyropoulos and J. S. Baras, “Extending Design Capabilities of SysML with Trade-off
Analysis: Electrical Microgrid Case Study,” Procedia Comput. Sci., vol. 16, pp. 108–117,
2013.
4. L. Apvrille and Y. Roudier, “SysML-Sec: A SysML environment for the design and
development of secure embedded systems,” APCOSEC, Asia-Pacific Counc. Syst. Eng., pp. 8–
11, 2013.
5. M. Ahmad and J.-M. Bruel, “A comparative study of RELAX and SysML/Kaos,” in Technical
Report, Institut de Recherche en Informatique de Toulouse, University Toulouse II Le Mirail,
France, 2014.
6. X. Cui and R. Paige, “An integrated framework for system/software requirements
development aligning with business motivations,” in Proceedings - 2012 IEEE/ACIS 11th
International Conference on Computer and Information Science, ICIS 2012, 2012, pp. 547–
552.
7. Baresi, L. and Pasquale, L. (2010a) Adaptive goals for self-adaptive service compositions. In
Web Services (ICWS), 2010 IEEE international conference on, 353–360. IEEE.
8. Kephart, Jeffrey O., and David M. Chess. "The vision of autonomic
computing." Computer 36.1 (2003): 41-50.
9. Amyot, D., Anda, A. A., Baslyman, M., Lessard, L. and Bruel, J. M. (2016) Towards Improved
Requirements Engineering with SysML and the User Requirements Notation. In 2016 IEEE
24th International Requirements Engineering Conference (RE), 329–334.
41

42. References
10. Ahmad, M., & Bruel, J.(2014) A comparative study of RELAX and SysML/Kaos. In Technical
Report. Institut de Recherche en Informatique de Toulouse, University Toulouse II Le Mirail,
France.
11. Andersson, J., De Lemos, R., Malek, S. andWeyns, D. (2009) Modeling dimensions of self-
adaptive software systems. Software engineering for self-adaptive systems, 27–47.
12. Krupitzer, C., Roth, F. M., VanSyckel, S., Schiele, G. and Becker, C. (2015) A survey on
engineering approaches for self-adaptive systems. Pervasive and Mobile Computing, 17, 184–
206.
13. Horváth, I. (2014) What the Design Theory of Social-Cyber-Physical Systems Must Describe,
Explain and Predict? In An Anthology of Theories and Models of Design, 99–120. Springer
14. Lace, K., & Kirikova, M. (2018). Required Changes in Requirements Engineering Approaches
for Socio-Cyber-Physical Systems.
42