1. Architectural Modeling and Domain-Specific Architecture
CS310 – Software Engineering

2. What to Model in Architectures?
Basic architectural elements
Components
Connectors
Interfaces
Configurations
Rationale – reasoning behind decisions

3. Important Characteristics of Models
A model is ambiguous if it is open to more than one interpretation
A model is accurate if it is correct, conforms to fact, or deviates from correctness within acceptable limits
A model is precise if it is sharply exact or delimited

4. Accuracy vs. Precision
Inaccurate and imprecise: incoherent or contradictory assertions
Accurate but imprecise: ambiguous or shallow assertions
Accurate and precise: detailed assertions that are correct
Inaccurate but precise: detailed assertions that are wrong

5. Views and Viewpoints
Generally, it is not feasible to capture everything we want to model in a single model or document
The model would be too big, complex, and confusing
So, we create several coordinated models, each capturing a subset of the design decisions
Generally, the subset is organized around a particular concern or other selection criteria
We call the subset-model a ‘view’ and the concern (or criteria) a ‘viewpoint’

6. Views and Viewpoints Example
Deployment view of a 3-tier application
Deployment view of a Lunar Lander system
Both instances of the deployment viewpoint

7. Commonly-Used Viewpoints
Logical Viewpoints
Capture the logical (often software) entities in a system and how they are interconnected.
Physical Viewpoints
Capture the physical (often hardware) entities in a system and how they are interconnected.
Deployment Viewpoints
Capture how logical entities are mapped onto physical entities.

8. Commonly-Used Viewpoints (cont’d)
Concurrency Viewpoints
Capture how concurrency and threading will be managed in a system.
Behavioral Viewpoints
Capture the expected behavior of (parts of) a system.

9. Example of View Inconsistency

10. Many Modeling-Language Options
Generic approaches
Natural language
PowerPoint-style modeling
UML, the Unified Modeling Language
Early architecture description languages
Darwin
Rapide
Wright
Domain- and style-specific languages
Koala
Weaves
AADL
Extensible architecture description languages
Acme
ADML
xADL

11. Natural Language Spoken/written languages such as English Advantages
Highly expressive
Accessible to all stakeholders
Good for capturing non-rigorous or informal architectural elements like rationale and non-functional requirements
Plentiful tools available (word processors and other text editors)
Disadvantages
Ambiguous, non-rigorous, non-formal
Often verbose
Cannot be effectively processed or analyzed by machines/software

12. Natural Language Example
“The Lunar Lander application consists of three components: a data store component, a calculation component, and a user interface component.
The job of the data store component is to store and allow other components access to the height, velocity, and fuel of the lander, as well as the current simulator time.
The job of the calculation component is to, upon receipt of a burn-rate quantity, retrieve current values of height, velocity, and fuel from the data store component, update them with respect to the input burn-rate, and store the new values back. It also retrieves, increments, and stores back the simulator time. It is also responsible for notifying the calling component of whether the simulator has terminated, and with what state (landed safely, crashed, and so on).
The job of the user interface component is to display the current status of the lander using information from both the calculation and the data store components. While the simulator is running, it retrieves the new burn-rate value from the user, and invokes the calculation component.”

13. Related Alternatives
Ambiguity can be reduced and rigor can be increased through the use of techniques like ‘statement templates,’ e.g.:
The (name) interface on (name) component takes (list-of-elements) as input and produces (list-of-elements) as output (synchronously | asynchronously).
This can help to make rigorous data easier to read and interpret, but such information is generally better represented in a more compact format

14. Informal Graphical Modeling
General diagrams produced in tools like PowerPoint and OmniGraffle
Advantages
Can be aesthetically pleasing
Size limitations (e.g., one slide, one page) generally constrain complexity of diagrams
Extremely flexible due to large symbolic vocabulary
Disadvantages
Ambiguous, non-rigorous, non-formal
But often treated otherwise
Cannot be effectively processed or analyzed by machines/software

15. Informal Graphical Model Example

16. UML – the Unified Modeling Language
13 loosely-interconnected notations called diagrams that capture static and dynamic aspects of software-intensive systems
Advantages
Support for a diverse array of viewpoints focused on many common software engineering concerns
Ubiquity improves comprehensibility
Extensive documentation and tool support from many vendors
Disadvantages
Needs customization through profiles to reduce ambiguity
Difficult to assess consistency among views
Difficult to capture foreign concepts or views

17. UML Example
Software Architecture: Foundations, Theory, and Practice; Richard N. Taylor, Nenad Medvidovic, and Eric M. Dashofy; © 2010 John Wiley & Sons, Inc. Reprinted with permission.

18. Domain-Specific Software Engineering
The traditional view of software engineering shows us how to come up with solutions for problems de novo
But starting from scratch every time is infeasible
This will involve re-inventing many wheels
Once we have built a number of systems that do similar things, we gain critical knowledge that lets us exploit common solutions to common problems
In theory, we can simply build “the difference” between our new target system and systems that have come before

19. Examples of Domains Compilers for programming languages
Consumer electronics
Electronic commerce system/Web stores
Video game
Business applications
Basic/Standard/“Pro”
We can subdivide, too:
Avionics systems
Boeing Jets
Boeing

20. Traditional Software Engineering
One particular problem can be solved in innumerable ways

21. Architecture-Based Software Engineering
Given a single problem, we select from a handful of potential architectural styles or architectures, and go from these into specific implementations

22. Domain-Specific Software Engineering
We map regions of the problem space (domains) into domain-specific software architectures (DSSAs)
These are specialized into application-specific architectures
These are implemented

23. Three Key Factors of DSSE
Domain
Must have a domain to constrain the problem space and focus development
Technology
Must have a variety of technological solutions—tools, patterns, architectures & styles, legacy systems—to bring to bear on a domain
Business
Business goals motivate the use of DSSE
Minimizing costs: reuse assets when possible
Maximize market: develop many related applications for different kinds of end users

24. Becoming More Concrete
Applying DSSE means developing a set of artifacts more specific than an ordinary software architecture
Focus on aspects of the domain
Focus on domain-specific solutions, techniques, and patterns
These are
Domain Model
Reference Requirements
Reference Architecture

25. Domain Model
A domain model is a set of artifacts that capture information about a domain
Functions performed
Objects (also known as entities) that perform the functions, and on which the functions are performed
Data and information that flows through the system
Standardizes terminology and semantics
Provides the basis for standardizing (or at least normalizing) descriptions of problems to be solved in the domain

26. (Partial) Domain Dictionary
Lunar Module (LM): this is the portion of the spacecraft that lands on the moon. It consists of two main parts: the Ascent Stage (which holds the crew cabin) and the Descent Stage, which contains thrusters used for controlling the landing of the LM.
Reaction Control System (RCS): a system on the Lunar Module responsible for the stabilization during lunar surface ascent/descent and control of the spacecraft’s orientation (attitude) and motion (translation) during maneuvers
Vertical velocity (see also One-dimensional motion):
For a free-falling object with no air resistance, ignoring the rotation of the lunar surface, the altitude is calculated as follows:
y = ½ * a * t2 + vi * t + yi
y = altitude
a = constant acceleration due to gravity on a lunar body (see Acceleration for sample values)
t = time in seconds; vi = initial velocity; yi = initial altitude
When thrust is applied, the following equation is used:
y = ½ * (aburner – agravity) * t2 + vi * t + yi
aburner = constant acceleration upward due to thrust
agravity = constant acceleration due to gravity on a lunar
(see Acceleration for sample values)

27. Info Model: Context Info Diagram
Defines high-level entities
Defines what is considered inside and outside the domain (or subdomains)
Defines relationships and high-level flows

28. Info Model: Entity-Relationship Diagram
Defines entities and cardinal relationships between them

29. Info Model: Object Diagram
Defines attributes and operations on entities
Closely resembles class diagram in UML but may be more abstract

30. Feature Model: Feature Relationship Diagram
Feature Relationship Diagram – Landing Phase
Mandatory: The Lunar Lander must continually read altitude from the Landing Radar and relay that data to Houston with less than 500 msec of latency. Astronauts must be able to control the descent of the Lunar Lander using manual control on the descent engine. The descent engine must respond to control commands in 250msec, with or without a functioning DSKY…
Optional/Variant: Lunar Lander provides the option to land automatically or allow the crew to manually steer the spacecraft.
Quality Requirements:
Real-time requirements: The thrusters and the descent engine must be able to respond to commands from the computer system in real-time.
Fault tolerance: Lunar Lander must be able to continue in its flight-path even when the main computer system (Primary Navigation Guidance & Control) goes down. Lunar Lander must be able to maintain system altitude even when one of the thrusters and propellant supplies goes down in the Reaction Control System.
Describes overall mission operations of a system
Describes major features and decomposition

31. Feature Model: Use Case Diagram
Defines use cases within the domain
Similar to use case models in UML

32. Feature Model: Representation Diagram
Defines how information is presented to human users

33. Operational Model: Data Flow Diagram
Focuses on data flow between entities with no notion of control

34. Operational Model: Control Flow Diagram
Focuses on control flow between entities separate from data flow

35. Operational Model: State Transition Diagram
Focuses on states of systems and transitions between them
Resembles UML state diagrams

36. Reference Requirements
Mandatory
Must display the current status of the Lunar Lander (horizontal and vertical velocities, altitude, remaining fuel)
Must indicate points earned by player based on quality of landing
Optional
May display time elapsed
Variant
May have different levels of difficulty based on pilot experience (novice, expert, etc)
May have different types of input depending on whether
Auto Navigation is enabled
Auto Throttle is enabled
May have to land on different celestial bodies
Moon
Mars
Jupiter’s moons
Asteroid
Software Architecture: Foundations, Theory, and Practice; Richard N. Taylor, Nenad Medvidovic, and Eric M. Dashofy; (C) 2008 John Wiley & Sons, Inc. Reprinted with permission.

37. Reference Architecture
Definition. Reference architecture is the set of principal design decisions that are simultaneously applicable to multiple related systems, typically within an application domain, with explicitly defined points of variation.
Reference architectures are still architectures (since they are also sets of principal design decisions)
Distinguished by the presence of explicit points of variation (explicitly “unmade” decisions)

38. Example Reference Architecture
Structural view of Lunar Lander DSSA
Invariant with explicit points of variation
Satellite relay
Sensors

39. Product Lines
A set of related products that have substantial commonality
In general, the commonality exists at the architecture level
One potential ‘silver bullet’ of software engineering
Power through reuse of
Engineering knowledge
Existing product architectures, styles, patterns
Pre-existing software components and connectors

40. Business vs. Engineering Product Lines
Business Product Line
A set of products marketed under a common banner to increase sales and market penetration through bundling and integration
Engineering Product Line
A set of products that have substantial commonality from a technical/engineering perspective
Generally, business product lines are engineering product lines and vice-versa, but not always
Applications bundled after a company acquisition
Chrysler Crossfire & Mercedes SLK V6

41. A Business or Engineering Product Line?
40% reuse of Mercedes parts in the Crossfire

42. Business Motivation for Product Lines
Traditional Software Engineering

43. Business Motivation for Product Lines
Traditional Software Engineering

44. Business Motivation for Product Lines
Product Line-Based Software Engineering

45. Capturing Product Line Architectures
Common: features common to all products
A: features specific to product A
B: features specific to product B
Product A = Common + A
Product B = Common + B

46. A Product-Line Architecture
Definition: A product-line architecture captures the architectures of many related products simultaneously
Generally employs explicit variation points in the architecture indicating where design decisions may diverge from product to product

47. Remember This?

48. Growing Sophistication of Consumer Devices

49. Families of Related Products

50. Philips’ Solution – Architecture

51. Case Study – Call Center Customer Care

52. Some Additional Resources
The entire deck is great, but particularly interesting are things starting on slide titled “ARCHITECTURAL DESIGN-1”