Software Architecture

Chapter 10
Architectural Design
CHAPTER OVERVIEW AND COMMENTS

The intent of this chapter is to provide a systematic approach for the derivation of the architectural design.  Architectural design encompasses both the data architecture and the program structure layers of the design model.  A general introduction to software architecture is presented.  Examples are presented to illustrate the use of transform mapping and transaction mapping as means of building the architectural model using structured design approach.

10.1 Software Architecture

This section defines the term “software architecture” as a framework made up of the system structures that comprise the software components, their properties, and the relationships among these components. The goal of the architectural model is to allow the software engineer to view and evaluate the system as a whole before moving to component design.
10.1.1 What is Architecture?
The architecture is not the operational software. Rather, it is a representation that enables a software engineer to:
(1) Analyze the effectiveness of the design in meeting its stated requirements,
(2) Consider architectural alternatives at a stage when making design changes is still relatively easy, and
(3) Reduce the risks associated with the construction of the software.

10.1.2 Why is Architecture Important?

• Representations of software architecture are an enabler for communication between all parties (stakeholders) interested in the development of a computer-based system.
• The architecture highlights early design decisions that will have a profound impact on all software engineering work that follows and, as important, on the ultimate success of the system as an operational entity.
• Architecture “constitutes a relatively small, intellectually graspable model of how the system is structured and how its components work together” [BAS03].

 

10.2 Data Design

This section describes data design at both the architectural and component levels. At the architecture level, data design is the process of creating a model of the information represented at a high level of abstraction (using the customer's view of data).

10.2.1 Data Design at the Architectural Level

The challenge is extract useful information from the data environment, particularly when the information desired is cross-functional.

To solve this challenge, the business IT community has developed data mining techniques, also called knowledge discovery in databases (KDD), that navigate through existing databases in an attempt to extract appropriate business-level information.

However, the existence of multiple databases, their different structures, the degree of detail contained with the databases, and many other factors make data mining difficult within an existing database environment.

An alternative solution, called a data warehouse, adds on additional layer to the data architecture.

A data warehouse is a separate data environment that is not directly integrated with day-to-day applications that encompasses all data used by a business.

In a sense, a data warehouse is a large, independent database that has access to the data that are stored in databases that serve as the set of applications required by a business.

10.2.2 Data Design at the Component Level

At the component level, data design focuses on specific data structures required to realize the data objects to be manipulated by a component.

• refine data objects and develop a set of data abstractions
• implement data object attributes as one or more data structures
• review data structures to ensure that appropriate relationships have been established
• simplify data structures as required

 

Set of principles for data specification:

1.   The systematic analysis principles applied to function and behavior should also be applied to data.
2.   All data structures and the operations to be performed on each should be identified.
3.   A data dictionary should be established and used to define both data and program design.  
4.   Low level data design decisions should be deferred until late in the design process.
5.   The representation of data structure should be known only to those modules that must make direct use of the data contained within the structure.
6.   A library of useful data structures and the operations that may be applied to them should be developed.
7.   A software design and programming language should support the specification and realization of abstract data types.  

10.3 Architectural Styles and Patterns

Each style describes a system category that encompasses:

(1) A set of components (e.g., a database, computational modules) that perform a function required by a system,
(2) A set of connectors that enable “communication, coordination and cooperation” among components,
(3) Constraints that define how components can be integrated to form the system, and
(4) Semantic models that enable a designer to understand the overall properties of a system by analyzing the known properties of its constituent parts.

An architectural style is a transformation that is imposed on the design of an entire system.

An architectural pattern, like an architectural style, imposes a transformation on the design of an architecture.

 A pattern differs from a style in a number of fundamental ways:

• The scope of a pattern is less broad, focusing on one aspect of the architecture rather than the architecture in its entirety.
• A pattern imposes a rule on the architecture, describing how the S/W will handle some aspect of its functionality at the infrastructure level.
• Architectural patterns tend to address specific behavioral issues within the context of the architectural.

 

 

10.3.1 A Brief Taxonomy of Architectural Styles

Styles can be categorized as follows:

Data-Centered Architecture

A data store resides at the center of this architecture and is accessed frequently by other components that update, add, delete, or otherwise modify data within the store.

This architecture promotes integrability.  Existing components can be changed and new client components can be added to the architecture without concern about other clients.

 

 

 

 

 

 

 

 

 

Data-flow Architecture

This architecture is applied when input data are to be transformed through a series of computational or manipulative components into output data.

A pipe and filter structure has a set of components, called filters, connected by pipes that transmit data from one component to the next.

 

 

 

 

 

 

 

 

 

 

Call and Return architecture

The architectural style enables a S/W designer to achieve a program structure that is relatively easy to modify and scale.

• Main program/subprogram architecture.
• Remote procedure-call architecture.

 

 

10.3.2 Architectural Patterns

A S/W architecture may have a number of architectural patterns that address issues such as concurrency, persistence, and distribution.

• Concurrency—applications must handle multiple tasks in a manner that simulates parallelism
•  operating system process management pattern
• task scheduler pattern
• Persistence—Data persists if it survives past the execution of the process that created it.  Persistent data are stored in a database or file and may be read and modified by other processes at a later time.

            Two patterns are common:

• a database management system pattern that applies the storage and retrieval capability of a DBMS to the application architecture
• an application level persistence pattern that builds persistence features into the application architecture
• Distribution— the manner in which systems or components within systems communicates with one another in a distributed environment, and the nature of the communication that occurs.
• A broker acts as a ‘middle-man’ between the client component and a server component.

10.4 Architectural Design

The architectural design process begins by representing the system in context.
10.4.1 Representing the System in Context

Architectural context represents how the S/W interacts with entities external to its boundaries.

The design should define the external entities (other systems, devices, people) that the software interacts with and the nature of the interaction

 

 

 

 

 

 

 

 

 

 

10.4.1 Defining Archetypes

• An archetype is an abstraction (similar to a class) that represents one element of system behavior
• The designer specifies the structure of the system by defining and refining software components that implement each archetype

 

 

 

 

 

 

 

 

 

 

10.5 Analyzing Alternative Architectural Designs

10.5.1 An Architecture Trade-off Analysis Method

The SEI has developed an Architecture Trade-off Analysis Method (ATAM) that established an iterative evaluation process for S/W architecture:

1.  Collect scenarios.
2.  Elicit requirements, constraints, and environment description.
3.  Describe the architectural styles/patterns that have been chosen to address the scenarios and requirements:
• module view
• process view
• data flow view
4.  Evaluate quality attributes by considered each attribute in isolation.
5.  Identify the sensitivity of quality attributes to various architectural attributes for a specific architectural style.
6.  Critique candidate architectures (developed in step 3) using the sensitivity analysis conducted in step 5.  

10.5 Mapping Data Flow into Software Architecture

This section describes the general process of mapping requirements into software architectures during the structured design process.  The technique described in this chapter is based on analysis of the data flow diagram discussed in Chapter 8.

An Architectural Design Method

customer requirements

four bedrooms, three baths, lots of glass…

Deriving Program Architecture

Partitioning the Architecture

horizontal” and “vertical” partitioning are required

 

 

 

 

 

 

 

 

Horizontal Partitioning

• define separate branches of the module hierarchy for each major function
• use control modules to coordinate communication between functions

 

 

 

 

 

 

 

Vertical Partitioning:
Factoring

• design so that decision making and work are stratified
• decision making modules should reside at the top of the architecture

 

 

 

 

 

 

Why Partitioned Architecture?

• results in software that is easier to test
• leads to software that is easier to maintain
• results in propagation of fewer side effects
• results in software that is easier to extend

 

• objective: to derive a program architecture that is partitioned
• approach:
• the DFD is mapped into a program architecture
• the PSPEC and STD are used to indicate the content of each module
• notation:  structure chart

Flow Characteristics

General Mapping Approach

Isolate incoming and outgoing flow boundaries; for transaction flows, isolate the transaction center.
Working from the boundary outward, map DFD transforms into corresponding modules.
Add control modules as required.
Refine the resultant program structure using effective modularity concepts.

 

 

 

 

 

 

 

 

 

 

Factoring

 

 

 

 

 

 

 

First Level Factoring

 

 

 

 

 

 

Second Level Mapping

 

 

 

 

 

 

 

 

Transaction Flow

 

 

 

 

 

 

 

 

 

 

 

 

 

Refining the Analysis Model

• Write an English language processing narrative for the level 01 flow model
• Apply noun/verb parse to isolate processes, data items, store and entities
• Develop level 02 and 03 flow models
• Create corresponding data dictionary entries
• Refine flow models as appropriate