1. Building System Models for RE
Chapter 13
Modeling System Operations

2. Modeling Instance Behaviors
Scenarios as UML Sequence Diagrams

3. Modeling Instance Behaviors
Scenarios as UML Sequence Diagrams

5. Scenario Refinement Episodes Agent Decomposition Illustrate sub-goals
Consider coarse-grained agent first, then refine
May involve coarse-grained interactions, rather than pure events.
May span successive states (macro-events)

8. Modeling Class Behaviors
State machines (SM) complement scenarios:
Make state info explicit
Capture behavior of agent of any instance, not just a specific instance
Capture all admissible sequences

9. Modeling Class Behaviors
2 Types of State variables:
Snapshot State
Possible value for xi
SM State
Some variable always has the same value regardless of other differing state variable values
2 SM Event Types:
External – SM does not control
Internal – Controlled by agent associated with SM

10. Modeling Class Behaviors
State Machines as UML Diagrams

11. Modeling Class Behaviors
State Machines as UML Diagrams
Transitions labeled by events fire if an event occurs
Transitions with no labels fire automatically

12. Modeling Class Behaviors
Guarded Transitions
Captures necessary conditions for firing
Without an event label -> trigger condition

14. Modeling Class Behaviors
Actions
Auxiliary operation applied when transitions fire
Used to prescribe operations to be applied in specific circumstances
I.e. acquisition of knowledge, display of information to/from the environment, acknowledgement, etc.

16. Modeling Class Behaviors
Event Notifications
Allow transition between diagrams
Event is notified from producing diagram to consuming diagram
Entry/Exit Actions
Entry: action has to be applied when entering a state
Exit: Action has to be applied when leaving the state
* different from pre/post conditions, designates timing

18. Examples/Tips

19. Examples/Tips

20. State Machine Refinement: Sequential and Concurrent Sub-States
Sequential Decomposition: decompose SM into sub-states by new transitions
Recursive
Instance modeled is in super-state iff it is one and only one sub-state
Incoming transition to super-state is inherited by every sub-state as an incoming transition
Except when non-deterministic

21. State Machine Refinement: Sequential and Concurrent Sub-States
Parallel Decomposition
SM decomposed into concurrent sub-states
Requires KxN states rather than K^n due to concurrency
Models concurrent behavior of agent controlling multiple states in parallel
The instance modeled by the state diagram is in the super-state iff it is each concurrent sub-state.
Incoming transitions to super-state are inherited to all substates
Outgoing tranistion from super-state is inherited by every substate
If the outgoing transition has no event or guard label, it is fired when all implicit outgoing transitions have been fired.
If the outgoing transition has a guard/event label, it is fired when the event occurs provided the guard is true, forcing exit from all concurrent sub-states.

22. State Machine Refinement: Sequential and Concurrent Sub-States
Guidelines:
For each sub-diagram, insert a initial sub-state and a final sub-state for those that reach the desired state.
Structure diagrams: do not connect a sequential sub-state of a concurrent state to sequential sub-state of other concurrent states or outer super-states.
Check after decomposition to maintain synchronization. Make sure guards, events, etc. line up.

23. Building Behavior Models
Goals
capture functional and non-functional aspects
have AND/OR structures
Pros: Support reasoning in early RE, provide conflict management, threat analysis, evaluation of alternatives, responsibility assignment, animation, requirements doc. generation.
Cons: Viewed as too abstract, behaviors left implicit, hard to elicit, hard to make precise.
See p. 464, table 13.1

24. Building Behavior Models
Scenarios
informal, narrative.
Pros: easy for stakeholders to understand, provide acceptance tests for free.
Cons: inherently partial, cover few behaviors of specific instances, require large# of scenarios.
See p. 464, table 13.1

25. Building Behavior Models
State Machines
Visual abstractions of explicit behaviors.
Pros: can be formally verified, yield counterexamples when problems are encountered, good basis for code generation
Cons: too operational too early in the RE process, difficult to build, too implicit.
See p. 464, table 13.1